AN ENHANCED RGB PROJECTION ALGORITHM FOR CONTENT BASED IMAGE RETRIEVAL
Abstract
Content based image retrieval (CBIR) is one of the most popular and rising research areas of the digital image processing. Most of the available image search tools, such as Google Images and Yahoo Image search, are based on textual annotation of images. In these tools, images are manually annotated with keywords and then retrieved using text-based search methods. Therefore, the performances of these systems are not satisfactory. The goal of CBIR is to extract visual content of an image, like colour, texture, and shape automatically and to get accurate results with lower computational time. The CBIR technology can be used in several applications such as digital libraries, crime prevention, photo sharing sites, etc. Such a system has great value in apprehending suspects and identifying victims in forensics and law enforcement. This article presents an enhanced Red Green Blue (RGB) projection Algorithm to address the limitations of RGB Projection algorithm and reduce semantic gap in content-based image retrieval using bitmapping algorithm, image scale algorithm and Weighted Euclidean distance. The enhance technique was evaluated using WANG dataset, which contains 10800 colored images. The results show that the enhanced technique has higher precision than the existing system.
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