https://github.com/ghaiszaher/image-processing-ocr-walsh

A demonstration of using Walsh Functions to recognize characters in a clear image (without any noise, rotation or skew).
https://github.com/ghaiszaher/image-processing-ocr-walsh

Last synced: 26 days ago
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A demonstration of using Walsh Functions to recognize characters in a clear image (without any noise, rotation or skew).

• Host: GitHub
• URL: https://github.com/ghaiszaher/image-processing-ocr-walsh
• Owner: ghaiszaher
• Created: 2019-02-20T18:48:28.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-03-05T16:31:53.000Z (over 4 years ago)
• Last Synced: 2024-08-25T13:06:46.352Z (2 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 13.6 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Image-Processing-OCR-Walsh

This project contains a demonstration of using Walsh Functions to recognize characters in a clear image (without any noise, rotation or skew).

## Requirements

* Python3

* Jupyter Notebook

* Matplotlib

* Numpy

* Opencv2

* Pillow

* Difflib

## 01 - Generate Walsh Functions

The file "jupyter/01-generate_walsh_functions.ipynb" contains the generation of 64 matrices obtained using Walsh Transformation and saved to a json file. Each is a 64x64 matrix.

## 02 - Build Database

The file "jupyter/02-build_database.ipynb" uses Pillow to generate a database that contains a set of characters, and a "Walsh Vector" for each character (consists of 64 values). Steps for each character:

- Generate blank Image, write the character on it

- Use vertical and horizontal segmentation to isolate the character

- Resize the image to 64x64

- Apply "Inner Product" between the image and each of the walsh matrices, resulting with 64 values that are considered as the character's "Walsh Vector"

The database is saved in a json file.

Note: some combinations of more than 1 character are considered as a whole character here, because they're very close to each other in Times font.

## 03 - Characters Segmentation

The file "jupyter/03-characters_segmentation.ipynb" uses Walsh matrices and the generated database to predict the values of the segmented characters in an image. Steps:

- Vertical Segmentation: gets the start and end pixel of each line.

- Horizontal Segmentaion for each line: gets the start and end pixel of each character in that line.

- Vertical Segmentation for each character: to remove spaces above & below the character

- Resize the character to 64x64

- Calculate the Walsh Vector for the character

- Search for the closest vector in the database using Manhattan Distance, and set the prediction to the character belonging to this vector