Shaker Kadhem Ali Al-Sharify

Hand Gesture Recognition for Dumb and Blind Social Communication Shaker Kadhem Ali Al-Sharify

Gestures communication between dumbs and other people using the expression of signs language an algorithm for recognizing hand gestures of (letters or numbers or words) to by using dumb (through signs) and convert the sings into voice corresponding to sings. Gestures are one of the best ways of communication between dumbs and other people using the expression of signs language. In this book, we suggest an algorithm for recognizing hand gestures of Arabic (letters or numbers or words) to by using dumb (through signs) and convert the sings into voice corresponding to sings (letters or numbers or words). The proposed algorithm use video for the gesture of the dumb then convert the video into frames ( images), preprocessing for the resulted image must be done by removing the noise, resize the images and increase the contrast, then calculate the distance to clustering the words by using (C4.5, k-mean, k- medoid and artificial neural network), calculate the distance ( or features) by using Euclidean distance and slope where, there are eighteen features (eight features from Euclidean distance, eight features from slop, Area, and perimeter). The results in the training stage were (C4.5 gave 99.8664%, k-mean gave 97.7930%, k-medoid gave 97.3620%and ANN gave 96.538% ). While in the testing stage we used three classifiers (Euclidian Distance, Modify of the Standardize Euclidian Distance and Correlation) and the results show that (Euclidian Distance gave 94.7368%, Modify of the Standardize Euclidian Distance gave 98.2456% and Correlation gave 96.4912%) We create our database (ten videos with 814 frames.