Subjective contours detection

  • Souheil Ben-Yacoub
Conference paper
Part of the Advances in Computing Science book series (ACS)


Basic visual activities are related to edge detection (motion, recognition,...). We show that there are different kinds of edges. The most known and already studied are edges due to luminance variations. After a brief introduction to classical edge-detectors, we introduce another class of edges, the “subjective contours”. We assume end-points as textons as proposed by B. Julesz [7] and D. Marr [11]. The first step of our algorithm consists in geometric feature (i.e. segments) extraction using the hierarchical Hough transform. The end-points of the detected features are then drawn on a new image. This second “feature map” (of higher level) is then processed in a second step using again the hierarchical Hough transform. The end-points acts as clues indicating the presence of “subjective contours”. We show that there is a relation between the number of clues present in the “feature map” and the pop-out phenomenon of the “subjective contour”.


Illusory Contour Subjective Contour Vote Process Hough Space Gestalt Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag/Wien 1997

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  • Souheil Ben-Yacoub

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