Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Image preprocessing and modified adaptive thresholding for improving OCR   In this paper I have proposed a method to find the major pixel intensity
inside the text and thresholding an image accordingly to make it easier to be
used for optical character recognition (OCR) models. In our method, instead of
editing whole image, I are removing all other features except the text
boundaries and the color filling them. In this approach, the grayscale
intensity of the letters from the input image are used as one of thresholding
parameters. The performance of the developed model is finally validated with
input images, with and without image processing followed by OCR by PyTesseract.
Based on the results obtained, it can be observed that this algorithm can be
efficiently applied in the field of image processing for OCR.

14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg