Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figure-Ground Discrimination: A Combinatorial Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Class-Specific, Top-Down Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Generic Multi-scale Segmentation and Curve Approximation Method
Scale-Space '01 Proceedings of the Third International Conference on Scale-Space and Morphology in Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Segmentation of Multiple Salient Closed Contours from Real Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Grouping for Contour Extraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Generic Detection of Multi-Part Objects
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Enhancing contour primitives by pairwise grouping and relaxation
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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A method is proposed to enhance boundary primitives of multi-part objects of unknown specific shape and appearance in natural images. Its input is a strictly over-segmented constant-curvature contour primitive (CCP) map. Each circular arc or straight-line segment primitive from the map has an unknown origin which may be the closed boundary of a multi-part object, the textured or marked region enclosed by that boundary, or the external background region. Five simple criteria are applied in order to weight each contour primitive and eliminate the weakest ones. The criteria are defined on the basis of the superposition of the CCP map on a multiscale quadtree segmentation of the original intensity image. A subjective ground-truth binary map is used to assess the degree to which the final weighted map corresponds to a selective enhancement of the primitives on the object boundary. Experimental results confirm the potential of the method to selectively enhance, in images of variable complexity, actual boundary primitives of natural and man-made multi-part objects of diverse shapes and appearances.