Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies
Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/230425 |
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| author | Bo Liu Chi-Man Pun Xiao-Chen Yuan |
| author_facet | Bo Liu Chi-Man Pun Xiao-Chen Yuan |
| author_sort | Bo Liu |
| collection | DOAJ |
| description | Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image. |
| format | Article |
| id | doaj-art-94a53befb5a44983ba02c951c02c5014 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-94a53befb5a44983ba02c951c02c50142025-02-03T01:12:21ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/230425230425Digital Image Forgery Detection Using JPEG Features and Local Noise DiscrepanciesBo Liu0Chi-Man Pun1Xiao-Chen Yuan2Department of Computer and Information Science, University of Macau, Macau, ChinaDepartment of Computer and Information Science, University of Macau, Macau, ChinaDepartment of Computer and Information Science, University of Macau, Macau, ChinaWide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image.http://dx.doi.org/10.1155/2014/230425 |
| spellingShingle | Bo Liu Chi-Man Pun Xiao-Chen Yuan Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies The Scientific World Journal |
| title | Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies |
| title_full | Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies |
| title_fullStr | Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies |
| title_full_unstemmed | Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies |
| title_short | Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies |
| title_sort | digital image forgery detection using jpeg features and local noise discrepancies |
| url | http://dx.doi.org/10.1155/2014/230425 |
| work_keys_str_mv | AT boliu digitalimageforgerydetectionusingjpegfeaturesandlocalnoisediscrepancies AT chimanpun digitalimageforgerydetectionusingjpegfeaturesandlocalnoisediscrepancies AT xiaochenyuan digitalimageforgerydetectionusingjpegfeaturesandlocalnoisediscrepancies |