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Segmentation-based Image Hash for Precise Tamper Localization
Yan, Cai-Ping; Pun, Chi-Man
Conference NameWorld Congress on Internet Security (WorldCIS-2017)
Source PublicationProceedings of the World Congress on Internet Security, 2017
Conference Date2017-12-11
Conference PlaceUniversity of Cambridge, UK

The block-based analysis for tamper localization is a prevailing mechanism in hash-based forgery detection algorithm. One of the main problems with a block-based analysis is its rough localization stemming from that the forensic hashes attached to the images are lack of contour information. In this paper, we present a novel tamper detection model which can generate an accurate tamper localization result. The main difference to the traditional algorithms is that the proposed model segments the image into closed regions based on strong edges. Then the color and position features of the closed regions are extracted as a forensic hash. Furthermore, a graph-based ranking algorithm is proposed to establish the region correspondence between the received image and forensic one by exploiting their intrinsic structure information. Experimental results demonstrate that the proposed tamper detection model is a promising method for precise tamper localization compared with state-of-the-art methods.

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Document TypeConference paper
CollectionFaculty of Science and Technology
AffiliationUniversity of Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yan, Cai-Ping,Pun, Chi-Man. Segmentation-based Image Hash for Precise Tamper Localization[C],2017:117-122.
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