A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Improved Ranking Metrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Orientation-Based Multi-View Object Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Content Based Image Retrieval Using Interest Points and Texture Features
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convex Optimization
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The geometric structure of an image exhibits fundamental information. Various structure-based feature extraction methods have been developed and successfully applied to image processing problems. In this paper we introduce a geometric structure-based feature generation method, called line-structure recognition (LSR) and apply it to content-based image retrieval. The algorithm is adapted from line segment coherences, which incorporate inter-relational structure knowledge encoded by hierarchical agglomerative clustering, resulting in illumination, scale and rotation robust features. We have conducted comprehensive tests and analyzed the results in detail. The results have been obtained from a subset of 6000 images taken from the Corel image database. Moreover, we compared the performance of LSR with Gabor wavelet features.