A cue integration method for anaglyph image partition

  • Qin WuEmail author
  • Guodong Guo
  • Jiuzhen Liang
Original Article


Image content analysis is important for automated image organization, labeling, and search. Partitioning an image into meaningful regions is one of the fundamental problems in image analysis. Anaglyph images and videos are more and more popular, such as in Flickr and YouTube. The anaglyph images provide disparity cue in a single image, which could be useful for image analysis. This paper exploits disparity cue for image partition. An image partition method for anaglyph is proposed. The disparity or depth cue is integrated with the traditional single-view image segmentation. A concept called dominant disparity is proposed, corresponding to each single-view image segment, which largely tolerates the disparity errors and image over-segmentations. A cue integration algorithm is developed. The integration is at the level of image segments rather than pixels, and object-level image segmentation is achieved. Experiments on both synthetic and real anaglyph images demonstrate the effectiveness of the proposed image partition method for anaglyph image analysis. To the best of our knowledge, our work is for the first time to perform anaglyph image partition.


Anaglyph image analysis Image partition Dominant disparity Cue integration Object-level image segmentation 



The work is partially supported by the National Natural Science Foundation of China (No. 61202312), and a NSF CITeR award.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceJiangnan UniversityWuxiChina
  2. 2.Department of Computer Science and Electrical EngineeringWest Virginia UniversityMorgantownUSA

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