Abstract: With the expanding utilize of advanced pictures in different applications, the issue of picture fraud has ended up more predominant than ever One of the greatest issues these days is picture frauds or control using different procedures In this paper, we propose a novel advanced picture fraud location framework based on Convolutional Neural Systems (CNNs) that can identify different sorts of picture controls, counting copy-move, grafting, and correcting. Our proposed framework coordinating Mistake Level Investigation (ELA) with profound learning strategies to supply a more exact and dependable arrangement to the issue of computerized picture imitation location. We assessed the proposed framework on a dataset of real-world pictures and accomplished a tall location precision of 93% Our framework outflanked existing strategies for picture imitation location and illustrated its potential for different applications, counting forensics, security, and computerized picture investigation. A convolutional neural organize that has been appeared successful for picture preparing is utilized at first. Generally, the proposed CNN-based picture imitation location framework offers a vigorous and successful arrangement to the developing issue of picture control and fraud in today's visual media scene. The execution of the proposed strategy is tried quantitatively, and picture alteration is distinguished
Keywords: Digital image analysis, Convolutional neural network (CNN), Error Level Analysis (ELA), Image processing.
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DOI:
10.17148/IJARCCE.2024.13440
