Authors: Sarbjeet kaur, V. K. Banga
This paper presents a vision based system that provides a feasible solution to Indian Sign Language (ISL) recognition of static gestures of alphabets. It deals with images of bare hands, which allows the user to interact with the system in a natural way. An image is processed and converted to a Eigen vector that will be compared with the Eigen vectors of a training set mean of signs. The most important part of the recognition method is a feature extraction process using Eigen value algorithm in MATLAB coding. An image is processed and converted to a feature vector that will be compared with the feature vectors of a training set mean of signs. The system was implemented and tested using a data set of 650 samples of hand sign images; 25 images for each sign. The system recognizes one handed alphabet signs from Indian sign language (ISL). The proposed system achieved a recognition accuracy of 100 %.
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[v1] 2014-05-07 05:42:31
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