A Fast Keypoint Based Hybrid Method for Copy Move Forgery Detection

Kumar, Sunil; Desai, J. V.; Mukherjee, S.

doi:10.12785/ijcds/040203

Cited by 14 publications

(9 citation statements)

References 21 publications

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“…The proposed technique parameters are set optimally based on previous best practices. Performance evaluation and numerical analysis of the proposed forgery detection technique are examined comparatively to one of the previously published technique [12], which is based as well on SURF and BRISK feature extraction techniques.…”

Section: Resultsmentioning

confidence: 99%

“…It accomplishes high performance, and minimizes computational cost. Journal of Computer and Communications Sunil Kumar [12] proposed a technique to detect forgery in images where SURF features are used for keypoints detection and BRISK is used for keypoints description. The proposed technique is invariant to rotation, translation, scaling and geometrical transformations.…”

Section: Related Workmentioning

confidence: 99%

“…the technique proposed in [12]. This technique is also based on the hybridization between SURF and BRISK.…”

Section: Performance Evaluation and Its Analysismentioning

confidence: 99%

“…The time taken by the proposed algorithm is much comparing to the technique in [12], because our supposed technique using more computations:…”

Section: ) Extracting Surf Keypoints;mentioning

confidence: 99%

“…2) In the refine stage by using bi-cubic interpolation, and there is no refine stage in technique proposed in [12].…”

Section: ) Extracting Surf Keypoints;mentioning

confidence: 99%

See 4 more Smart Citations

Copy-Move Forgeries Detection and Localization Using Two Levels of Keypoints Extraction

Samir¹,

Emary²,

Elsayed³

et al. 2019

JCC

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Copy-move offense is considerably used to conceal or hide several data in the digital image for specific aim, and onto this offense some portion of the genuine image is reduplicated and pasted in the same image. Therefore, Copy-Move forgery is a very significant problem and active research area to check the confirmation of the image. In this paper, a system for Copy Move Forgery detection is proposed. The proposed system is composed of two stages: one is called the detection stages and the second is called the refine detection stage. The detection stage is executed using Speeded-Up Robust Feature (SURF) and Binary Robust Invariant Scalable Keypoints (BRISK) for feature detection and in the refine detection stage, image registration using non-linear transformation is used to enhance detection efficiency. Initially, the genuine image is picked, and then both SURF and BRISK feature extractions are used in parallel to detect the interest keypoints. This gives an appropriate number of interest points and gives the assurance for finding the majority of the manipulated regions. RANSAC is employed to find the superior group of matches to differentiate the manipulated parts. Then, non-linear transformation between the best-matched sets from both extraction features is used as an optimization to get the best-matched set and detect the copied regions. A number of numerical experiments performed using many benchmark datasets such as, the CASIA v2.0, MICC-220, MICC-F600 and MICC-F2000 datasets. With the proposed algorithm, an overall average detection accuracy of 95.33% is obtained for evaluation carried out with the aforementioned databases. Forgery detection achieved True Positive Rate of 97.4% for tampered images with object translation, different degree of rotation and enlargement. Thus, results from different datasets have been set, proving that the proposed algorithm can individuate the altered areas, with high reliability and dealing with multiple cloning.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…the technique proposed in [12]. This technique is also based on the hybridization between SURF and BRISK.…”

Section: Performance Evaluation and Its Analysismentioning

confidence: 99%

“…The time taken by the proposed algorithm is much comparing to the technique in [12], because our supposed technique using more computations:…”

Section: ) Extracting Surf Keypoints;mentioning

confidence: 99%

“…2) In the refine stage by using bi-cubic interpolation, and there is no refine stage in technique proposed in [12].…”