Lip Movement Feature Detection and Classification Methods

Computerized lip reading has been one of the most actively researched areas of computer vision in recent past because of its crime fighting potential and invariance to acoustic environment. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. In present work, we propose a solution for automatic lip contour tracking and recognizing numbers 1-10 of English language spoken by speakers using the information available from lip movements. In this method first, we are detecting Face then in that ROI Lip detection. Lip movements as the only input and without using any speech recognition system in parallel. The approach used in this work is found to significantly solve the purpose of lip reading when size of database is small. In this paper also compare LBP and HOG feature with Support Vector Machine Classification. The system is use for the modern sign in PASSWORD systems.

Techniques for Skin, Face, Eye and Lip Detection using Skin Segmentation in Color Images

Face detection is a challenging and important problem in Computer Vision. In most of the face recognition systems, face detection is used in order to locate the faces in the images. There are different methods for detecting faces in images. One of these methods is to try to find faces in the part of the image that contains human skin. This can be done by using the information of human skin color. Skin detection can be challenging due to factors such as the differences in illumination, different cameras, ranges of skin colors due to different ethnicities, and other variations. Neural networks have been used for detecting human skin. Different methods have been applied to neural networks in order to increase the detection rate of the human skin. The resulting image is then used in the detection phase. The resulting image consists of several components and in the face detection phase, the faces are found by just searching those components. If the components consist of just faces, then the faces can be detected using correlation. Eye and lip detections have also been investigated using different methods, using information from different color spaces. The speed of face detection methods using color images is compared with other face detection methods.