2015 International Conference on Information Processing (ICIP) Vishwakarma Institute of Technology. Dec 16-19, 2015
Robust Image Hashing Algorithm for Detecting and Localizing Image Tamper in Small Region Swati A.Khavare
Amrita A. Manjrekar
Computer Science and Technology Department of Technology, Shivaji University Kolhapur, India
[email protected]
Computer Science and Technology Department of Technology, Shivaji University Kolhapur, India
[email protected]
Abstract Paper proposes the novel technique for Active tamper detection and tamper localization, which uses image hashing algorithm applied on extended image based on ring partition and Non Negative Matrix Factorization (NMF). Key contribution is tamper detection in small region especially corner regions and exact localization of that tampered object. Particular tampered region is localized with the help of recursive use of image hashing algorithm on each partition of image in significantly less time. Experiments are carried out on various types of more than 200 images with different dimensions and memory space. Experimental results proved that this system has best perceptual robustness and discriminative capability. The system is able to detect and locate tamper at any region of image even from unrepresented corner region. The system is useful in many applications where original image plays an important role.
gray level, color combination, contrast, rotation, scaling, shapes, compression details, sharpness etc. In certain situations, original image is available. Comparison of the features of original image with the tampered image can ascertain the extent of tampering. Sometime image is not changed but just rotated or scaled, but few algorithms are not able to detect these operations and give positive result for tamper detection. Image tampering detection techniques are classified into two groups namely active tampering detection and passive tampering detection [02].
Keywords-Image Tampering; Image Hashing; NMF; Perceptual Robustness
I. INT RODUCT ION Digital image technologies have become mandatory part of many applications. Capturing, storing, sharing, editing digital images have become very common in practice with the help of different digital devices like digital camera, video camera, digital scanner, smart phones etc. and image processing tools including Adobe Photoshop, Corel Paint shop etc. It is very easy to tamper the original image that is difficult to identify. An image can be tampered by various ways such as cut-paste, copy-move, compression, retouching, slicing and by many other manipulating operations [01].This is dangerous in many applications where original images are very valuable. Image can be tampered with different motivations like transferring incorrect information, or modified information. For example Fig.1 (a) shows original image and Fig.1 (b) shows its tampered version generated by deleting building from image. Fig. 2(b) shows original image is modified by inserting copying more waterfalls in it Fig.2 (a). Image tampering can cause problem in different important fields such as military applications, GIS based applications, medical data application and even someones personal data. Tampering is normally done in an image in order to either produce false proof or to make the image more pleasant for appearance. Different research issues related to digital images tampering detection are object identification, presence of noise, color or
978-1-4673-7758-4/15/$31.00 ©2015 IEEE
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Fig.1.a) Original Image 610×362 dpi (b)T ampered Image :Building deleted
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Fig2.a) Original Image 275×183dpi (b)T ampered Image :Waterfalls inserted
A. Active Tampering Detection Techniques under this group are also known as informed approach. These techniques use in-built construct to provide security to the image. Image tampering is detected using following methods: 1) Data hiding approach: In this approach, the secondary data embedded into the image. 2) Digital signature: Image hash functions are used to generate image hash value which is depends on the
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