An MRF model-based approach to the detection of rectangular shape objects in color images

Yangxing Liu*, Takeshi Ikenaga, Satoshi Goto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)


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. Firstly, 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.

Original languageEnglish
Pages (from-to)2649-2658
Number of pages10
JournalSignal Processing
Issue number11
Publication statusPublished - 2007 Nov 1


  • Edge detection
  • Line segment detection
  • MRF model
  • Randomized Hough transform
  • Rectangle detection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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