Jhilik Bhattacharya

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Since its emergence in the 1990s the World Wide Web (WWW) has rapidly evolved into a huge mine of global information and it is growing in size everyday. The presence of huge amount of resources on the Web thus poses a serious problem of accurate search. This is mainly because today’s Web is a human-readable Web where information cannot be easily processed(More)
This paper proposes two new approaches of hand gesture recognition which will recognize sign language gestures in a real time environment. A hybrid feature descriptor, which combines the advantages of SURF & Hu Moment Invariant methods, is used as a combined feature set to achieve a good recognition rate along with a low time complexity. To further increase(More)
The detection of fine feature from an image is often challenging.Generally,the smoothing filters used for the purpose are inadequate for such applications with the exception of bilateral and mean shift filter.A new smoothing filter termed Gaussian Maxima Filter(GMF) , developed and presented here shows better performance in preserving fine features even for(More)
This paper proposes two face recognition algorithms namely Logarithmic Fourier Domain Principal Component Analysis (Log Fourier PCA) and Log fourier PCA with Independent Component Analysis (ICA) which successfully tackles multiple variations of face images. Neural network is used as classifier for both these methods. The Log Fourier PCA method proves to be(More)
Some experiments on a face verification tool based on FaceNet are presented in this paper. The task of the system is to perform face verification in a real-time assistive system aiming at facilitating the approach between a blind person and a preselected acquaintance of his/her who enters the field of view. Face detection is made easier by the fact that an(More)
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