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Lip contour detection and tracking is the most important pre-requisite for computerized speech reading. Several approaches have been proposed for lip tracking after lip contour is accurately initialized on first frame. Detection and tracking of the lip contour is an issue in speech reading. A relatively large class of lip reading algorithms are available based on lip contour analysis. In these cases, lip contour extraction is needed as the first step. By lip contour extraction, we usually refer to the process of lip contour detection in the first frame of an audio-visual image sequence. Obtaining the lip contour in subsequent frames is usually referred as lip tracking. While for lip contour tracking there are well developed techniques and algorithms to perform this task automatically, in the case of lip contour extraction in the first frame the things are different. This is a much more difficult task than tracking, due to the lack of a good a-priori information in respect to the mouth position in the image, the mouth size, the approximate shape of the mouth, mouth opening etc. In this paper we propose a solution to automatic lip contour detection if front view of face is available. The proposed method has been tested on a database containing face images of different people and was found to have maximum success rate of 85%.

Prof. Samir K. Bandyopadhyay

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