Python Image Processing Project - Copy-Move Image Forgery Detetcion - ClickMyProject
Copy-move forgery is a specific type of image tampering where a part of the image is copied and pasted somewhere else in the image with the intent to cover an important image feature. Hence, the goal in detection of copy-move forgeries is to detect image areas that are same or extremely similar.
In this process, we investigate the problem of detecting the copy-move forgery and describe an efficient and reliable passive-blind detection method.
The method used block-matching procedures, which first divided the image into the same size block, then applied improved singular value decomposition to all of the image blocks to yield a reduced dimension representation for forming the singular value feature matrix of image blocks which was lexicographically sorted.
Later, a matching step took place where the aim is to find the duplicated blocks based on their feature vectors. A forgery detection decision is made only image hashing and SSIM technique.
The experimental has done by different types of machine learning algorithm like, Support Vector Machine, Logistic Regression, Linear Regression, Naïve Bayes and Convolutional Neural Network.
The predicted result based on accuracy and comparing the algorithms.
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