ABSTRACT
PROJECT OUTPUT
Image forgery means manipulation of digital image to
conceal meaningful information of the image. The detection of forged
image is driven by the need of authenticity and to maintain
integrity of the image. A copy move forgery detection theme
victimization adaptive over segmentation and have purpose feature
matching is proposed. The proposed scheme integrates both block
based and key point based forgery detection methods. The
proposed adaptive over segmentation algorithm segments the host
image into non over lapping and irregular blocks adaptively. Then,
the feature points are extracted from each block as block
features, and the block features are matched with one another to
locate the labeled feature points; this procedure can
approximately indicate the suspected forgery regions. To
detect the forgery regions more accurately, we propose the
forgery region extraction algorithm which replaces the features
point with small super pixels as feature blocks and them merges
the neighboring blocks that have similar local color features
into the feature block to generate the merged regions.
Finally, it applies the morphological operation to merged
regions to generate the detected forgery regions. In cut paste image
forgery detection, proposed digital image forensic techniques
capable of detecting global and local contrast enhancement,
identifying the use of histogram equalization.
PROJECT OUTPUT
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Contact:
Mr. Roshan P. Helonde
Mobile:+91-7276355704
