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In this work, we developed a model for representation and indexing of objects for given input query sketch. In some applications, where the database is supposed to be very large, the retrieval process typically has an unacceptably long response time. A solution to speed up the retrieval process is to design an indexing model prior to retrieval. In this work, we study the suitability of Kd-tree indexing mechanism for sketch based retrieval system based on shape descriptors like Scale invariant feature transform(SIFT), Histogram of Gradients (HOG), Edge orientation histograms (EOH) and Shape context (SC). To corroborate the efficacy of the proposed method, an experiment was conducted on Caltech-101 dataset. And we collected about 200 sketches from 20 users. Experimental results reveal that indexing prior to identification is faster than conventional identification method.