Automatic Image Grading Based on Skin Segmentation

摘要：

This paper proposes an automatic image grading method, which classifies an image into three levels, i.e., Normal, Revealing Attire and Nude. First, a novel region-based skin detection method, which incorporates the clues of color, shape, texture and neighborhood, is used to get the skin regions. Then a normalized mask is generated from the skin-region image according to the scale and location of the face. Global and spatial features extracted based on this mask are used as the input of SVM to give the grade of an image. Besides, because false classifications of images with different grades have quite different affections, a cost-matrix is defined and the MetaCost method is used to get the minimumrisk results. Experimental results show the effectiveness of our method.

关键词： image grading skin detetion minimum-risk

作者: Pu Cheng Ming Zhang Jie Zhou

作者单位: Department of Automation Tsinghua University Beijing, China

会议类型: 国际会议

会议名称: 2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics 第三届智能人机系统与控制论国际会议 IHMSC 2011

会议地点: 杭州

会议语种:英文

页码: 39-42

在线出版日期: 2011-08-26（万方平台首次上网日期，不代表论文的发表时间）