Content Based Image Retrieval Method using Fuzzy Heuristics

Content based image retrieval (CBIR) refers to image content that is retrieved directly, by which the images with features or containing certain contents will be searched in an image database. The main idea of CBIR is to analyze image information by low level features of an image, which includes color, texture, shape and space relationship of objects etc., and to set up feature vectors of an image as its index. A new CBIR search engine is proposed using three features and similarity is measured and controlled by fuzzy heuristics. CBIR Search Engine relies on the characterization of primitive features such as color, shape, and texture that are automatically extracted from the images. There are several techniques to deal with CBIR problems for retrieving the relevant images. CBIR proposed by using three methods. Colour feature is extracted by using histogram based method, texture feature is extracted by using Gabor filter and shape feature is by moment invariant algorithm. For searching the similar images with the database similarity measure is calculated and is controlled by using fuzzy. Fuzzy similarity measure is implemented by using mamdani fuzzy inference method. The use of these three algorithms ensures that the image retrieval approach produces images which are relevant to the content of an image query.