SYSTEM FOR DETECTING IMAGE FORGERY

Abstract

ABSTRACT A system (100) for detecting image forgery, the system (100) comprising: an input module (102) comprising: a database stored with a plurality of images; a processor (104) communicatively coupled with the input module (102), wherein the processor (104) is configured to: receive the plurality of images from the input module (102), divide the plurality of images into a plurality of blocks, detect a duplicate block from the plurality of blocks, perform feature extraction to determine genuine blocks from the duplicate block, and provide an output image highlighting the duplicate block on the plurality of images by performing quantization and lexicographic sorting; a display module (106) configured to display the output image.

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to a field of image processing and, in particular, to a system and method for detecting image forgery through the identification of duplicate blocks within digital images. The method employs advanced computational techniques to enhance the accuracy and efficiency of forgery detection.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] With the proliferation of digital imagery, the potential for image forgery has increased significantly. Conventional , Claims:1. A system (100) for detecting image forgery, the system (100) comprising:
an input module (102) comprising:
a database stored with a plurality of images;
a processor (104) communicatively coupled with the input module (102), wherein the processor (104) is configured to:
receive the plurality of images from the input module (102),
diving the plurality of images into a plurality of blocks,
detect a duplicate block from the plurality of blocks,
perform feature extraction to determine genuine blocks from the duplicate block, and
providing an output image highlighting the duplicate block on the plurality of images by performing quantization and lexicographic sorting; and
a display module (106) configured to display the output image.

2. The system (100) as claimed in claim 1, wherein the processor (104) is configured to utilize a discrete cosine transform, K-nearest neighbour (KNN) and other techniques to obtain the output image.

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