A novel approach of rectangular shape object detection in color images based on an MRF model

Yangxing Liu, Takeshi Ikenaga, Satoshi Goto

Research output: Contribution to conferencePaper

Abstract

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.

Original languageEnglish
Pages386-393
Number of pages8
DOIs
Publication statusPublished - 2006 Dec 1
Event5th IEEE International Conference on Cognitive Informatics, ICCI 2006 - Beijing, China
Duration: 2006 Jul 172006 Jul 19

Conference

Conference5th IEEE International Conference on Cognitive Informatics, ICCI 2006
CountryChina
CityBeijing
Period06/7/1706/7/19

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Liu, Y., Ikenaga, T., & Goto, S. (2006). A novel approach of rectangular shape object detection in color images based on an MRF model. 386-393. Paper presented at 5th IEEE International Conference on Cognitive Informatics, ICCI 2006, Beijing, China. https://doi.org/10.1109/COGINF.2006.365521