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Photo-to-Sketch Transformation in a Complex Background

Xianlin Zhang,Xueming Li,Shuxin Ouyang,Yang Liu

Published 2017 in IEEE Access

ABSTRACT

We investigate the problem of sketch generation for sketch-based image retrieval (SBIR). Solving this problem is important to obtain better retrieval results, because a powerful feature extraction algorithm is inefficient. Transforming photos from raw pixels into pseudo-sketches closes the gap between these two domains and plays a significant role in SBIR. This problem is relatively challenging because of: 1) the complexity of the image background and 2) the complexity of the resulting edge map. In this paper, we develop a system to generate pseudo-sketches from photos. Saliency detection is used to extract the major objects from a photo. Then, a Gabor filter is designed to further capture the “real-major” object. Finally, the Sobel operator is used to obtain the final pseudo-sketch. Experiments are conducted using the Flickr15k data set. The results show that the obtained pseudo-sketches are reasonable and that the SBIR process produces the state-of-the-art results in certain categories.

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