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Hierarchy SURF Feature Clustering for Image Forgery Detection


Author : Neha Sharma and Pallavi Gupta

Pages : 523-527, DOI: https://doi.org/10.14741/ijcet/v.12.6.5
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Abstract

Today manipulation of digital images has become easy due to powerful computers, advanced photo-editing software packages and high-resolution capturing devices. Verifying the integrity of images and detecting traces of tampering without requiring extra prior knowledge of the image content or any embedded watermarks is an important research field. Copy move is the most common image tampering technique used due to its simplicity and effectiveness, in which parts of the original image is copied, moved to a desired location and pasted. This is usually done in order to hide certain details or to duplicate certain aspects of an image. This paper is an attempt for surveying the recent developments in the field of Copy move image forgery detection and complete bibliography is presented on blind methods for forgery detection. As the advent and growing popularity of image editing software, digital images can be manipulated easily without leaving obvious visual clues. If the tampered images are abused, it may lead to potential social, legal or private consequences. To this end, it’s very necessary and also challenging to find effective methods to detect digital image forgeries. In This works, a fast keypoint based method to detect image copy move forgery is will be used based on the SIFT (scale-invariant feature transform) descriptors, which are invariant to rotation, scaling etc. Results of experiments indicate that the proposed method is valid in detecting the image region duplication and quite robust to additive noise and blurring. For Clustering of Keypoints Clusting algorithm will be used.

Keywords: Clustering algorithm, Image tampering technique, SIFT etc.

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