文章基本信息

标题：Spliced Image Classification and Tampered Region Localization Using Local Directional Pattern
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作者：Surbhi Sharma ; Umesh Ghanekar
期刊名称：International Journal of Image, Graphics and Signal Processing
印刷版ISSN：2074-9074
电子版ISSN：2074-9082
出版年度：2019
卷号：11
期号：3
页码：35-42
DOI：10.5815/ijigsp.2019.03.05
出版社：MECS Publisher
摘要：In this paper the authors have proposed a spliced image detection algorithm based on Local Directional Pattern (LDP). The output of many splicing detection techniques is either to classify spliced image from authentic images or to localize the spliced region. But the proposed algorithm has ability to classify and to localize the spliced region. First, the original image (RGB color space) is converted to Ycbcr color space. The histogram of LDP of chrominance component of suspect image is used in classification. Whereas for localization of spliced region, the chrominance component of input image is divide into overlapping blocks; then, the LDP of each block is calculated. The standard deviation of each block is used as clue to visualize the spliced region. The experimental results are calculated in terms of accuracy, specificity (true negative tare), sensitivity (true positive rate) and error rate and proves effectiveness of the proposed algorithm. The accuracy of the proposed algorithm is 98.55 %. The algorithm is also robust against post splicing image processing operation such as gaussian blur, additive white gaussian noise, JPEG compression and scaling however, previous techniques have not considered these experimental environment.
关键词：Passive image tampering detection;Splicing detection;Local Directional Pattern;SVM