Image retrieval based on image mean mapping method

Image searching is often done in the world of computer visualization. Time and again users get to see many new digital images uploaded on web. They are fascinated towards automatic image retrieval. In the past few years, many methods were introduced to retrieve images which were based on similarity of size and shape of the image. Content Based Image Retrieval (CBIR) method created the need for proficient and intelligent schemes for classifying and retrieval of Images. One of the main advantages of CBIR is automatic retrieval process in place of the keyword-based approach. The CBIR technology has been used in several applications such as biodiversity information systems, medicine, digital libraries, crime investigation and Historical research. In this method, mean-mapping techniques have been used for the retrieval of images. Each image is converted into the gray form. The database contains threshold values and cluster mean values of more then 10000 images which are extracted using k-mean retrieval method. The query image is compared with the database image using mean mapping methods. The main aim of this work is to extract images with high-class similarity.