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Pornographic image rejection using eigenporn of simplified LDA of skin ROIs images

机译:使用Skin Rois图像的简化LDA的特征化色情图像排斥

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This paper proposes alternative solution for pornographic rejection using eigenporn extracted by simplified linear discriminant analysis (LDA) of skin region of interests (ROIs) of pornographic images. The skin ROI is extracted by skin segmentation that is performed by threshold rule of YCbCr color space. The skin ROI is employed to handle the large variability of pornographic images due to backgrounds variations. While eigenporn is employed not only to decrease the dimensionality of the input images but also to handle the large variability of pornographic images due to poses variations. The main aim of this research is to obtain good algorithm for rejection of pornographic contents, which can be developed for rejecting of accessing pornographic contents in the Internet from unexpected people like children. The experimental results show that the proposed rejection system is suitable concept for rejecting of accessing pornographic images, which is shown by higher accuracy and less false rejection rate than those of existing methods (increasing the accuracy by about 2.38% and decrease the FPR and computational time by about 13.20% and 0.195 seconds of those of FD based method, respectively).
机译:本文提出了通过通过色情图像(ROIS)的皮肤区域(ROI)的简化线性判别分析(LDA)提取的特征抑制来替代方法。皮肤投资回报率由YCBCR颜色空间的阈值规律执行的皮肤分段提取。由于背景变化,使用皮肤投资回报率来处理色情图像的大幅变化。虽然特征斑件不仅用于减少输入图像的维度,而且还用于处理由于姿势变化而导致的色情图像的大变化。本研究的主要目的是获得良好的拒绝色情内容算法,可以制定用于拒绝从互联网中的色情内容从像儿童这样的意想不到的人访问。实验结果表明,该拒绝系统是拒绝访问色情图像的合适概念,其比现有方法更高的准确性和较少的假拒绝率(将精度提高约2.38%并降低FPR和计算时间而显示基于FD的方法分别约为13.20%和0.195秒)。

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