DocumentCode :
3085669
Title :
Watermark Image Recognition from Local Scale-Invariant Feature
Author :
Madane, Amol R.
Author_Institution :
Sardar Patel Coll. of Eng., Mumbai
fYear :
2009
fDate :
25-27 March 2009
Firstpage :
258
Lastpage :
263
Abstract :
This paper explains algorithm of digital image watermarking using DWT for copyright protection.The detail coefficients of second level host image after taking DWT is used as a watermark key for the watermark logo insertion and extraction process. A watermark image recognition system has been developed that uses new class of local image features.These local features of image are invariant to rotation,scaling and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The recognition proceeds by matching individual features to a database of features from known watermark images using a fast nearest neighbor algorithm, followed by Hough transform to identify clusters belonging to a single object. The effectiveness of local scale invariant feature is tested on original watermark logo, extracted watermark logo. We were able to design a prototype system,which provides user authentication.
Keywords :
Hough transforms; copy protection; copyright; discrete wavelet transforms; feature extraction; image coding; watermarking; Hough transform; copyright protection; digital image watermarking; discrete wavelet transform; extraction process; fast nearest neighbor algorithm; illumination; local scale-invariant feature; Digital images; Discrete wavelet transforms; Image databases; Image recognition; Lighting; Nearest neighbor searches; Noise robustness; Protection; Spatial databases; Watermarking; Correlation Coefficient; Discrete Wavelet Transform; Mean Square Error; Peak Signal to Noise Ratio; Scale Invariant Feature Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Modelling and Simulation, 2009. UKSIM '09. 11th International Conference on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4244-3771-9
Electronic_ISBN :
978-0-7695-3593-7
Type :
conf
DOI :
10.1109/UKSIM.2009.63
Filename :
4809774
Link To Document :
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