LIP DETECTION BASED-ON NORMALIZED RGB CHROMATICITY DIAGRAM

This paper presents a new lip detection method based-on normalized RGB chromaticity diagram. The method consists of three stages: face detection, lip region localization and lip detection. The popular Viola-Jones face detection technique is employed in the face detection stage. In the lip detection stage, lip color is extracted using our novel color segmentation method that exploits the distribution of lip color on the RGB chromaticity diagram. From the experiment using 100 face images, the detection rate of 97% is achieved

LIP DETECTION BASED-ON NORMALIZED RGB CHROMATICITY DIAGRAM

ABSTRACT This paper presents a new lip detection method based-on normalized RGB chromaticity diagram. The method consists of three stages: face detection, lip region localization and lip detection. The popular Viola-Jones face detection technique is employed in the face detection stage. In the lip detection stage, lip color is extracted using our novel color segmentation method that exploits the distribution of lip color on the RGB chromaticity diagram. From the experiment using 100 face images, the detection rate of 97% is achieved. Keywords: Face detection, lip detection, color segmentation, chromaticity diagram

Adaptive Mouth Segmentation using Chromatic Features

The automatic segmentation of the mouth from its facial background is a very difficult computer vision problem due to the low grayscale distinction between classes. Recently chromatic based segmentation has enjoyed some popularity for the purposes of mouth tracking due to its ability to distinguish between the two classes. Such systems have to be highly adaptive due to problems with colour constancy. In this paper a technique for adaptive segmentation is investigated using an unsupervised clustering technique incorporating the expectation maximisation (EM) algorithm across a variety of chromatic features. Results are presented from the M2VTS database across a number of subjects