Comparison of Edge Detection Algorithms for Texture Analysis on Copy-Move Forgery Detection Images

Feature extraction in Copy-Move Forgery Detection (CMFD) is crucial to facilitate image forgery analysis. Edge detection one of the processes extract specific information from (CMF) Images. It sensitizes amount and filters out useless ones while preserving important structural properties image. This paper compares five edge methods: Robert, Sobel, Prewitt (first Derivative), Laplacian, Canny detectors (second Derivatives). CMFD evaluation datasets images (MICC-F220) are tested with both methods comparison. The operators were implemented their respective convolution masks. Robert a 2x2 mask, Sobel 3x3 Laplacian canny used adjustable These masks determine quality detected edges. Edges reflect great-intensity contrast that either darker or brighter.