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This paper proposes a sign language translation system for communication among deaf and common people. It uses an algorithm about hand detection and analysis from previous studies and project assignments. The algorithm performs five steps within the limitations, which is the key that it measures a center of gravity with 4 vertexes from sign language images and sifts the latent features from calculated...
Various sign languages are used in India, but in schools for deaf, American Sign Language (ASL) is taught. So, the work is based on ASL. Sign recognition application is the development of more effective and friendly interfaces for human-machine interaction. It can provide an opportunity for a mute person to communicate with normal people without the need of an interpreter. We propose a novel system...
This paper demonstrates the evaluation of various pixel level features for the dual handed sign language data set. Data sets are collected from the real life scenario. We compare the feature extraction methods like Histogram of Orientation Gradient (HOG), Histogram of Boundary Description (HBD) and the Histogram of Edge Frequency (HOEF). The accuracy of HOG and HBD found up to 71.4% and 77.3% whereas...
Sign language helps the deaf and mute to communicate effectively. The paper demonstrates the evaluation of various feature extraction techniques for the dual -handed sign language alphabets. The efficiency of features like Histogram of Orientation Gradient (HOG) is discussed followed by the demonstration of the Histogram of Edge Frequency (HOEF) which overcomes the short coming of HOG. The evaluation...
Sign language is the language of the deaf which used as major daily communication tool. Sign language recognition can not only provide convenience for the deaf and also personified as a research platform for human-computer interaction and it has important academic values and broad application prospects. The current field of pattern recognition, Gabor wavelet transform has been widely used. In this...
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