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Time stamp: 05:56:54-24/5/2024


Handwriting Recognition Using Image Processing

Kevyne L Selmo


Supervised by Hantao Liu; Moderated by Alia I Abdelmoty

We've probably come across a situation where you've wrote notes on paper and typed them into word process afterwards. From a point of view, some may find this redundant.

The main idea of this project is to be able to recognise handwritten characters from an image and output the results into a file(e.g. .txt). The approach that I am considering will consists of: - Pre-processing: e.g. making the image into a binary or perhaps applying some blurring to remove noise. - Segmentation: ideally we'd want to process separate each character. (may start with simple images consisting of non-joint up handwriting) Using connectivity approach to differentiate each character. - Feature Detection: obtain specific points of the character. Satisfying invariants, e.g. translation/scale/rotation. - Classification: using the points to classify what character it is based on training data. (perhaps machine learning)

Initial Plan (31/01/2016) [Zip Archive]

Final Report (06/05/2016) [Zip Archive]

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