Similarity Analysis Of Images Using Content Based Image Retrieval System (International Journal of Engineering and Computer Science, 2013)
The content based image retrieval (CBIR) is one of the digital image processing system. Most of the available image search tools are based on textual explanation of images. In these tools, images are manually annotated with keywords and then retrieved using text-based search means. This method would not produce promising results. The goal of CBIR is to extract visual features and display the required image. This paper aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, using SBIR. With the help of the existing methods, a possible solution how to design and implement a task specific descriptor, which can handle the informational gap among a sketch and a colored image, making an opportunity for the efficient search hereby. The results show that the sketch-based system allows users a shrewd access to search-tools. This technology can be used in several applications such as digital libraries, crime prevention, and photo sharing sites. Such a system has great value in apprehending suspects and identifying victims in forensics and law enforcement. A possible application is matching a forensic sketch to a gallery of mug shot images. This paper focus on retrieval of images based on the visual content of the query picture, which demands on the quite wide methodology spectrum on the area of the image processing.