Visual Based Information Retrieval Using Voronoi Tree

摘要

Content retrieval from large databases needs an efficient approach due to the increasing growth in the digital images. Especially content based image retrieval is an extensive research area. This mainly includes retrieving similar images from the large dataset based on the extracted features. The extracted feature content can be texture, colour, shape etc. Efficient method for image recuperation is proposed in this paper based on shape feature. Shape features like computing Boundary, mode using morphological operations and Harris corner detector and Voronoi diagram are proposed. These matching decisions can be made by different classification models. SVM classifier is used in this research work to get the best matched images during image retrieval. The proposed algorithm is evaluated on JPEG images to get accuracy of about 90 %.