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2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Genetic Algorithm-Backpropagation Network Hybrid Architecture for Grayscale Image Watermarking in DCT Domain
Dalian, China
October 14-October 16
ISBN: 978-0-7695-4517-2
| ASCII Text | x | ||
| Charu Agarwal, Anurag Mishra, Arpita Sharma, "Genetic Algorithm-Backpropagation Network Hybrid Architecture for Grayscale Image Watermarking in DCT Domain," Intelligent Information Hiding and Multimedia Signal Processing, International Conference on, pp. 177-180, 2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/IIHMSP.2011.72, author = {Charu Agarwal and Anurag Mishra and Arpita Sharma}, title = {Genetic Algorithm-Backpropagation Network Hybrid Architecture for Grayscale Image Watermarking in DCT Domain}, journal ={Intelligent Information Hiding and Multimedia Signal Processing, International Conference on}, volume = {0}, year = {2011}, isbn = {978-0-7695-4517-2}, pages = {177-180}, doi = {http://doi.ieeecomputersociety.org/10.1109/IIHMSP.2011.72}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Intelligent Information Hiding and Multimedia Signal Processing, International Conference on TI - Genetic Algorithm-Backpropagation Network Hybrid Architecture for Grayscale Image Watermarking in DCT Domain SN - 978-0-7695-4517-2 SP177 EP180 A1 - Charu Agarwal, A1 - Anurag Mishra, A1 - Arpita Sharma, PY - 2011 KW - Human Visual System KW - GA based BPN KW - Luminance Sensitivity KW - Edge Sensitivity KW - Contrast Sensitivity KW - Similarity Correlation Parameter VL - 0 JA - Intelligent Information Hiding and Multimedia Signal Processing, International Conference on ER - | |||
In this paper, Human Visual System (HVS) characteristics are modeled using a Genetic Algorithm (GA) based technique for the determination of weights in a BPN (GA/BPN) for the purpose of image watermarking. The GA based BP network is trained by 27 inference rules comprising of three input HVS features namely luminance sensitivity, edge sensitivity computed using threshold and contrast sensitivity computed using variance. The GA / BP network block wise produces a single output weighting factor which is used to embed two different watermarks -- (a) a sequence of normalized random numbers and (b) a binary image, with in the host image in the transform (DCT) domain. The high computed value of PSNR parameter indicates that the signed image has good perceptible quality. The watermark is extracted from the signed image using Cox's algorithm. The embedded and extracted watermarks are compared and SIM(X, X^* ) correlation parameter is computed.
Index Terms:
Human Visual System, GA based BPN, Luminance Sensitivity, Edge Sensitivity, Contrast Sensitivity, Similarity Correlation Parameter
Citation:
Charu Agarwal, Anurag Mishra, Arpita Sharma, "Genetic Algorithm-Backpropagation Network Hybrid Architecture for Grayscale Image Watermarking in DCT Domain," iih-msp, pp.177-180, 2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2011
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