Transform Invariant Approach to Video Fingerprinting

Abstract

Estimation of spatial-temporal transformation consistency in object level between the original video and its copies is one of the main issues arise in video ngerprinting. The key purpose of this research is to discover an e cient and excellent approach for the above mentioned problematic situation even though the comparison happens with longer length videos under various types of photometric and geometric transformations. Convert classical copy detection into high level pattern matching task was the proposed and applied approach in this scenario. In here frame wise SIFT interest point trajectory data provide precise and invariant information of relevant video in pattern matching phase. Finally classical challenges of video copy detection like brightness changes, blurs, zooming, size changes, cropping, illumination changes, noise, ratio changes, etc were addressed by proposed methodology successfully.