text:
Redraw an image with just one closed curve
Inspired by vi.sualize.us
Goal
The input is a grayscale image and the output is a black and white image. The output image consists of just one closed curve (loop) that is not allowed to intersect with itself or touch itself. The width of the line shall be constant throughout the whole image. The challenge here is finding an algorithm for doing so. The output just has to represent the input image, but with any artistic freedom. The resolution is not so important but the aspect ratio should stay about the same.
Example

More test images

You might want to put some restriction on the relative resolutions. Otherwise one could just increase the resolution considerably (say a factor of 32 or something), and then replace each pixel with a 32x32 block of appropriate average intensity. It should be easy enough to make the blocks all connect and them arrange them in such a way that everything connects to a single loop.

Does touching count as intersecting?

@Calvin'sHobbies Yes I think the line should not touch itself. @ Martin Büttner Well that would be a perfectly fine solution if you first decrease the image to a low resolution! But what limits would you recommend?

If the line can't touch itself, no dark areas, the darker shade will be a 50% gray

@edc65 You can get it darker than that by making the line wider than a pixel, but yeah you won't get black.

@Martin The width of the line shall be constant throughout the whole image. But still a useful hint

@edc65 Yes constant, but you can still make it wider than a pixel (constantly) in which case you can have two parts of the line separated by one pixel and then that area will be darker than 50% average intensity.

Does no touching include no diagonal touching at corners? That is, can the line pass through (x,y) and later pass through (x+1,y+1)?

Answers to this question might be very useful inspiration for use in answers to the black and white forest question.

The example line image contains anti-aliasing (greyscale to smooth the edges of the line). Is this permitted in answers or must the output images contain only 2 types of pixel, pure black and pure white?

@githubphagocyte Primarly the image should be in black and white, but it does not matter if it contains anti aliasing effects. And you should try to avoid this situation of diagonally touching pixels, but again, if this happens only a few times in the image it will be ok, as long as you do not use it systematically. Thank you for the input. @ edc65: Yes I am aware of that, the goal is that the viewer can still identify one distinct line on the image (when zooming in).

I would like to see the curve shortening flow of the generated images

@DenDenDo Is there a general algorithm for this task? I imagine that you e.g. try to locally reduce the curvature in each step, but I have no idea how to implment this.

@flawr If the curve has a parametric representation (x(t); y(t)) (or is stored as an ordered set of points) then you can compute the tangent vector (basically velocity of a point moving along the curve) ( x(t)'; y(t)') and the curvature (acceleration) (x(t)'';  y(t)'') and then move each point in the direction of the acceleration vector. Optionally add some scaling to preserve the total curve length or enclosed area. (too bad the math tags dont work here)

Oh that isn't even as difficult as I imagined it. So if any of the submitters would provide an ordered list of the corner points of their curves, I'd give it a try!

So I made a script in matlab for doing so, and it works (Amazing, @DenDenDo thank you for showing us this great effect=) now I'd just need a list of the points.

As interesting as that collapsing GIF is, have you considered posting it with the frames in reverse order and a pause at the end when the image has come into focus...?

Haha, no, but thats a nice idea! Let's see what I can do.

The "Update" doesn't make any sense without reading the comments (which are after it in the page rendering order), and mentioning one answer in the question seems like a way of biasing votes towards that answer (which should be done by accepting it, if it's the best according to the scoring criteria, or by mentioning it in chat otherwise ;) ). Perhaps move it to a link in the comments?

I didn't even think so far, just had fun fiddling around=) This is the backwards animation as suggested by @githubphagocyte: http://i.stack.imgur.com/muMWd.gif

Java : Dot matrix style
Since nobody has answered the question yet I'll give it a shot. First I wanted to fill a canvas with Hilbert curves, but in the end I've opted for a simpler approach:

Here is the code:
import java.awt.Color;
import java.awt.Dimension;
import java.awt.Graphics;
import java.awt.Graphics2D;
import java.awt.image.BufferedImage;
import java.io.File;

import javax.imageio.ImageIO;
import javax.swing.JFrame;
import javax.swing.JPanel;
import javax.swing.JScrollPane;

public class LineArt extends JPanel {
    private BufferedImage ref;
    //Images are stored in integers:
    int[] images = new int[] {31, 475, 14683, 469339};
    int[] brightness = new int[] {200,170,120,0};

    public static void main(String[] args) throws Exception {
        new LineArt(args[0]);
    }

    public LineArt(String filename) throws Exception {
        ref = ImageIO.read(new File(filename));
        JFrame frame = new JFrame();
        frame.setVisible(true);
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frame.setSize(ref.getWidth()*5, ref.getHeight()*5);
        this.setPreferredSize(new Dimension((ref.getWidth()*5)+20, (ref.getHeight()*5)+20));
        frame.add(new JScrollPane(this));
    }

