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Sketch-Based Image Retrieval with Multiple Binary HoG Descriptor

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 819))

Abstract

The proliferation of touch screen devices has enabled Sketch-Based Image Retrieval (SBIR) to become an effective method for image retrieval. Although prior research efforts have ex-tensively explored the methods for SBIR, the appropriate descriptor which can accurately and efficiently describe sketch and natural images is still unavailable. To further improve the accuracy and efficiency of SBIR, in this paper, we pro-pose a novel sketch-based image retrieval method leveraging Multiple Binary HoG (MBHoG) descriptor. In this method, two novel binary descriptors named Primary Binary HoG (PBHoG) and Discrete Binary HoG (DBHoG), are proposed and combined, together with the color feature as an extra condition to enhance the accuracy of results. We use Ham-ming distance with two binary masks as constraint to re-trieve images. The method ensures time and space efficiency. The experimental results performed on the public dataset demonstrate that the proposed method has the superiority of accuracy.

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Acknowledgement

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61522203 and 61572252), the Natural Science Foundation of Jiangsu Province (Grant No. BK20140058 and BK20150755).

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Correspondence to Liyan Zhang .

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Wang, T., Zhang, L., Tang, J. (2018). Sketch-Based Image Retrieval with Multiple Binary HoG Descriptor. In: Huet, B., Nie, L., Hong, R. (eds) Internet Multimedia Computing and Service. ICIMCS 2017. Communications in Computer and Information Science, vol 819. Springer, Singapore. https://doi.org/10.1007/978-981-10-8530-7_4

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  • DOI: https://doi.org/10.1007/978-981-10-8530-7_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8529-1

  • Online ISBN: 978-981-10-8530-7

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