Content based image retrieval using interest points and texture features

Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. 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. The 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