基于Viola-Jones方法的人脸检测成人图像分类器

M. D. Putro, T. B. Adji, Bondhan Winduratna
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引用次数: 19

摘要

本研究包括一个分类系统,以确定成人和良性图像。在本研究中,成人形象被定义为印尼人认为是色情的形象。本研究的方法将人脸检测与HS肤色检测相结合。人脸检测是通过使用Viola-Jones方法完成的。经过人脸检测后,对图像进行皮肤检测。基于人脸和皮肤的检测结果,提取一组特征并插入到分类器中。用于确定成人或良性图像的分类将基于图像中面部面积的百分比,图像中面部的位置以及图像中肤色的百分比。对于每个特征,本研究定义了阈值。分类器的结果是输入图像是良性图像还是成人图像。从30张样本图像中,分类过程将5张图像分类为良性图像,25张图像分类为成人图像。假阳性率为2张,假阴性率为1张,准确率为90%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adult image classifiers based on face detection using Viola-Jones method
This research consists of a classification system to determine the adult and benign image. Adult image in this research was defined as image that is perceived as pornographic by Indonesian people. The method in this research combines face detection and HS skin color detection on an image. Face detection is done by using the Viola-Jones method. After face detection process, skin detection is performed on the image. Based on the results of face and skin detections, a set of features is extracted and inserted into the classifier. The classification used in determining adult or benign image will be based on the percentage of face area in the image, the position of face in the image, and the percentage of the skin color in the image. For each feature, the threshold value is defined in this research. The results of the classifier is whether an input image is benign or adult images. From 30 sample images, the classification process classifies 5 pieces of images as benign images and 25 images as adult images. False positive rate are 2 images and false negative rate is 1 image with the accuracy of 90%.
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