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As a result, seam-carving detection is becoming crucially important to recognize the image authenticity. However, existing methods do not perform well in the accuracy of seam-carving detection especially when the scaling ratio is low. In this paper, we propose an image forensic approach based on the cooccurrence of adjacent local binary patterns (LBPs), which employs LBP to better display texture information. Specifically, a total of 24 energy-based, seam-based, half-seam-based, and noise-based features in the LBP domain are applied to the seam-carving detection. Moreover, the cooccurrence features of adjacent LBPs are combined to highlight the local relationship between LBPs. Besides, SVM after training is adopted for feature classification to determine whether an image is seam-carved or not. Experimental results demonstrate the effectiveness in improving the detection accuracy with respect to different scaling ratios, especially under low scaling ratios.<\/jats:p>","DOI":"10.1155\/2020\/8830310","type":"journal-article","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T19:35:59Z","timestamp":1608579359000},"page":"1-12","source":"Crossref","is-referenced-by-count":23,"title":["Seam-Carved Image Tampering Detection Based on the Cooccurrence of Adjacent LBPs"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2789-2980","authenticated-orcid":true,"given":"Dengyong","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China"},{"name":"Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha 410114, Hunan, China"}]},{"given":"Xiao","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China"},{"name":"Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha 410114, Hunan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2718-9918","authenticated-orcid":true,"given":"Feng","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China"},{"name":"Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha 410114, Hunan, China"}]},{"given":"Arun Kumar","family":"Sangaiah","sequence":"additional","affiliation":[{"name":"School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India"}]},{"given":"Xiangling","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411004, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1111\/coin.12202"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276390"},{"key":"3","first-page":"107","article-title":"Detection of seam carving and localization of seam insertions in digital images","author":"A. 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