ssghule/Optical-Character-Recognition-using-Hidden-Markov-Models
This project aims to recognize text from images using Hidden Markov Models and Viterbi algorithm
This project helps you identify individual characters within images of text, especially when the font and size are already known. You provide an image containing a text string and a representative text document for the language (e.g., English), and it outputs the recognized text using different character recognition methods. This is useful for researchers or students working on fundamental optical character recognition problems.
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Use this if you need to recognize text from images where you know the exact font and font size, and you're interested in how Hidden Markov Models can be applied to this specific task.
Not ideal if you need a robust, general-purpose OCR solution for varied documents with unknown fonts, sizes, or complex layouts.
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Python
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Last pushed
Dec 31, 2017
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