Illusory contour detection using MRF models

Suthep Madarasmi, Ting Chuen Pong, Daniel J Kersten

Research output: Contribution to conferencePaperpeer-review

4 Scopus citations


This paper presents a computational model for obtaining relative depth information from image contours. Local occlusion properties such as T-junctions and concavity are used to arrive at a global percept of distinct surfaces at various relative depths. A multi-layer representation is used to classify each image pixel into the appropriate depth plane based on the local information from the occluding contours. A Bayesian framework is used to incorporate the constraints defined by the contours and the prior constraints. A solution corresponding to the maximum posteriori probability is then determined, resulting in a depth assignment and surface assignment for each image site or pixel. The algorithm was tested on various contour images, including two classes of illusory surfaces: the Kanizsa and the line termination illusory contours.

Original languageEnglish (US)
Number of pages6
StatePublished - 1994
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994


OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA


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