Handwritten Digits and Optical Characters Recognition

Handwritten Digits Recognition

Optical Character Recognition: Classification of Handwritten Digits and Computer Fonts

Optical character Recognition (OCR) is an important application of machine learning where an algorithm is trained on a data set of known letters/digits and can learn to accurately classify letters/digits. A variety of algorithms have shown excellent accuracy for the problem of handwritten digits, 4 of which are looked at here. Additionally, we attempt to extend these techniques to the harder pr...

Handwritten digits recognition using OpenCV

The automated recognition of handwritten digits is a largely studied problem which connects the fields of Computer Vision and Machine Learning and has many applications in real life. In this project, I detail an introductory investigation of the performance of classification in several contexts. Namely, relying on the OpenCV implementations of k-Nearest Neighbor, Random Forests, and Support Vec...

Segmentation Based Optical Character Recognition for Handwritten Marathi characters

Valuable ancient documents like historical books, old scripts etc. are available in specific regional languages. Problems occur when those documents have to be preserve in digital form or to modify them. Optical Character Recognition is used to convert the scanned document word, notepad or any other format, so that we can easily edit that document. A complete OCR system for handwritten Devanaga...

Optical Character Recognition for Handwritten Cursive English characters

Optical Character Recognition (OCR) is the technique which enables a machine to automatically recognize the characters or scripts written in the users’ language. Optical Character Recognition (OCR) has become one of the most successful applications of technology in the field of pattern recognition and artificial intelligence. In this project a scanned image is translated into machine editable t...