Copy-Move Forgery Detection with GLCM and Euclidian Distance Technique in Image Processing
Parul Sharma1, Harpreet Kaur2
1Parul Sharma, Research Scholar, Chandigarh University, Mohali (Punjab), India.
2Harpreet Kaur, Assistant Professor, Chandigarh University, Mohali (Punjab), India.
Manuscript received on 13 June 2019 | Revised Manuscript received on 09 July 2019 | Manuscript Published on 17 July 2019 | PP: 43-47 | Volume-8 Issue-1C2 May 2019 | Retrieval Number: A10080581C219/2019©BEIESP
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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: The approach using which the forgery part of an image can be detected is called image forgery detection. The copy-move part of an image can be detected using copy-move forgery detection technique. The various techniques have been designed so far for the copy-move forgery detection. The techniques which are designed for the copy-move forgery detection are based on the three steps which are feature extraction, Euclidian distance and image marking. In the previous method DWT algorithm is applied for the feature extraction and Euclidian distance is calculated for the forgery part detection. The GLCM algorithm is applied in this research for the feature extraction and Euclidian distance is calculated for the pixel detection. MATLAB simulator is used to implement the proposed technique and perform evaluations by calculating various parametric values.
Keywords: Copy-Move Forgery, DWT, GLCM, Euclidian Distance.
Scope of the Article: Image Processing and Pattern Recognition