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Face detection in color images based on sub-image fusion and SVM

机译:基于子图像融合和支持向量机的彩色图像人脸检测

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A face detection method in color images using multi-resolution sub-images fusion combined with support vector machine (SVM) is proposed. Firstly the skin images are obtained by two different color modes (HSI and YCbCr). Secondly, multi-resolution sub-image is gained by wavelet analysis of skin area image. Thirdly fusion image can be obtained by sub-image LH and HL according to pixel fusion criterion. Fusion images should be incorporated if necessary, candidate face area can be detected in fusion image. Finally face images can be validated by using SVM. Experiment result shows that, detection rate of faces in a complex background image achieves 95.8%. This method is not effected by gesture, expression and rotation but the distance of the faces in a group photo.
机译:提出了一种多分辨率子图像融合与支持向量机(SVM)相结合的彩色图像人脸检测方法。首先,通过两种不同的颜色模式(HSI和YCbCr)获得皮肤图像。其次,通过皮肤区域图像的小波分析获得多分辨率子图像。第三,可以根据像素融合标准,通过子图像LH和HL获得融合图像。如有必要,应合并融合图像,可以在融合图像中检测出候选脸部区域。最后,可以使用SVM验证人脸图像。实验结果表明,复杂背景图像中人脸的检测率达到95.8%。此方法不受手势,表情和旋转的影响,但受集体照片中脸部的距离的影响。

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