Detection of copy-move image forgery based on discrete cosine transform

Since powerful editing software is easily accessible, manipulation on images is expedient and easy without leaving any noticeable evidences. Hence, it turns out to be a challenging chore to authenticate the genuineness of images as it is impossible for human’s naked eye to distinguish between the ta...

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Main Authors: Alkawaz, Mohammed Hazim, Sulong, Ghazali, Saba, Tanzila, Rehman, Amjad
Format: Article
Published: Springer London 2016
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Online Access:http://eprints.utm.my/id/eprint/72802/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996866529&doi=10.1007%2fs00521-016-2663-3&partnerID=40&md5=fcdc374ddb7f455c23c9d821bb7d014b
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.728022017-11-20T08:03:19Z http://eprints.utm.my/id/eprint/72802/ Detection of copy-move image forgery based on discrete cosine transform Alkawaz, Mohammed Hazim Sulong, Ghazali Saba, Tanzila Rehman, Amjad QA76 Computer software Since powerful editing software is easily accessible, manipulation on images is expedient and easy without leaving any noticeable evidences. Hence, it turns out to be a challenging chore to authenticate the genuineness of images as it is impossible for human’s naked eye to distinguish between the tampered image and actual image. Among the most common methods extensively used to copy and paste regions within the same image in tampering image is the copy-move method. Discrete Cosine Transform (DCT) has the ability to detect tampered regions accurately. Nevertheless, in terms of precision (FP) and recall (FN), the block size of overlapping block influenced the performance. In this paper, the researchers implemented the copy-move image forgery detection using DCT coefficient. Firstly, by using the standard image conversion technique, RGB image is transformed into grayscale image. Consequently, grayscale image is segregated into overlying blocks of m × m pixels, m = 4.8. 2D DCT coefficients are calculated and reposition into a feature vector using zig-zag scanning in every block. Eventually, lexicographic sort is used to sort the feature vectors. Finally, the duplicated block is located by the Euclidean Distance. In order to gauge the performance of the copy-move detection techniques with various block sizes with respect to accuracy and storage, threshold D_similar = 0.1 and distance threshold (N)_d = 100 are used to implement the 10 input images in order. Consequently, 4 × 4 overlying block size had high false positive thus decreased the accuracy of forged detection in terms of accuracy. However, 8 × 8 overlying block accomplished more accurately for forged detection in terms of precision and recall as compared to 4 × 4 overlying block. In a nutshell, the result of the accuracy performance of different overlying block size are influenced by the diverse size of forged area, distance between two forged areas and threshold value used for the research. Springer London 2016 Article PeerReviewed Alkawaz, Mohammed Hazim and Sulong, Ghazali and Saba, Tanzila and Rehman, Amjad (2016) Detection of copy-move image forgery based on discrete cosine transform. Neural Computing and Applications . pp. 1-10. ISSN 0941-0643 (In Press) https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996866529&doi=10.1007%2fs00521-016-2663-3&partnerID=40&md5=fcdc374ddb7f455c23c9d821bb7d014b
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA76 Computer software
spellingShingle QA76 Computer software
Alkawaz, Mohammed Hazim
Sulong, Ghazali
Saba, Tanzila
Rehman, Amjad
Detection of copy-move image forgery based on discrete cosine transform
description Since powerful editing software is easily accessible, manipulation on images is expedient and easy without leaving any noticeable evidences. Hence, it turns out to be a challenging chore to authenticate the genuineness of images as it is impossible for human’s naked eye to distinguish between the tampered image and actual image. Among the most common methods extensively used to copy and paste regions within the same image in tampering image is the copy-move method. Discrete Cosine Transform (DCT) has the ability to detect tampered regions accurately. Nevertheless, in terms of precision (FP) and recall (FN), the block size of overlapping block influenced the performance. In this paper, the researchers implemented the copy-move image forgery detection using DCT coefficient. Firstly, by using the standard image conversion technique, RGB image is transformed into grayscale image. Consequently, grayscale image is segregated into overlying blocks of m × m pixels, m = 4.8. 2D DCT coefficients are calculated and reposition into a feature vector using zig-zag scanning in every block. Eventually, lexicographic sort is used to sort the feature vectors. Finally, the duplicated block is located by the Euclidean Distance. In order to gauge the performance of the copy-move detection techniques with various block sizes with respect to accuracy and storage, threshold D_similar = 0.1 and distance threshold (N)_d = 100 are used to implement the 10 input images in order. Consequently, 4 × 4 overlying block size had high false positive thus decreased the accuracy of forged detection in terms of accuracy. However, 8 × 8 overlying block accomplished more accurately for forged detection in terms of precision and recall as compared to 4 × 4 overlying block. In a nutshell, the result of the accuracy performance of different overlying block size are influenced by the diverse size of forged area, distance between two forged areas and threshold value used for the research.
format Article
author Alkawaz, Mohammed Hazim
Sulong, Ghazali
Saba, Tanzila
Rehman, Amjad
author_facet Alkawaz, Mohammed Hazim
Sulong, Ghazali
Saba, Tanzila
Rehman, Amjad
author_sort Alkawaz, Mohammed Hazim
title Detection of copy-move image forgery based on discrete cosine transform
title_short Detection of copy-move image forgery based on discrete cosine transform
title_full Detection of copy-move image forgery based on discrete cosine transform
title_fullStr Detection of copy-move image forgery based on discrete cosine transform
title_full_unstemmed Detection of copy-move image forgery based on discrete cosine transform
title_sort detection of copy-move image forgery based on discrete cosine transform
publisher Springer London
publishDate 2016
url http://eprints.utm.my/id/eprint/72802/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996866529&doi=10.1007%2fs00521-016-2663-3&partnerID=40&md5=fcdc374ddb7f455c23c9d821bb7d014b
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