Lip contour extraction using RGB color space and fuzzy c-means clustering

Lip contour extraction is very important issue in visual speech recognition systems (lip reading). To extract the lip contour, proper segmentation is needed. There are many approaches for image segmentation such as colour segmentation (histogram-based and clustering-based) that have been widely used in different areas. In this paper we use RGB colour space and fuzzy C-means clustering for lip segmentation. Compared to previous methods, we obtain a simple feature for lip region extraction using RGB components which can be used as input to C-means clustering algorithm for lip region extraction. Then the outputs of the C-means clustering algorithm are fed into active contour model to obtain final lip region. We tested the proposed algorithm with different images and results showed good segmentation for different speakers with different illumination.

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