Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Efficient Shape Matching Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
An A Contrario Decision Method for Shape Element Recognition
International Journal of Computer Vision
A Theory of Shape Identification
A Theory of Shape Identification
From Gestalt Theory to Image Analysis: A Probabilistic Approach
From Gestalt Theory to Image Analysis: A Probabilistic Approach
Recognizing objects in adversarial clutter: breaking a visual captcha
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
License Plate Recognition From Still Images and Video Sequences: A Survey
IEEE Transactions on Intelligent Transportation Systems
Morphological Shape Context: Semi-locality and Robust Matching in Shape Recognition
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Multiple clues for license plate detection and recognition
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
On the Role of Contrast and Regularity in Perceptual Boundary Saliency
Journal of Mathematical Imaging and Vision
Hi-index | 0.00 |
This work presents a novel contribution in the field of shape recognition, in general, and in the Shape Context technique, in particular. We propose to address the problem of deciding if two shape context descriptors match or not using an a contrario approach. Its key advantage is to provide a measure of the quality of each match, which is a powerful tool for later recognition processes. We tested the proposed combination of Shape Context and the a contrario framework in character recognition from license plate images.