DocumentCode :
618718
Title :
Optimizations using the genetic algorithm for reversible watermarking
Author :
Panyindee, C. ; Pintavirooj, Chuchart
Author_Institution :
Dept. of Electr. Eng., King Mongkut´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
fYear :
2013
fDate :
15-17 May 2013
Firstpage :
1
Lastpage :
5
Abstract :
Important requirements for reversible data hiding techniques: the embedding capacity should be large and distortion should be low. This paper represents a high performance reversible watermarking technique which involves adaptable predictor and sorting parameter to suit each image and each payload in order get lowest image distortion. Our proposed method relies on a well-known prediction error (PE) expansion technique. Having small PE values and a harmonious PE sorting parameter will greatly decrease distortion. In order to get adaptable tools, Gaussian weight predictor and expanded variance mean were used as parameters in this work. A genetic algorithm has also been introduced to optimize all parameters and produce the best results possible. Implementation showed a significantly improved result compared to previous work.
Keywords :
Gaussian processes; data encapsulation; embedded systems; genetic algorithms; image watermarking; Gaussian weight predictor; embedding capacity; expanded variance mean parameter; genetic algorithm; harmonious PE sorting parameter; image distortion; optimization; prediction error expansion technique; reversible data hiding technique; reversible watermarking technique; Biological cells; Genetic algorithms; PSNR; Payloads; Prediction algorithms; Sorting; Watermarking; Gaussian weight predictor; Prediction error (PE); expanded variance mean; genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on
Conference_Location :
Krabi
Print_ISBN :
978-1-4799-0546-1
Type :
conf
DOI :
10.1109/ECTICon.2013.6559504
Filename :
6559504
Link To Document :
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