Locating Image Splicing by Improved DeepLabv3+

doi:10.13190/j.jbupt.2018-244

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (1): 68-73.doi: 10.13190/j.jbupt.2018-244

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Locating Image Splicing by Improved DeepLabv3+

ZHANG Ji-wei, NIU Shao-zhang, CAO Zhi-yi, WANG Xin-yi

Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2018-09-24 Online:2019-02-28 Published:2019-03-08

Abstract

Abstract: As the existing splicing detection algorithms mainly detect whether the image has undergone image splicing, rather than regional localization of the spliced area. An improved DeepLabv3+ network that changes the categories of original DeepLabv3+ network is proposed to locate image regional forgery. In addition, the original images are added to the training dataset, and the ground truth of the original images are set to be black images, which will guide the network to learn the difference between the original images and the spliced images. Experimental results show that the improved DeepLabv3+ network has achieved a finer effect for locating image regional forgery than the existing algorithms on the CASIA database.

Key words: improved DeepLabv3+, image splicing, regional localization, contour learning, edge features

CLC Number:

TN929.53

ZHANG Ji-wei, NIU Shao-zhang, CAO Zhi-yi, WANG Xin-yi. Locating Image Splicing by Improved DeepLabv3+[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(1): 68-73.

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Locating Image Splicing by Improved DeepLabv3+

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