    @Override
    public void paint(Graphics g) {
        Graphics2D g2d = (Graphics2D) g;
        g2d.setColor(Color.WHITE);
        g2d.fillRect(0, 0, getWidth(), getHeight());
        g2d.translate(10, 10);
        g2d.setColor(Color.BLACK);
        g2d.drawLine(0, 0, 4, 0);
        g2d.drawLine(0, 0, 0, ref.getHeight()*5);

        for(int y = 0; y<ref.getHeight();y++) {
            for(int x = 1; x<ref.getWidth()-1;x++) {
                int light = new Color(ref.getRGB(x, y)).getRed();
                int offset = 0;
                while(brightness[offset]>light) offset++;
                for(int i = 0; i<25;i++) {
                    if((images[offset]&1<<i)>0) {
                        g2d.drawRect((x*5)+i%5, (y*5)+(i/5), 0,0);
                    }
                }
            }
            g2d.drawLine(2, (y*5), 4, (y*5));
            g2d.drawLine((ref.getWidth()*5)-5, (y*5), (ref.getWidth()*5)-1, (y*5));
            if(y%2==0) {
                g2d.drawLine((ref.getWidth()*5)-1, (y*5), (ref.getWidth()*5)-1, (y*5)+4);
            } else {
                g2d.drawLine(2, (y*5), 2, (y*5)+4);
            }
        }
        if(ref.getHeight()%2==0) {
            g2d.drawLine(0, ref.getHeight()*5, 2, ref.getHeight()*5);
        } else {
            g2d.drawLine(0, ref.getHeight()*5, (ref.getWidth()*5)-1, ref.getHeight()*5);
        }
    }
}

Update: Now it creates a cycle, not just a single line

Very nice and simple solution, I didn't imagine that way of solving it but it looks great!

@DenDenDo suggested plotting a curve shortening flow animation. It would be great if you could provide a textfile (csv or whatever you want) with the coordinates of all conrner points that you used in the right order. I made a matlab script for calculating the animation - but of course you are also free to do it yourself=)

Python: Hilbert curve (373 361)
I decided to draw a Hilbert curve with variable granularity depending on the image intensity:
import pylab as pl
from scipy.misc import imresize, imfilter
import turtle

# load image
img = pl.flipud(pl.imread("face.png"))

# setup turtle
levels = 8
size = 2**levels
turtle.setup(img.shape[1] * 4.2, img.shape[0] * 4.2)
turtle.setworldcoordinates(0, 0, size, -size)
turtle.tracer(1000, 0)

# resize and blur image
img = imfilter(imresize(img, (size, size)), 'blur')

# define recursive hilbert curve
def hilbert(level, angle = 90):
    if level == 0:
        return
    if level == 1 and img[-turtle.pos()[1], turtle.pos()[0]] > 128:
        turtle.forward(2**level - 1)
    else:
        turtle.right(angle)
        hilbert(level - 1, -angle)
        turtle.forward(1)
        turtle.left(angle)
        hilbert(level - 1, angle)
        turtle.forward(1)
        hilbert(level - 1, angle)
        turtle.left(angle)
        turtle.forward(1)
        hilbert(level - 1, -angle)
        turtle.right(angle)

# draw hilbert curve
hilbert(levels)
turtle.update()

Actually I planned to make decisions on different levels of detail, like "This spot is so bright, I'll stop the recursion and move to the next block!". But evaluating image intensity locally leading to large movements is very inaccurate and looks ugly. So I ended up with only deciding whether to skip level 1 or to draw another Hilbert loop.
Here is the result on the first test image:

Thanks to @githubphagocyte the rendering is pretty fast (using turtle.tracer). Thus I don't have to wait all night for a result and can go to my well-deserved bed. :)

Some code golf
@flawr: "short program"? You haven't seen the golfed version! ;)
So just for fun:
from pylab import*;from scipy.misc import*;from turtle import*
i=imread("f.p")[::-1];s=256;h=i.shape;i=imfilter(imresize(i,(s,s)),'blur')
setup(h[1]*4.2,h[0]*4.2);setworldcoordinates(0,0,s,-s);f=forward;r=right
def h(l,a=90):
 x,y=pos()
 if l==1and i[-y,x]>128:f(2**l-1)
 else:
  if l:l-=1;r(a);h(l,-a);f(1);r(-a);h(l,a);f(1);h(l,a);r(-a);f(1);h(l,-a);r(a)
h(8)

(373 361 characters. But it will take forever since I remove the turte.tracer(...) command!)

Animation by flawr
flawr: My algorithm is slightly modified to what @DenDenDo told me: I had to delete some points in every iteration because the convergence would slow down drastically. That's why the curve will intersect itself.

Nicely done! If you want faster running, try screen.tracer(0) instead of turtle.speed(0). You might need to instantiate screen at the start, but if it's the only instance of screen all your turtles will automatically be assigned to it. Then just screen.update() at the end to display the results. I was amazed at the speed difference when I first discovered this...

I was really surprised that you were able to do it in such a short program! But anyway, congrats! fractals ftw=)

@DenDenDo suggested plotting a curve shortening flow animation. It would be great if you could provide a textfile (csv or whatever you want) with the coordinates of all conrner points that you used in the right order. I made a matlab script for calculating the animation - but of course you are also free to do it yourself=)

@flawr: Here we go.

So here's the code: http://pastebin.com/wTcwb0nm

Just realised the curve isn't closed. Should be straightforward to correct that since you have the end points on the outside.

