环状物新检测方法及在敏感图像识别中的应用

被引：2

作者：

王宇石 ^{[1
]}

王伟强 ^{[2
]}

高文 ^{[1
]}

机构：

[1] 哈尔滨工业大学计算机科学与技术学院

[2] 中国科学院计算技术研究所

来源：

哈尔滨工业大学学报 | 2008年 / 03期

关键词：

环形类物体检测; Cascade结构分类器; 物体分割; Bagging算法;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

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.

引用

页码：393 / 396

页数：4

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