CBIR using fuzzy edge detection mask

In this paper a novel method for an application of digital image processing, edge detection is developed using fuzzy logic. Content based image retrieval means retrieval of images from database on the basis of visual features of image like as color and texture. In our proposed method feature are extracted after calculate vertical and horizontal edge detection mask with specified threshold on input image. The features are extracted using color and texture methods. Feature extracted values are used to find the similarity between input query image and the data base image. It can be measure by the Manhattan distance formula. In this study we make use of fuzzy logic to improve CBIR by allowing users to express their requirements in words, the natural way of human communication. The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for edge detection in digital images with determining the threshold value. Subjective and objective methods are used to evaluate the performance of the proposed operator with other existing edge detection operators. The proposed system is evaluated by different users with different perspectives and gives satisfactory results. The results are presented for several real and synthetic images to show the effectiveness of the proposed technique. The experimental result shows that the proposed approach has a better retrieval results with fuzzy logic.