Abstract: Super pixel segmentation is an effective technique for detecting copy-move forgery, which is a type of image manipulation where a portion of an image is copied and pasted onto another area of the same image. This technique works by grouping neighboring pixels with similar properties into perceptually meaningful units called super pixels.

These super pixels are used to identify regions of an image that have been manipulated by identifying identical clusters of pixels. Various techniques can be combined with super pixel segmentation to improve the accuracy of the detection process, such as feature extraction and machine learning algorithms. The use of super pixel segmentation for copy-move forgery detection simplifies the image analysis process, making it easier to detect duplicate regions in the image. As image manipulation becomes increasingly prevalent, the development of new and innovative techniques like super pixel segmentation will become increasingly important for ensuring the integrity of digital images.

 Index Terms - Super pixel segmentation, copy-move forgery, image manipulation, identical clusters of pixels, feature extraction, machine learning, accuracy, detection process, image analysis, digital images.

PDF | DOI: 10.17148/IJARCCE.2023.124175

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