A Novel Approach of Rectangular Shape Object Detection in Color Images Based on An MRF Model

摘要：

Rectangular shape object detection in color images is a critical step of many image recognition systems. However, there are few reports on this matter. In this paper, we proposed a hierarchical approach, which combines a global contour based line segment detection algorithm and an Markov Random Field (MRF) Model, to extract rectangular shape objects from real color images. First, we use an elaborate edge detection algorithm to obtain image edge map and accurate edge pixel gradient information (magnitude and direction). Then line segments are extracted from the edge map and some neighboring parallel segments are merged into a single line segment. Finally all segments lying on the boundary of unknown rectangular shape objects are labeled via an MRF Model built on line segments. Experimental results show that our method is robust in locating multiple rectangular shape objects simultaneously with respect to different size, orientation and color.

作者: Yangxing LIU Takeshi IKENAGA Satoshi GOTO

作者单位: Graduate School of Information, Production and Systems, Waseda University, Japan

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 386-393

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）