A New Web Image Searching Engine by Using SIFT Algorithm

Abstract

This paper provides a web content-based image searching engine based on SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. Therefore, feature keypoints can be extracted more accurately by using SIFT than color, texture, shape and spatial relations feature. To decrease unavailable features matching, a dynamic probability function replaces the original fixed value to determine the similarity distance and database from training images. For the establishment of source image library, in this paper, the spider technology used to extract images in Web pages. Then, by using pretreatment of the source images, the keypoints will be stored to the XML format, which can improve the searching performance. By using of the Hibernate framework and related technology, all of the information of image can establish a link with the database, and completed the development of persistent object. Finally, the results displayed to the user through the HTML. The experimental results show that this method improves the stability and precision of image searching engine.