Python 3.4 - Traveling Salesman Problem
The program creates a dithered image from the original:

For each black pixel a point is randomly generated near the pixel centre and these points are treated as a traveling salesman problem. The program saves an html file containing an SVG image at regular intervals as it attempts to reduce the path length. The path starts out self intersecting and gradually becomes less so over a number of hours. Eventually the path is no longer self intersecting:

'''
Traveling Salesman image approximation.
'''

import os.path

from PIL import Image   # This uses Pillow, the PIL fork for Python 3.4
                        # https://pypi.python.org/pypi/Pillow

from random import random, sample, randrange, shuffle
from time import perf_counter

def make_line_picture(image_filename):
    '''Save SVG image of closed curve approximating input image.'''
    input_image_path = os.path.abspath(image_filename)
    image = Image.open(input_image_path)
    width, height = image.size
    scale = 1024 / width
    head, tail = os.path.split(input_image_path)
    output_tail = 'TSP_' + os.path.splitext(tail)[0] + '.html'
    output_filename = os.path.join(head, output_tail)
    points = generate_points(image)
    population = len(points)
    save_dither(points, image)
    grid_cells = [set() for i in range(width * height)]
    line_cells = [set() for i in range(population)]
    print('Initialising acceleration grid')
    for i in range(population):
        recalculate_cells(i, width, points, grid_cells, line_cells)
    while True:
        save_svg(output_filename, width, height, points, scale)
        improve_TSP_solution(points, width, grid_cells, line_cells)

def save_dither(points, image):
    '''Save a copy of the dithered image generated for approximation.'''
    image = image.copy()
    pixels = list(image.getdata())
    pixels = [255] * len(pixels)
    width, height = image.size
    for p in points:
        x = int(p[0])
        y = int(p[1])
        pixels[x+y*width] = 0
    image.putdata(pixels)
    image.save('dither_test.png', 'PNG')

def generate_points(image):
    '''Return a list of points approximating the image.

    All points are offset by small random amounts to prevent parallel lines.'''
    width, height = image.size
    image = image.convert('L')
    pixels = image.getdata()
    points = []
    gap = 1
    r = random
    for y in range(2*gap, height - 2*gap, gap):
        for x in range(2*gap, width - 2*gap, gap):
            if (r()+r()+r()+r()+r()+r())/6 < 1 - pixels[x + y*width]/255:
                        points.append((x + r()*0.5 - 0.25,
                                       y + r()*0.5 - 0.25))
    shuffle(points)
    print('Total number of points', len(points))
    print('Total length', current_total_length(points))
    return points

def current_total_length(points):
    '''Return the total length of the current closed curve approximation.'''
    population = len(points)
    return sum(distance(points[i], points[(i+1)%population])
               for i in range(population))

def recalculate_cells(i, width, points, grid_cells, line_cells):
    '''Recalculate the grid acceleration cells for the line from point i.'''
    for j in line_cells[i]:
        try:
            grid_cells[j].remove(i)
        except KeyError:
            print('grid_cells[j]',grid_cells[j])
            print('i',i)
    line_cells[i] = set()
    add_cells_along_line(i, width, points, grid_cells, line_cells)
    for j in line_cells[i]:
        grid_cells[j].add(i)

def add_cells_along_line(i, width, points, grid_cells, line_cells):
    '''Add each grid cell that lies on the line from point i.'''
    population = len(points)
    start_coords = points[i]
    start_x, start_y = start_coords
    end_coords = points[(i+1) % population]
    end_x, end_y = end_coords
    gradient = (end_y - start_y) / (end_x - start_x)
    y_intercept = start_y - gradient * start_x
    total_distance = distance(start_coords, end_coords)
    x_direction = end_x - start_x
    y_direction = end_y - start_y
    x, y = start_x, start_y
    grid_x, grid_y = int(x), int(y)
    grid_index = grid_x + grid_y * width
    line_cells[i].add(grid_index)
    while True:
        if x_direction > 0:
            x_line = int(x + 1)
        else:
            x_line = int(x)
            if x_line == x:
                x_line = x - 1
        if y_direction > 0:
            y_line = int(y + 1)
        else:
            y_line = int(y)
            if y_line == y:
                y_line = y - 1
        x_line_intersection = gradient * x_line + y_intercept
        y_line_intersection = (y_line - y_intercept) / gradient
        x_line_distance = distance(start_coords, (x_line, x_line_intersection))
        y_line_distance = distance(start_coords, (y_line_intersection, y_line))
        if (x_line_distance > total_distance and
            y_line_distance > total_distance):
            break
        if x_line_distance < y_line_distance:
            x = x_line
            y = gradient * x_line + y_intercept
        else:
            y = y_line
            x = (y_line - y_intercept) / gradient
        grid_x = int(x - (x_direction < 0) * (x == int(x)))
        grid_y = int(y - (y_direction < 0) * (y == int(y)))
        grid_index = grid_x + grid_y * width
        line_cells[i].add(grid_index)

def improve_TSP_solution(points, width, grid_cells, line_cells,
                         performance=[0,0,0], total_length=None):
    '''Apply 3 approaches, allocating time to each based on performance.'''
    population = len(points)
    if total_length is None:
        total_length = current_total_length(points)

    print('Swapping pairs of vertices')
    if performance[0] == max(performance):
        time_limit = 300
    else:
        time_limit = 10
    print('    Aiming for {} seconds'.format(time_limit))
    start_time = perf_counter()
    for n in range(1000000):
        swap_two_vertices(points, width, grid_cells, line_cells)
        if perf_counter() - start_time > time_limit:
            break
    time_taken = perf_counter() - start_time
    old_length = total_length
    total_length = current_total_length(points)
    performance[0] = (old_length - total_length) / time_taken
    print('    Time taken', time_taken)
    print('    Total length', total_length)
    print('    Performance', performance[0])

