Comparative Study: Content Based Image Retrieval using Low Level Features

Image retrieval plays an important role in many areas like architectural and engineering design, fashion, journalism, advertising, entertainment, etc. How to search and to retrieve the images that we are interested in is a fatal problem: it brings a necessity for image retrieval systems. As we know, visual features of the images provide a description of their content. Contentbased image retrieval (CBIR), emerged as a promising mean for retrieving images and browsing large images databases. It is the process of retrieving images from a collection based on automatically extracted features by generally using low level features. To improve CBIR, human perception i.e. high level feature extraction can be included for better efficiency. In this paper, a comparative analysis is performed so as to achieve efficient results.