000			01969nam a22001457a 4500
999			_c60375 _d60372
100			_aMumtaz Ali _a13MCSE04 _aSupervisor - Dr. Umair Ali Khan
100			_a13MCSE04
245			_aPerformance Comparison of Feature Detectors in Image Forgery Detection (ME Thesis)
260			_aNawabshah: _bQUEST, _c2016.
300			_a56p.
500			_aABSTRACT The authenticity of digital images has remained questionable ever since the technology has progressed to the extent where a plethora of freely available software can drastically change the image contents with much less effort. This offers a dedicated challenge to ascertain the veracity of a digital image, especially when it is to be presented as legal evidence. A number of techniques have been proposed to detect image forgery, albeit their respective efficacy depends on the type of forgery and image features. Moreover, their respective performance with respect to accuracy and execution time also varies. This thesis focuses on the most frequently used image forgery referred to as. copy­ move forgery. The work carried out in this thesis is two-fold. First. n hybrid approach combining the existing block-based and non-block-based techniques of copy-move forgery has been proposed. second, the performance of the proposed techniques has been evaluated with different image feature, including SIFT, SURF MSER, MinEgen, FAST and Harris. The evaluation criteria comprising accuracy, Precision, recall and execution time help to select a desired tradeoff between accuracy and execution time. The results proposed in the thesis show that the proposed image forgery detection technique can successfully detect copy-move forgery with remarkably high accuracy and reasonable execution time. Apart from this, the proposed technique also works fine with the smoothed and brightened images.
700			_aDepartment of Computer System Engineering
856			_uhttps://tinyurl.com/v2ymcexv
942			_cTHESIS