    print('Moving single vertices')
    if performance[1] == max(performance):
        time_limit = 300
    else:
        time_limit = 10
    print('    Aiming for {} seconds'.format(time_limit))
    start_time = perf_counter()
    for n in range(1000000):
        move_a_single_vertex(points, width, grid_cells, line_cells)
        if perf_counter() - start_time > time_limit:
            break
    time_taken = perf_counter() - start_time
    old_length = total_length
    total_length = current_total_length(points)
    performance[1] = (old_length - total_length) / time_taken
    print('    Time taken', time_taken)
    print('    Total length', total_length)
    print('    Performance', performance[1])

    print('Uncrossing lines')
    if performance[2] == max(performance):
        time_limit = 60
    else:
        time_limit = 10
    print('    Aiming for {} seconds'.format(time_limit))
    start_time = perf_counter()
    for n in range(1000000):
        uncross_lines(points, width, grid_cells, line_cells)
        if perf_counter() - start_time > time_limit:
            break
    time_taken = perf_counter() - start_time
    old_length = total_length
    total_length = current_total_length(points)
    performance[2] = (old_length - total_length) / time_taken
    print('    Time taken', time_taken)
    print('    Total length', total_length)
    print('    Performance', performance[2])

def swap_two_vertices(points, width, grid_cells, line_cells):
    '''Attempt to find a pair of vertices that reduce length when swapped.'''
    population = len(points)
    for n in range(100):
        candidates = sample(range(population), 2)
        befores = [(candidates[i] - 1) % population
                   for i in (0,1)]
        afters = [(candidates[i] + 1) % population for i in (0,1)]
        current_distance = sum((distance(points[befores[i]],
                                         points[candidates[i]]) +
                                distance(points[candidates[i]],
                                         points[afters[i]]))
                               for i in (0,1))
        (points[candidates[0]],
         points[candidates[1]]) = (points[candidates[1]],
                                   points[candidates[0]])
        befores = [(candidates[i] - 1) % population
                   for i in (0,1)]
        afters = [(candidates[i] + 1) % population for i in (0,1)]
        new_distance = sum((distance(points[befores[i]],
                                     points[candidates[i]]) +
                            distance(points[candidates[i]],
                                     points[afters[i]]))
                           for i in (0,1))
        if new_distance > current_distance:
            (points[candidates[0]],
             points[candidates[1]]) = (points[candidates[1]],
                                       points[candidates[0]])
        else:
            modified_points = tuple(set(befores + candidates))
            for k in modified_points:
                recalculate_cells(k, width, points, grid_cells, line_cells)
            return

def move_a_single_vertex(points, width, grid_cells, line_cells):
    '''Attempt to find a vertex that reduces length when moved elsewhere.'''
    for n in range(100):
        population = len(points)
        candidate = randrange(population)
        offset = randrange(2, population - 1)
        new_location = (candidate + offset) % population
        before_candidate = (candidate - 1) % population
        after_candidate = (candidate + 1) % population
        before_new_location = (new_location - 1) % population
        old_distance = (distance(points[before_candidate], points[candidate]) +
                        distance(points[candidate], points[after_candidate]) +
                        distance(points[before_new_location],
                                 points[new_location]))
        new_distance = (distance(points[before_candidate],
                                 points[after_candidate]) +
                        distance(points[before_new_location],
                                 points[candidate]) +
                        distance(points[candidate], points[new_location]))
        if new_distance <= old_distance:
            if new_location < candidate:
                points[:] = (points[:new_location] +
                             points[candidate:candidate + 1] +
                             points[new_location:candidate] +
                             points[candidate + 1:])
                for k in range(candidate - 1, new_location, -1):
                    for m in line_cells[k]:
                        grid_cells[m].remove(k)
                    line_cells[k] = line_cells[k - 1]
                    for m in line_cells[k]:
                        grid_cells[m].add(k)
                for k in ((new_location - 1) % population,
                          new_location, candidate):
                    recalculate_cells(k, width, points, grid_cells, line_cells)
            else:
                points[:] = (points[:candidate] +
                             points[candidate + 1:new_location] +
                             points[candidate:candidate + 1] +
                             points[new_location:])
                for k in range(candidate, new_location - 3):
                    for m in line_cells[k]:
                        grid_cells[m].remove(k)
                    line_cells[k] = line_cells[k + 1]
                    for m in line_cells[k]:
                        grid_cells[m].add(k)
                for k in ((candidate - 1) % population,
                          new_location - 2, new_location - 1):
                    recalculate_cells(k, width, points, grid_cells, line_cells)
            return

def uncross_lines(points, width, grid_cells, line_cells):
    '''Attempt to find lines that are crossed, and reverse path to uncross.'''
    population = len(points)
    for n in range(100):
        i = randrange(population)
        start_1 = points[i]
        end_1 = points[(i + 1) % population]
        if not line_cells[i]:
            recalculate_cells(i, width, points, grid_cells, line_cells)
        for cell in line_cells[i]:
            for j in grid_cells[cell]:
                if i != j and i != (j+1)%population and i != (j-1)%population:
                    start_2 = points[j]
                    end_2 = points[(j + 1) % population]
                    if are_crossed(start_1, end_1, start_2, end_2):
                        if i < j:
                            points[i + 1:j + 1] = reversed(points[i + 1:j + 1])
                            for k in range(i, j + 1):
                                recalculate_cells(k, width, points, grid_cells,
                                                  line_cells)
                        else:
                            points[j + 1:i + 1] = reversed(points[j + 1:i + 1])
                            for k in range(j, i + 1):
                                recalculate_cells(k, width, points, grid_cells,
                                                  line_cells)
                        return

