Bonfring International Journal of Software Engineering and Soft Computing, Vol. 6, Special Issue, October 2016 213 ISSN 2277-5099 | © 2016 Bonfring Abstract---- In today’s world, technology is enhancing day by day, the most enhanced research area in digital image processing is image retrieval system .The techniques used for retrieving image on the basis of sketches that can be describe as an image. So the system is referred to as Sketch Based Image Retrieval System (SBIR). Here we made the comparison of efficiency of different methods like Manhattan, Euclidean, Correlation, Spearman and city block distances approaches on different dataset and we find which is the best method based on the efficiency. Keywords--- Classification, Sketch, 3D Model, 3D Retrieval, SBIR. I. INTRODUCTION ith the increasing number of 3D models created every day and stored in databases, the development of effective and scalable 3D search algorithms has become an important research area. Generally speaking, their objective is to retrieve 3D models similar to a 2D/3D sketch/image or a complete 3D model query from a large collection of 3D shapes Query-by-Sketch (sketch-based) 3D retrieval is to retrieve a list of 3D models that closely match a provided input sketch. It is more challenging because of the semantic and representational gap between the 2D query sketches and the 3D sketches, and because user sketches may vary widely in sketching style and level of detail, as well[4][2][3]. It has many applications, including sketch-based modeling and recognition, and sketch based 3D animation. Sketch-based 3D model retrieval is focusing on retrieving relevant 3D models using sketches as input[1-5].The sketches are Hand-Drawn sketches as shown in the figure[1]. For objective evaluation, we have collected a large number of query sketches . Poornima Raikar, HOD, Dept. of CSE, KLS’s VDRIT, Haliyal, Karnataka, India. Dr.S.M. Joshi, Dept. Of Computer science, HOD, SDMCET, Dharwad Karnataka, India. E-mail:joshshree@yahoo.co.in DOI:10.9756/BIJSESC.8280 Figure 1: Images Stored in the Database with 5 Classes (a)Planes (b)Beds (c)Bicycles d) Bees e)Barns An image is retrieved from the database in several ways in user queries. SBIR is one of the efficient and important methods which are not necessary to have a high skill to draw the query sketch. First, we review the feature extraction, features based matching, and indexing which represents the base of recall images.. In this paper we discuss about how to retrieve the images using shape , texture descriptor, then method for retrieval, then experimentation results of methods and lastly comparison of efficiency of distance methods. Figure 2: Diagram for Image Retrieval The steps involved in shape based image retrieval Query as shown in Fig 2. Image Database contains set of sketch images into the database. First we extract the features of the input Efficiency of Methods in Retrieval Using Query by Sketch Poornima Raikar and Dr.S.M. Joshi W