With the intensively increasing of digital media new challenges has been created for authentication and protection of digital intellectual property. A hash function extracts certain features of a multimedia object e.g. an image and maps it to a fixed string of bits. A perceptual hash function unlike normal cryptographic hash is change tolerant for image processing techniques. Perceptual hash function also referred to as robust hash, like any other algorithm is prone to errors. These errors are false negative and false positive, of which false positive error is neglected compared to false negative errors. False positive occurs when an unknown object is identified as known. In this work a new method for raising false alarms in robust hash function is devised for evaluation purposes i.e. this algorithm modifies hash key of a target image to resemble a different image’s hash key without any significant loss of quality to the modified image. This algorithm is implemented in MATLAB using block mean value based hash function and successfully reduces hamming distance between target image and modified image with a good result and without significant loss to attacked imaged quality.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-12822 |
| Date | January 2016 |
| Creators | Amir Asgari, Azadeh |
| Publisher | Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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