This paper presents a novel approach for sketch-based image retrieval. The approach enables measuring the similarity between a full color multicomponent model image and a black and white sketched query and needs no cost intensive image segmentation. Two different procedures, based on strong edges of the model image and thinned outline of the sketched image, are exploited to derive an abstract image. Spiral decomposition of pixels in the abstract image is then used to extract new compact and effective features. A collection of paintings and sketches (ART BANK) is used for testing the proposed method. The results are compared with three other wellknown approaches. Experimental results show significant improvement in the Recall ratio using the proposed features
