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首页> 外文期刊>Journal of computer sciences >Statistical pattern recognition for thresholding between human skin and background in color images
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Statistical pattern recognition for thresholding between human skin and background in color images

机译：统计模式识别，用于彩色图像中人的皮肤和背景之间的阈值

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摘要

Many research works based on the tone of human skin have been developed to locate and track the human body for the purpose of recognition in color images. With respect to other techniques, some advantages of face detection based on skin color are the smaller processing time, invariant angles of rotation and the performance in semi-occluded faces. In this study we present the results of a survey that investigated the performance of 4 supervised classifiers in skin detection. In order to maximize the generalization of the models, a training set containing samples of individuals of different ages and ethnicities was used.Experimental results showed that the best performance was achieved by using an ANN and the worst results were yielded by LDA. With the Naive Bayes, QDA and ANN algorithms, we showed that the white, black, yellow and brown tones of human skin are in a well-defined range of the RGB color spectrum determined by common characteristics. We also compiled 2798 skin samples for treatment and 305 images with their manually obtained labels as supplementary material, which was made available to help in the development of further research in human skin detection.
机译：为了基于彩色图像进行识别，已经进行了许多基于人体肤色的研究工作来定位和追踪人体。关于其他技术，基于肤色的面部检测的一些优点是处理时间更短，旋转角度不变以及半封闭面部的性能。在这项研究中，我们提出了一项调查的结果，该调查研究了4个监督分类器在皮肤检测中的性能。为了最大化模型的通用性，使用了包含不同年龄和种族的样本的训练集。实验结果表明，使用ANN可获得最佳性能，而LDA产生的结果最差。使用朴素贝叶斯，QDA和ANN算法，我们显示出人类皮肤的白色，黑色，黄色和棕色色调处于由共同特征确定的RGB光谱的明确定义的范围内。我们还编辑了2798个皮肤样本进行治疗，并用人工获得的标签作为补充材料编辑了305张图像，这些样本可用于帮助开展进一步的人类皮肤检测研究。

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