There is a great significance of Image retrieval in multimedia and for image retrieval shape is one of the promising features. This paper presents a survey on one of the method of image retrieval based on shape. First, Shape context is described in this paper and the various versions of it that are implemented are given in detail. This paper gives a summarized view of all the methods of shape context in one single place. It investigates all the methods and gives a brief review. Shape context is descriptor that uses the global features of the shape.

Increasing demands for image retrieval in field such as health informatics, biometrics, and crime prevention has forced developers to explore ways to manage and retrieve images more efficiently. An automated way to retrieve images based on the content or features of the images itself is provided by CBIR. Shape is one of key visual features used by human for distinguishing visual data along with other features of color and texture. Therefore, this work investigates one of the shape representation method shape context which helps in efficient CBIR.The main aim of this research is to look for and develop promising shape descriptor(s) which was found to be Shape Context for image retrieval and also to improve efficiency. The Shape context descriptor is contour based which focuses on irregular shapes. The time consuming step of shape context matching is reduced in this work up to approx. 48% on an average. The proposed work reduces the computational complexity maintaining its overall accuracy.