def are_crossed(start_1, end_1, start_2, end_2):
    '''Return True if the two lines intersect.'''
    if end_1[0]-start_1[0] and end_2[0]-start_2[0]:
        gradient_1 = (end_1[1]-start_1[1])/(end_1[0]-start_1[0])
        gradient_2 = (end_2[1]-start_2[1])/(end_2[0]-start_2[0])
        if gradient_1-gradient_2:
            intercept_1 = start_1[1] - gradient_1 * start_1[0]
            intercept_2 = start_2[1] - gradient_2 * start_2[0]
            x = (intercept_2 - intercept_1) / (gradient_1 - gradient_2)
            if (x-start_1[0]) * (end_1[0]-x) > 0 and (x-start_2[0]) * (end_2[0]-x) > 0:
                return True

def distance(point_1, point_2):
    '''Return the Euclidean distance between the two points.'''
    return sum((point_1[i] - point_2[i]) ** 2 for i in (0, 1)) ** 0.5

def save_svg(filename, width, height, points, scale):
    '''Save a file containing an SVG path of the points.'''
    print('Saving partial solution\n')
    with open(filename, 'w') as file:
        file.write(content(width, height, points, scale))

def content(width, height, points, scale):
    '''Return the full content to be written to the SVG file.'''
    return (header(width, height, scale) +
            specifics(points, scale) +
            footer()
            )

def header(width, height,scale):
    '''Return the text of the SVG header.'''
    return ('<?xml version="1.0"?>\n'
            '<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.0//EN"\n'
            '    "http://www.w3.org/TR/2001/REC-SVG-20010904/DTD/svg10.dtd">\n'
            '\n'
            '<svg width="{0}" height="{1}">\n'
            '<title>Traveling Salesman Problem</title>\n'
            '<desc>An approximate solution to the Traveling Salesman Problem</desc>\n'
            ).format(scale*width, scale*height)

def specifics(points, scale):
    '''Return text for the SVG path command.'''
    population = len(points)
    x1, y1 = points[-1]
    x2, y2 = points[0]
    x_mid, y_mid = (x1 + x2) / 2, (y1 + y2) / 2
    text = '<path d="M{},{} L{},{} '.format(x1, y1, x2, y2)
    for i in range(1, population):
        text += 'L{},{} '.format(*points[i])
    text += '" stroke="black" fill="none" stroke-linecap="round" transform="scale({0},{0})" vector-effect="non-scaling-stroke" stroke-width="3"/>'.format(scale)
    return text

def footer():
    '''Return the closing text of the SVG file.'''
    return '\n</svg>\n'

if __name__ == '__main__':
    import sys
    arguments = sys.argv[1:]
    if arguments:
        make_line_picture(arguments[0])
    else:
        print('Required argument: image file')

The program uses 3 different approaches to improving the solution, and measures the performance per second for each. The time allocated to each approach is adjusted to give the majority of time to whatever approach is best performing at that time.
I initially tried guessing what proportion of time to allocate to each approach, but it turns out that which approach is most effective varies considerably during the course of the process, so it makes a big difference to keep adjusting automatically.
The three simple approaches are:

Pick two points at random and swap them if this does not increase the total length.
Pick one point at random and a random offset along the list of points and move it if the length does not increase.
Pick a line at random and check whether any other line crosses it, reversing any section of path that causes a cross.

For approach 3 a grid is used, listing all of the lines that pass through a given cell. Rather than have to check every line on the page for intersection, only those that have a grid cell in common are checked.

I got the idea for using the traveling salesman problem from a blog post that I saw before this challenge was posted, but I couldn't track it down when I posted this answer. I believe the image in the challenge was produced using a traveling salesman approach too, combined with some kind of path smoothing to remove the sharp turns.
I still can't find the specific blog post but I have now found reference to the original papers in which the Mona Lisa was used to demonstrate the traveling salesman problem.
The TSP implementation here is a hybrid approach which I experimented with for fun for this challenge. I hadn't read the linked papers when I posted this. My approach is painfully slow by comparison. Note that my image here uses less than 10,000 points, and takes many hours to converge enough to have no crossing lines. The example image in the link to the papers uses 100,000 points...
Unfortunately most of the links seem to be dead now, but the paper "TSP Art" by Craig S Kaplan & Robert Bosch 2005 still works and gives an interesting overview of different approaches.

Wow, thats really nice=) (If you want me to do a curve shortening flow animation too just provide a csv or something similar with an ordered list of the point coordinates.)

@flawr thank you! As for the ordered list of point coordinates, it's almost 10,000 points for the mona lisa face. It would be nearer 100,000 points for the bigger images. That's why I haven't posted the SVG text here... :)

Well you could use pastebin.com or something similar, but I do not want to force you, it's your decision (I am not good at Python=)

@flawr I wouldn't want you to have to wait hours and hours for the program to run. I won't be adding a flow animation to my answer but if you want the points for yourself let me know and I can find somewhere to post them...

I would never had the idea of TSP for such thing! Get the upvote!

@sergiol it's not an original idea - the image in the challenge was produced using a TSP implementation, but looks smoother than mine as it uses some kind of path smoothing algorithm to avoid sharp corners. I remembered seeing the blog post explaining it before the challenge was posted, but couldn't track it down to link to when I posted my answer. The TSP implementation here is my own hybrid approach, but if anyone can find the original blog/paper then using their approach should give much faster results. Let me know if you do and I can link to it from the answer.

