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Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length

Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length

Liang Yang, Tiegang Gao, Yan Xuan, Hang Gao
Copyright: © 2020 |Pages: 11
ISBN13: 9781799824664|ISBN10: 1799824667|EISBN13: 9781799824671
DOI: 10.4018/978-1-7998-2466-4.ch016
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MLA

Yang, Liang, et al. "Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length." Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 255-265. https://doi.org/10.4018/978-1-7998-2466-4.ch016

APA

Yang, L., Gao, T., Xuan, Y., & Gao, H. (2020). Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length. In I. Management Association (Ed.), Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications (pp. 255-265). IGI Global. https://doi.org/10.4018/978-1-7998-2466-4.ch016

Chicago

Yang, Liang, et al. "Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length." In Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 255-265. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2466-4.ch016

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Abstract

A novel image forensic algorithm against contrast modification based on merged weight histogram of run length is proposed. In the proposed algorithm, the run length histogram features were firstly extracted, and then those of different orientation were subsequently merged; after normalization of the prior features, the authors calculated leaps in the histogram numerically; lastly, the generated features of authentic and tampered images were trained by a SVM classifier. Large amounts of experiments show that, the proposed algorithm has low cost of computation complexity, compared with some existing scheme, and it has better performance with many test databases, furthermore, the proposed algorithm can effectively detect local contrast modification of image.

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