IMAGE MATCHING ALGORITHM BASED ON HUMAN PERCEPTION
There has been in depth analysis and numerous researches on image matching and storage. Major software distributors providing RDBMS provide image storage based on textual description. Since Images can easily be searched based on textual information, it is not so efficient and hence brings need of such technique that allows search based on image feature and not based on textual description of image. In recent years dramatic changes have been seen in digital image libraries and other multimedia databases. In order to effectively and precisely retrieve the desired images from a large image database, the development of a content-based image matching system has become an important research issue. However, most of the proposed approaches emphasize on finding the best representation for different image features. Human perception of comparing image is something else. Visual perception is the ability to interpret the surrounding environment by processing information that is contained in visible light. The resulting perception is also known as eyesight, sight, or vision. Hence color attributes like the mean value, the standard deviation, and the image bitmap of a color image are used as the features for matching. In addition, the entropy based on the gray level co-occurrence matrix and the edge histogram of an image is also considered as the texture features.