Matching oversegmented 3D images to models using association graphs
Image and Vision Computing
Using complex Gabor filters to detect and localize edges and bars
Advances in machine vision
Automatic feature point extraction and tracking in image sequences for arbitrary camera motion
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multichannel Approach to Fingerprint Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orientation Space Filtering for Multiple Orientation Line Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Gabor wavelet representation for 3-D object recognition
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Gabor filter-based feature extraction and its use in object shape matching are addressed. For the feature extraction multi-scale Gabor filters are used. From the analysis of the properties of the Gabor-filtered image, we know isolated dominant points generally exist on the object contour, when the filter design parameters are properly selected. The dominant points thus extracted are robust to the image noise, scaling, rotation, translation, and the minor projection deformation. Object shape matching in terms of a two-stage point matching is presented. First, a feature vector representation of the dominant point is used for initial matching. Secondly, the compatibility constraints on the distances and angles between point pairs are used for the final matching. Computer simulations with synthetic and real object images are included to show the feasibility of the proposed method.