An MRF Model Based Algorithm of Triangular Shape Object Detection in Color Images

Triangular shape object detection in color images is an important issue in computer vision. However, there are few reports on this matter. In this paper, we proposed a novel approach, which combines a global contour based line segment detection algorithm and Markov Random Field (MRF) Model, to extract triangular objects from color images. First, we use an elaborate edge detection algorithm to obtain image edge map and accurate edge pixel gradient information. 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 triangular objects are labeled via an MRF Model built on line segments. Experimental results show that our method is robust in locating multiple triangular objects simultaneously with respect to different size, orientation and color.