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Static Sign Language Recognition

This project recognises the various static symbols that are part of ASL and classifies them based on k-nearest neighbour algorithm.

The images were retrieved from a video, filmed at 640x480 using a mobile camera. Further image processing was done to retrive ROIs from the images and resize them to create a uniform dataset for the pattern recognition algo.

Libraries used:

Image processing: OpenCV Classification (ML): Scikit-learn Langauge: Python

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