Comparative analysis of skin color model for face detection

C. Sumathi, M. Mahadevi
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Abstract

Skin color detection plays an important phase in identifying the face in images. Detecting face has become difficult because of the complexity in facial features and the similarity between those features. To identify a face, one of the basic step is to segment the image based on skin color. The main objective of the paper is to find a color model which is more suitable and shows a good performance in detecting a face. This paper compares each of the skin color models namely HSV, YCBCR, L*a*b for better accuracy. On such comparison, a hybrid skin color model is derived by combining the suitable color component from the three skin color models. After Morphological operations and using connected components a face is detected. After experiments it is observed that the Hybrid color model based skin detection is more suitable with an accuracy of 93%.
肤色模型在人脸检测中的比较分析
肤色检测是人脸识别的一个重要环节。由于人脸特征的复杂性和特征之间的相似性,人脸检测变得非常困难。人脸识别的基本步骤之一是基于肤色对图像进行分割。本文的主要目的是寻找一种更合适的颜色模型,并在人脸检测中表现出良好的性能。本文对HSV、YCBCR、L*a*b三种肤色模型进行了比较,以获得更好的准确性。在此基础上,结合三种肤色模型中合适的肤色分量,得到混合肤色模型。经过形态学操作,并使用连接的组件来检测人脸。实验结果表明,基于混合颜色模型的皮肤检测更为合适,准确率达到93%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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