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

Vahid Ezzati Chahar Ghaleh, A. Behrad
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引用次数: 12

Abstract

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.
基于RGB色彩空间和模糊c均值聚类的唇形轮廓提取
唇轮廓提取是视觉语音识别系统(唇读)中的一个重要问题。为了提取唇轮廓,需要进行适当的分割。图像分割的方法有很多,如基于直方图的颜色分割和基于聚类的颜色分割在不同领域得到了广泛的应用。本文采用RGB色彩空间和模糊c均值聚类进行唇形分割。与以前的方法相比,我们使用RGB分量获得了一个简单的唇区提取特征,该特征可以作为唇区提取的c均值聚类算法的输入。然后将c均值聚类算法的输出输入到活动轮廓模型中,得到最终的唇形区域。我们用不同的图像对算法进行了测试,结果表明对不同光照下不同说话人的分割效果良好。
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