Local image representations using pruned salient points with applications to CBIR
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A neural network based CBIR system using STI features and relevance feedback
Intelligent Data Analysis
Comparing global and interest point descriptors for similarity retrieval in remote sensed imagery
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Geographic image retrieval using interest point descriptors
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Structure features for content-based image retrieval
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Hierarchical Salient Point Selection for image retrieval
Pattern Recognition Letters
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Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. In this work, we present methods for content-based image retrieval based on texture similarity using interest points and Gabor features. Interest point detectors are used in computer vision to detect image points with special properties, which can be geometric (corners) or non-geometric (contrast etc.). Gabor functions and Gabor filters are regarded as excellent tools for feature extraction and texture segmentation. This article combines these methods and generates a textural description of images. Special emphasis is devoted to distance measures on texture descriptions. Experimental results of a query system are given.