An Image Recognition/Retrieval System: Design And Implementation

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Introduction This paper discusses the design and implementation of an image recognition /retrieval system indexed with parameterized color histogram. As the usage of multimedia data has increased in recent years, effective and efficient methods for storing and retrieving multimedia have been required and are being developed. In particular, images are used as important inputs in a variety of areas. The area of content-based image retrieval is a hybrid research area that requires knowledge of both computer vision and of database systems. Large image databases are collected, and images from these collections made available to users in advertising, marketing, entertainment, and other areas where images can be used to enhance the product. The generally categorized images as animals, natural scenes, people, and so on for access require browsing by a user to select the appropriate images. Image Recognition/Retrieval System Over the previous years, techniques for content-based image retrieval systems are published. The focus of this paper is to design and implement the efficient way of retrieving the images by sample query images. A set of color features has been efficiently used to measure the similarity of given images. However, at the same time the size of the color features is too large to implement an indexing scheme effectively. In other words, the large size of color features need to have large amount of resources and the computer systems require much of the time to operate. It has been, therefore, proposed to retrieve similar images by using interpolated color histogram to save resources and to increase efficiency. In order to represent the distribution of the color histograms, the best order of interpolated polynomial would be ...

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... Reference Linda G. Shapiro Efficient Content-Based Image Retrieval Department of Computer Science and Engineering, University of Washington. This project has supported the Ph.D. research of Andrew Berman, who received his degree in March 1999 and has partially supported the work of Yu-Yu Chou, who received his Ph.D. in December 1999. John R. Smith and Shih-Fu Chang (October 1995) Single Color Extraction and Image Query Proceedings of the I.E.E.E. International Conference on Image Processing (ICIP-95), October 1995. Columbia University, Center for Telecommunications Research, Image and Advanced Television Laboratory, New York, N.Y. 10027 Y. Tao and W. I. Grosky Image Matching Using the OBIR System with Feature Point Histograms Computer Science Department, Wayne State University, Detroit, Michigan 48202, U.S.A.
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