Notes on shape orientation where the standard method does not work
Pattern Recognition
Boundary vector field for parametric active contours
Pattern Recognition
Reflective Symmetry Detection Based on Parallel Projection
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
External Force for Active Contours: Gradient Vector Convolution
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Symmetry-integrated injury detection for brain MRI
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
3-D Symmetry Detection and Analysis Using the Pseudo-polar Fourier Transform
International Journal of Computer Vision
Convolutional virtual electric field external force for active contours
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Boundary based orientation of polygonal shapes
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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This paper addresses the problem of detecting axes of bilateral symmetry in images. In order to achieve robustness to variation in illumination, only edge-gradient information is used. To overcome the problem of edge breaks, a potential field is developed from the edge map which spreads the information in the image plane. Pairs of points in the image plane are made to vote for their axes of symmetry with some confidence values. To make the method robust to overlapping objects, only local features in the form of Taylor coefficients are used for quantifying symmetry. We define an axis of symmetry histogram, which is used to accumulate the weighted votes for all possible axes of symmetry. To reduce the computational complexity of voting, a hashing scheme is proposed, wherein pairs of points, whose potential fields are too asymmetric, are pruned by not being counted for the vote. Experimental results indicate that the proposed method is fairly robust to edge breaks and is able to detect symmetries even when only 0.05% of the possible pairs are used for voting.