Spatial Feature Extractions Using Supervised Fuzzy Classification

This paper emphasis on spatial feature extractions and selection techniques adopted in content based image retrieval that uses the visual content of a still image to search for similar images in large scale image databases, according to a user’s interest. The content based image retrieval problem is motivated by the need to search the exponentially increasing space of image databases efficiently and effectively. It is also possible to classify the remotely sensed image to represent the specific feature of the target images. In this paper, a priori knowledge about information for certain feature classes is used in order to classify image in fuzzy logic classification procedure. Here first we have to supervised image classification and then use the logic based on fuzzy logic. Based on similarities supervised membership function is used. Results of the procedure, based on pixel-by-pixel technique, were compared and certain encouraging conclusion remarks come out.