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A method of leg skin recognition based on distribution of skin texture

机译:一种基于皮肤纹理分布的腿部皮肤识别方法

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Identifying the criminal and victims in images with only parts of skin existing is a new and challenging task. For this situation, the individual recognition in tradition is invalid, because there are not obvious features existing in the skin images, especially in some forensic cases, there are neither faces nor body labels can be observed. To address this problem, some methods based on skin mark pattern and blood vessel pattern are proposed, however, these methods neglected a fact that the image is not always high resolution, skin marks and blood vessel are not reliable sometimes. A recent paper indicated that androgenic hair patterns are effective in low resolution, but the alignment is not considered and the matching is not robust to viewpoint changing. In this paper, a new feature pattern based on distribution of skin texture trend which firstly borrows the conception of contour line in geography is proposed. A sliding block system is designed to increase discrimination ability and robustness to rotation. Different legs with resolution of 25, 18.75, 12.5, 6.25, 2.60 and 1.30 dpi were examined. Experiment results demonstrate that the proposed algorithm is effective and has rotation invariance, which has a certain improvement.
机译:在仅存在一部分皮肤的图像中识别罪犯和受害者是一项新的挑战性任务。对于这种情况,传统上的个人识别是无效的,因为在皮肤图像中不存在明显的特征,特别是在某些法医情况下,无法观察到脸部或身体标签。为了解决这个问题,提出了一些基于皮肤标记图案和血管图案的方法,但是这些方法忽略了图像并不总是高分辨率的事实,皮肤标记和血管有时不可靠。最近的一篇论文表明,雄激素的头发模式在低分辨率下是有效的,但未考虑对齐方式,并且该匹配对改变视点也不可靠。本文提出了一种基于皮肤纹理趋势分布的新特征模式,该特征模式首先借鉴了地理学中的轮廓线概念。滑块系统被设计为增加辨别能力和对旋转的鲁棒性。检查了分辨率为25、18.75、12.5、6.25、2.60和1.30 dpi的不同支脚。实验结果表明,该算法是有效的,并且具有旋转不变性,有一定的改进。

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