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Hand gestures is one of the methods used in sign language for non verbal communication and that is what we have used in our web development. It is most commonly used by deaf and dumb people who have hearing or speech problems to communicate among themselves or with normal people. Hence, it is a software which presents a system prototype that is able to automatically recognize sign language to help deaf and dumb people to communicate more effectively with each other or normal people. Dumb people are usually deprived of normal communication with other people in the society, also normal people find it difficult to under and communicate with them. These people have to rely on an interpreter or on some sort of visual communication. An interpreter won’t be always available and visual communication is most difficult to understand.

SVM + HoG and Convolutional Neural Networks can be used as classification algorithms for sign language recognition. Support Vector Machine(SVM) is a supervised machine learning algorithm used for both classification and regression. Though we say regression problems as well its best suited for classification. The objective of SVM algorithm is to find a hyperplane in an N-dimensional space that distinctly classifies the data points. A HoG is a feature descriptor generally used for object detection. HOGs are widely known for their use in pedestrian detection. A HoG relies on the property of objects within an image to possess the distribution of intensity gradients or edge directions. Gradients are calculated within an image per block Convolutional Neural Networks (CNNs) are analogous to traditional ANNs in that they are comprised of neurons that self-optimise through learning. Each neuron will still receive an input and perform an operation (such as a scalar product followed by a non-linear function)-the basis of countless ANNs. These all combine to give the output.

The system converts the sign gesture that is depicted by the muted (Someone who is completely unable to speak) into speech/text depending on our convenience, this is to break the barrier in communication between the muted and a normal individual. Due to complexity issues and inconvenience (using a computer) we have developed a Web application and Mobile application.


To achieve our project goal


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