Abstract
Due to the development of Internet and photographic technology the numbers of digital images have been increasing rapidly. In this scenario, maintaining the database of images and retrieval of correct image from online database is a challenging task. To perform this task Content Based Image Retrieval (CBIR) is used which is the process of retrieving the most closely matched images automatically by extracting different features. Single feature-based system cannot retrieve image accurately and efficiently. Highdimensional feature reduced the query efficiency and less-dimensional feature reduced query accuracy. So it may be a better solution using multi features for image retrieval. The proposed system is based on CBIR, in which the colour feature extraction is accomplished through constructing a one dimension feature vector. The texture feature extraction is acquired by using gray-level co-occurrence matrix (GLCM) or colour co-occurrence matrix (CCM). The GLCM and CCM are separately combined into a colour feature with the use of quantization of HSV (Hue, Saturation, and Value) colour space. The purpose of this paper is to provide a better and efficient way for image retrieval by using integrated features. Performance is computed separately for three feature extraction mode and got better result using multi-feature extraction retrieval system.