Content-Based Image Retrieval-Sketch for Match

Abstract

The content based image retrieval (CBIR) is one of the most popular, rising research areas of the digital image pro-cessing. 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. The performances of these systems are not satisfactory. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or shape. This paper aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, which is based on a free hand sketch (Sketch based image retrieval – SBIR). The used descriptor is constructed after such special sequence of pre-processing steps that the transformed full color image and the sketch can be compared. We have studied EHD, HOG and SIFT. Experimental results on two sample databases showed good results. Overall, the results show that the sketch based system allows users an intuitive access to search-tools. The SBIR technology can be used in several applications such as digital libraries, crime prevention, 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. The area of retrieve images based on the visual content of the query picture intense recently, which demands on the quite wide methodology spectrum on the area of the image processing.