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Global Binary Continuity for Color Face Detection With Complex Background

机译:复杂背景颜色面部检测的全球二进制连续性

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In this paper, we propose a method to detect human faces in color images, with complex background. The proposed algorithm makes use of basically two color space models, specifically HSV and YCgCr. The color segmented image is filled uniformly with a single color (binary) and then all unwanted discontinuous lines are removed to get the final image. Experimental results on Caltech database manifests that the purported model is able to accomplish far better segmentation for faces of varying orientations, skin color and background environment.
机译:在本文中,我们提出了一种方法来检测彩色图像中的人脸,复杂的背景。所提出的算法利用基本上两种颜色空间模型,特别是HSV和YCGCR。颜色分段图像均匀地用单个颜色(二进制)填充,然后移除所有不需要的不连续线以获得最终图像。 CALTECH数据库的实验结果表明,声称的模型能够为不同方向,肤色和背景环境的面孔完成更好的细分。

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