A Novel Technique for Copy Move Forgery Detection using Grey Level Co-occurrence Matrix
Parul Sharma1, Harpreet Kaur2, Simran Uppal3
1Parul Sharma, Department of Computer science, Chandigarh University, Mohali (punjab), India.
2Harpreet Kaur, Department of Computer science, Chandigarh University, Mohali (punjab), India.
3Simran Uppal, Department of Computer science, Chandigarh University, Mohali (punjab), India.
Manuscript received on 05 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 26 August 2019 | PP: 581-586 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10910789S19/19©BEIESP | DOI: 10.35940/ijitee.I1091.0789S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper we have studied the GLCM approach as an improvement over SWT-DCT method for feature extraction for CMFD. We have carefully studied the previously used methods and also studied the SWT-DCT method for improvement in features. We have proposed a method for the use of GLCM instead of SWT-DCT method for feature extraction which will improve the results of CMFD method used in the base work framework.
Keywords: CMFD, GLC, SWT.
Scope of the Article: Cloud Resources Utilization in IoT