@sergiol 3 years later I've found some relevant links and edited them into the answer.

May be http://www2.oberlin.edu/math/faculty/bosch/ftb.pdf ?

@sergiol that link isn't working for me.

Strange ... it renders perfectly here.

This approach is the same as the example image in the original post, which is from original research by Kaplan and Bosch: 'TSP Art'.

Thanks @Angelorf . If you have a link to their work I can edit it into the answer for comparison. The approach is the same in that it is based on the the Travelling Salesman Problem, but my approach to dithering to generate the initial points, and my approaches to reducing the path length are different (more naive). Their approach gives significantly clearer and smoother results.

The last link in your post is already referencing 'TSP Art' by Kaplan and Bosch. It's good to be explicit in such references.

I've changed the link wording to include the names and date - does that cover what you meant?

Java - Oscillations
The program draws a closed path and add oscillations whose amplitude and frequency are based on image brightness. The "corners" of path do not have oscillations to make sure the path does not intersects itself.

package trace;

import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

import snake.Image;

public class Main5 {

    private final static int MULT = 3;
    private final static int ROWS = 80; // must be an even number
    private final static int COLS = 40;

    public static void main(String[] args) throws IOException {
        BufferedImage src = ImageIO.read(Image.class.getClassLoader().getResourceAsStream("input.png"));
        BufferedImage dest = new BufferedImage(src.getWidth()*MULT, src.getHeight()*MULT, BufferedImage.TYPE_INT_RGB);

        int [] white = {255, 255, 255};
        for (int y = 0; y < dest.getHeight(); y++) {
            for (int x = 0; x < dest.getWidth(); x++) {
                dest.getRaster().setPixel(x, y, white);
            }
        }
        for (int j = 0; j < ROWS; j++) {
            if (j%2 == 0) {
                for (int i = j==0 ? 0 : 1; i < COLS-1; i++) {
                    drawLine(dest, src, (i+.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS, (i+1.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS,
                            i > 1 && i < COLS-2);
                }

                drawLine(dest, src, (COLS-.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS, (COLS-.5)*dest.getWidth()/COLS, (j+1.5)*dest.getHeight()/ROWS, false);
            } else {
                for (int i = COLS-2; i >= (j == ROWS - 1 ? 0 : 1); i--) {
                    drawLine(dest, src, (i+.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS, (i+1.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS,
                            i > 1 && i < COLS-2);
                }
                if (j < ROWS-1) {
                    drawLine(dest, src, (1.5)*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS, (1.5)*dest.getWidth()/COLS, (j+1.5)*dest.getHeight()/ROWS, false);
                }
            }
            if (j < ROWS-1) {
                drawLine(dest, src, 0.5*dest.getWidth()/COLS, (j+.5)*dest.getHeight()/ROWS, 0.5*dest.getWidth()/COLS, (j+1.5)*dest.getHeight()/ROWS, false);
            }
        }
        ImageIO.write(dest, "png", new File("output.png"));
    }

    private static void drawLine(BufferedImage dest, BufferedImage src, double x1, double y1, double x2, double y2, boolean oscillate) {
        int [] black = {0, 0, 0};

        int col = smoothPixel((int)((x1*.5 + x2*.5) / MULT), (int)((y1*.5+y2*.5) / MULT), src);
        int fact = (255 - col) / 32;
        if (fact > 5) fact = 5;
        double dx = y1 - y2;
        double dy = - (x1 - x2);
        double dist = 2 * (Math.abs(x1 - x2) + Math.abs(y1 - y2)) * (fact + 1);
        for (int i = 0; i <= dist; i++) {
            double amp = oscillate ? (1 - Math.cos(fact * i*Math.PI*2/dist)) * 12 : 0;
            double x = (x1 * i + x2 * (dist - i)) / dist;
            double y = (y1 * i + y2 * (dist - i)) / dist;
            x += dx * amp / COLS;
            y += dy * amp / ROWS;
            dest.getRaster().setPixel((int)x, (int)y, black);
        }
    }

    public static int smoothPixel(int x, int y, BufferedImage src) {
        int sum = 0, count = 0;
        for (int j = -2; j <= 2; j++) {
            for (int i = -2; i <= 2; i++) {
                if (x + i >= 0 && x + i < src.getWidth()) {
                    if (y + j >= 0 && y + j < src.getHeight()) {
                        sum += src.getRGB(x + i, y + j) & 255;
                        count++;
                    }
                }
            }
        }
        return sum / count;
    }
}

Below a comparable algorithm that is based on a spiral. (I know the path does not close and that it certainly intersects, I just post it for the sake of art :-)

I particularly like the visual effect of the spiral!

Me too, thanks for sharing! (If you want you can also make a an ordered list of path points and I'll see whether I can do an animation with this one too=)

@github Thanks for your constructive comments.

+1 from me - it fits the rules perfectly now, and I love the smooth transitions that the changing frequency gives.

Java - Recursive Path
I start from a 2x3 closed path.
I scan each cell of the path and divide it into a new 3x3 sub-path. I try each time to choose the 3x3 sub-path that "looks like" the original picture.
I repeat the above process 4 times.

