Welcome to the InfoSci Platform
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: 10
ISBN13: 9781799830252|ISBN10: 179983025X|EISBN13: 9781799830269
DOI: 10.4018/978-1-7998-3025-2.ch031
Cite Chapter Cite Chapter

MLA

Yang, Liang, et al. "Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length." Digital Forensics and Forensic Investigations: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2020, pp. 475-484. https://doi.org/10.4018/978-1-7998-3025-2.ch031

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.), Digital Forensics and Forensic Investigations: Breakthroughs in Research and Practice (pp. 475-484). IGI Global. https://doi.org/10.4018/978-1-7998-3025-2.ch031

Chicago

Yang, Liang, et al. "Contrast Modification Forensics Algorithm Based on Merged Weight Histogram of Run Length." In Digital Forensics and Forensic Investigations: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 475-484. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-3025-2.ch031

Export Reference

Mendeley
Favorite

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.