IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
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
Generic Detection of Multi-Part Objects
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Enhancing Boundary Primitives Using a Multiscale Quadtree Segmentation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Detection of unexpected multi-part objects from segmented contour maps
Pattern Recognition
Morphology based spatial relationships between local primitives in line drawings
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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A method is proposed to enhance contour primitives of multipart objects in complex images. It consists in first extracting circular arcs and straight-line segment primitives from the image edge map. The produced binary constant-curvature primitive map includes primitives of interest on the object contour or silhouette, as well as two types of distractors: internal texture segments and external background segments. Each obtained primitive is enhanced using an exhaustive evaluation of a number of pairwise grouping criteria. Finally, an iterative relaxation procedure adjusts the weight of each primitive according to the weights of its best-matching primitives. A subjective ground-truth binary map may be used to assess the degree to which the final weighted map corresponds to a selective enhancement of contour primitives