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During past few years, people have been substantially attracted towards Content-Based Image Retrieval (CBIR) because of its varied multimedia applications. CBIR is one of the most popular research areas of digital image processing. The goal of the CBIR is to extract the visual features of the image such as color, texture or shape. An attempt is made to develop a Sketch Based Image Retrieval (SBIR) making it use of the features such as shape or form of the object . This paper aims to introduce the creation and design of SBIR system making use of extraction techniques of Biased Maximum Margin Analysis (BMMA) and a Semi-Supervised Biased Maximum Margin Analysis (Semi BMMA) .. With the help of existing methods, design a task specific descriptor, which can handle the informational gap between a sketch and a colored image. The result of SBIR includes the set of positive images (relevant) and negative images (irrelevant). Iterative process acts on the positive set for the optimal extraction of the object. By using Laplacian regularizer to BMMA, the Semi BMMA integrates the information of unlabelled samples  to result in the better extraction of refined set of objects. The SBIR have several applications such as digital libraries, crime prevention, photo sharing sites etc. An important application is a matching a forensic image to gallery of mug shot images.