Here is the code:
package divide;

import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import javax.imageio.ImageIO;

import snake.Image;

public class Divide {

    private final static int MULT = 3;
    private final static int ITERATIONS = 4;

    public static void main(String[] args) throws IOException {
        BufferedImage src = ImageIO.read(Image.class.getClassLoader().getResourceAsStream("input.png"));
        BufferedImage dest = new BufferedImage(src.getWidth() * MULT, src.getHeight() * MULT, BufferedImage.TYPE_INT_RGB);
        for (int y = 0; y < src.getHeight() * MULT; y++) {
            for (int x = 0; x < src.getWidth() * MULT; x++) {
                dest.getRaster().setPixel(x, y, new int [] {255, 255, 255});
            }
        }
        List<String> tab = new ArrayList<String>();
        tab.add("rg");
        tab.add("||");
        tab.add("LJ");

        for (int k = 1; k <= ITERATIONS; k++) {
            boolean choose = k>=ITERATIONS-1;
            // multiply size by 3
            tab = iterate(src, tab, choose);
            // fill in the white space - if needed
            expand(src, tab, " r", " L", "r-", "L-", choose);
            expand(src, tab, "g ", "J ", "-g", "-J", choose);
            expand(src, tab, "LJ", "  ", "||", "LJ", choose);
            expand(src, tab, "  ", "rg", "rg", "||", choose);
            expand(src, tab, "L-J", "   ", "| |", "L-J", choose);
            expand(src, tab, "   ", "r-g", "r-g", "| |", choose);
            expand(src, tab, "| |", "| |", "Lg|", "rJ|", choose);
            expand(src, tab, "--", "  ", "gr", "LJ", choose);
            expand(src, tab, "  ", "--", "rg", "JL", choose);
            expand(src, tab, "| ", "| ", "Lg", "rJ", choose);
            expand(src, tab, " |", " |", "rJ", "Lg", choose);

            for (String s : tab) {
                System.out.println(s);
            }
            System.out.println();
        }

        for (int j = 0; j < tab.size(); j++) {
            String line = tab.get(j);
            for (int i = 0; i < line.length(); i++) {
                char c = line.charAt(i);
                int xleft = i * dest.getWidth() / line.length();
                int xright = (i+1) * dest.getWidth() / line.length();
                int ytop = j * dest.getHeight() / tab.size();
                int ybottom = (j+1) * dest.getHeight() / tab.size();
                int x = (xleft + xright) / 2;
                int y = (ytop + ybottom) / 2;
                if (c == '|') {
                    drawLine(dest, x, ytop, x, ybottom);
                }
                if (c == '-') {
                    drawLine(dest, xleft, y, xright, y);
                }
                if (c == 'L') {
                    drawLine(dest, x, y, xright, y);
                    drawLine(dest, x, y, x, ytop);
                }
                if (c == 'J') {
                    drawLine(dest, x, y, xleft, y);
                    drawLine(dest, x, y, x, ytop);
                }
                if (c == 'r') {
                    drawLine(dest, x, y, xright, y);
                    drawLine(dest, x, y, x, ybottom);
                }
                if (c == 'g') {
                    drawLine(dest, x, y, xleft, y);
                    drawLine(dest, x, y, x, ybottom);
                }
            }

        }

        ImageIO.write(dest, "png", new File("output.png"));

    }

    private static void drawLine(BufferedImage dest, int x1, int y1, int x2, int y2) {
        int dist = Math.max(Math.abs(x1 - x2), Math.abs(y1 - y2));
        for (int i = 0; i <= dist; i++) {
            int x = (x1*(dist - i) + x2 * i) / dist;
            int y = (y1*(dist - i) + y2 * i) / dist;
            dest.getRaster().setPixel(x, y, new int [] {0, 0, 0});
        }
    }

    private static void expand(BufferedImage src, List<String> tab, String p1, String p2, String r1, String r2, boolean choose) {
        for (int k = 0; k < (choose ? 2 : 1); k++) {
            while (true) {
                boolean again = false;
                for (int j = 0; j < tab.size() - 1; j++) {
                    String line1 = tab.get(j);
                    String line2 = tab.get(j+1);
                    int baseScore = evaluateLine(src, j, tab.size(), line1) + evaluateLine(src, j+1, tab.size(), line2);
                    for (int i = 0; i <= line1.length() - p1.length(); i++) {
                        if (line1.substring(i, i + p1.length()).equals(p1)
                                && line2.substring(i, i + p2.length()).equals(p2)) {
                            String nline1 = line1.substring(0,  i) + r1 + line1.substring(i + p1.length());
                            String nline2 = line2.substring(0,  i) + r2 + line2.substring(i + p2.length());
                            int nScore = evaluateLine(src, j, tab.size(), nline1) + evaluateLine(src, j+1, tab.size(), nline2);
                            if (!choose || nScore > baseScore) {
                                tab.set(j, nline1);
                                tab.set(j+1, nline2);
                                again = true;
                                break;
                            }
                        }
                    }
                    if (again) break;
                }
                if (!again) break;
            }
            String tmp1 = r1;
            String tmp2 = r2;
            r1 = p1;
            r2 = p2;
            p1 = tmp1;
            p2 = tmp2;
        }
    }

    private static int evaluateLine(BufferedImage src, int j, int tabSize, String line) {
        int [] color = {0, 0, 0};
        int score = 0;
        for (int i = 0; i < line.length(); i++) {
            char c = line.charAt(i);
            int x = i*src.getWidth() / line.length();
            int y = j*src.getHeight() / tabSize;
            src.getRaster().getPixel(x, y, color);
            if (c == ' ' && color[0] >= 128) score++;
            if (c != ' ' && color[0] < 128) score++;
        }
        return score;
    }

