Segmentation of Complex Images Based on Component-Trees: Methodological Tools
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Component-Trees and Multi-value Images: A Comparative Study
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Shape detection from line drawings with local neighborhood structure
Pattern Recognition
Image retrieval based on multi-texton histogram
Pattern Recognition
TAR based shape features in unconstrained handwritten digit recognition
WSEAS Transactions on Computers
Measuring Squareness and Orientation of Shapes
Journal of Mathematical Imaging and Vision
Balancing deformability and discriminability for shape matching
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Interactive segmentation based on component-trees
Pattern Recognition
Using diagonals of orthogonal projection matrices for affine invariant contour matching
Image and Vision Computing
Shape matching and classification using height functions
Pattern Recognition Letters
Shape matching and recognition using group-wised points
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Perceptually motivated morphological strategies for shape retrieval
Pattern Recognition
Densifying Distance Spaces for Shape and Image Retrieval
Journal of Mathematical Imaging and Vision
Perceptually motivated shape context which uses shape interiors
Pattern Recognition
A shape-based approach for leaf classification using multiscaletriangular representation
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Shape retrieval and recognition based on fuzzy histogram
Journal of Visual Communication and Image Representation
Component-Trees and Multivalued Images: Structural Properties
Journal of Mathematical Imaging and Vision
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In this paper, a geometry-based image retrieval system is developed for multi-object images. We model both shape and topology of image objects using a structured representation called curvature tree (CT). The hierarchy of the CT reflects the inclusion relationships between the image objects. To facilitate shape-based matching, triangle-area representation (TAR) of each object is stored at the corresponding node in the CT. The similarity between two multi-object images is measured based on the maximum similarity subtree isomorphism (MSSI) between their CTs. For this purpose, we adopt a recursive algorithm to solve the MSSI problem and a very effective dynamic programming algorithm to measure the similarity between the attributed nodes. Our matching scheme agrees with many recent findings in psychology about the human perception of multi-object images. Experiments on a database of 13500 real and synthesized medical images and the MPEG-7 CE-1 database of 1400 shape images have shown the effectiveness of the proposed method.