环状物新检测方法及在敏感图像识别中的应用  

A novel circular object detection method and its application in pornographic image detection

作　　者：王宇石[1] 王伟强[2] 高文[1] 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001 [2]中国科学院计算技术研究所,北京100080

出　　处：《哈尔滨工业大学学报》2008年第3期393-396,共4页Journal of Harbin Institute of Technology

基　　金：国家高技术研究发展计划资助项目(2003AA142140)

摘　　要：为了克服传统的Hough变换类环状物体检测的局限,提出了1种结合物体形状与外观特征的环状物体识别检测算法.识别算法使用cascade结构,分别使用灰度、纹理以及外观综合特征,按Bagging的方法训练产生一组弱分类器.这些弱分类器串接而成,并结合局部物体分割,逐个处理当前扫描窗口.相比于传统的Hough算法,新方法具有更快的检测速度.选择敏感图像作为实验对象,采集数据进行训练和检测,实验结果表明,新方法具有明显的性能优势.使用更全面的物体外观信息,按Bagging产生弱分类器的组合,能够在提高环状物体的检测性能的同时,获得理想的处理速度.The paper proposes a new method to detect circular objects in images which performs better than Hough-like approaches. The method makes use of the shape and appearance information of objects. The detector is composed of a cascade of weak classifiers constructed by the Bagging algorithm and a local segmentation module. Three groups of local features involving gray value, texture and appearance were used in these classifiers in turn. An image＇ s window is reported as a circular object when it passes all the weak classifiers. Compared with the Hough algorithm, the detector has a faster detection speed and a better performance on the pornographic test data. Utilizing the information of object＇ s appearance and integrating it into a cascade of weak classifiers can improve the performance of circular object detection and lower the computational cost.

关 键 词：环形类物体检测 Cascade结构分类器 物体分割 BAGGING算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]