    private static List<String> iterate(BufferedImage src, List<String> tab, boolean choose) {
        int [] color = {0, 0, 0};
        List<String> tab2 = new ArrayList<String>();
        for (int j = 0; j < tab.size(); j++) {
            String line = tab.get(j);
            String l1 = "", l2 = "", l3 = "";
            for (int i = 0; i < line.length(); i++) {
                char c = line.charAt(i);
                List<String []> candidates = replace(c);
                String [] choice = null;
                if (choose) {

                    int best = 0;
                    for (String [] candidate : candidates) {
                        int bright1 = 0;
                        int bright2 = 0;
                        for (int j1 = 0; j1<3; j1++) {
                            int y = j*3+j1;
                            for (int i1 = 0; i1<3; i1++) {
                                int x = i*3+i1;
                                char c2 = candidate[j1].charAt(i1);
                                src.getRaster().getPixel(x*src.getWidth()/(line.length()*3), y*src.getHeight()/(tab.size()*3), color);
                                if (c2 != ' ') bright1++;
                                if (color[0] > 128) bright2++;
                            }
                        }
                        int score = Math.abs(bright1 - bright2);
                        if (choice == null || score > best) {
                            best = score;
                            choice = candidate;
                        }

                    }
                } else {
                    choice = candidates.get(0);
                }
                //String [] r = candidates.get(rand.nextInt(candidates.size()));
                String [] r = choice;
                l1 += r[0];
                l2 += r[1];
                l3 += r[2];
            }
            tab2.add(l1);
            tab2.add(l2);
            tab2.add(l3);
        }
        return tab2;
    }

    private static List<String []> replace(char c) {
        if (c == 'r') {
            return Arrays.asList(
                    new String[] {
                    "r-g",
                    "| L",
                    "Lg "},
                    new String[] {
                    "   ",
                    " r-",
                    " | "},
                    new String[] {
                    "   ",
                    "r--",
                    "Lg "},
                    new String[] {
                    " rg",
                    " |L",
                    " | "},
                    new String[] {
                    "   ",
                    "  r",
                    " rJ"});
        } else if (c == 'g') {
            return Arrays.asList(
                    new String[] {
                    "r-g",
                    "J |",
                    " rJ"},
                    new String[] {
                    "   ",
                    "-g ",
                    " | "},
                    new String[] {
                    "   ",
                    "--g",
                    " rJ"},
                    new String[] {
                    "rg ",
                    "J| ",
                    " | "},
                    new String[] {
                    "   ",
                    "g  ",
                    "Lg "});
        } else if (c == 'L') {
            return Arrays.asList(
                    new String[] {
                    "rJ ",
                    "| r",
                    "L-J"},
                    new String[] {
                    " | ",
                    " L-",
                    "   "},
                    new String[] {
                    "rJ ",
                    "L--",
                    "   "},
                    new String[] {
                    " | ",
                    " |r",
                    " LJ"},
                    new String[] {
                    " Lg",
                    "  L",
                    "   "});
        } else if (c == 'J') {
            return Arrays.asList(
                    new String[] {
                    " Lg",
                    "g |",
                    "L-J"},
                    new String[] {
                    " | ",
                    "-J ",
                    "   "},
                    new String[] {
                    " Lg",
                    "--J",
                    "   "},
                    new String[] {
                    " | ",
                    "g| ",
                    "LJ "},
                    new String[] {
                    "rJ ",
                    "J  ",
                    "   "});
        } else if (c == '-') {
            return Arrays.asList(
                    new String[] {
                    " rg",
                    "g|L",
                    "LJ "},
                    new String[] {
                    "rg ",
                    "J|r",
                    " LJ"},
                    new String[] {
                    "   ",
                    "---",
                    "   "},
                    new String[] {
                    "r-g",
                    "J L",
                    "   "},
                    new String[] {
                    "   ",
                    "g r",
                    "L-J"},
                    new String[] {
                    "rg ",
                    "JL-",
                    "   "},
                    new String[] {
                    " rg",
                    "-JL",
                    "   "},
                    new String[] {
                    "   ",
                    "gr-",
                    "LJ "},
                    new String[] {
                    "   ",
                    "-gr",
                    " LJ"}
                    );
        } else if (c == '|') {
            return Arrays.asList(
                    new String[] {
                    " Lg",
                    "r-J",
                    "Lg "},
                    new String[] {
                    "rJ ",
                    "L-g",
                    " rJ"},
                    new String[] {
                    " | ",
                    " | ",
                    " | "},
                    new String[] {
                    " Lg",
                    "  |",
                    " rJ"},
                    new String[] {
                    "rJ ",
                    "|  ",
                    "Lg "},
                    new String[] {
                    " Lg",
                    " rJ",
                    " | "},
                    new String[] {
                    " | ",
                    " Lg",
                    " rJ"},
                    new String[] {
                    "rJ ",
                    "Lg ",
                    " | "},
                    new String[] {
                    " | ",
                    "rJ ",
                    "Lg "}
                    );
        } else {
            List<String []> ret = new ArrayList<String []>();
            ret.add(
                    new String[] {
                    "   ",
                    "   ",
                    "   "});
            return ret;
        }

    }
}

This looks like one of the most innovative solutions so far! +1 for Batman=)

I love this one.

authors: Антония Малинова

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/