IEEE Trans Image Process - On the selection of optimal feature region set for robust digital image watermarking.

Tópicos

{ imag(2830) propos(1344) filter(1198) }
{ featur(3375) classif(2383) classifi(1994) }
{ method(984) reconstruct(947) comput(926) }
{ perform(1367) use(1326) method(1137) }
{ problem(2511) optim(1539) algorithm(950) }
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Resumo

A novel feature region selection method for robust digital image watermarking is proposed in this paper. This method aims to select a nonoverlapping feature region set, which has the greatest robustness against various attacks and can preserve image quality as much as possible after watermarked. It first performs a simulated attacking procedure using some predefined attacks to evaluate the robustness of every candidate feature region. According to the evaluation results, it then adopts a track-with-pruning procedure to search a minimal primary feature set which can resist the most predefined attacks. In order to enhance its resistance to undefined attacks under the constraint of preserving image quality, the primary feature set is then extended by adding into some auxiliary feature regions. This work is formulated as a multidimensional knapsack problem and solved by a genetic algorithm based approach. The experimental results for StirMark attacks on some benchmark images support our expectation that the primary feature set can resist all the predefined attacks and its extension can enhance the robustness against undefined attacks. Comparing with some well-known feature-based methods, the proposed method exhibits better performance in robust digital watermarking.

Resumo Limpo

novel featur region select method robust digit imag watermark propos paper method aim select nonoverlap featur region set greatest robust various attack can preserv imag qualiti much possibl watermark first perform simul attack procedur use predefin attack evalu robust everi candid featur region accord evalu result adopt trackwithprun procedur search minim primari featur set can resist predefin attack order enhanc resist undefin attack constraint preserv imag qualiti primari featur set extend ad auxiliari featur region work formul multidimension knapsack problem solv genet algorithm base approach experiment result stirmark attack benchmark imag support expect primari featur set can resist predefin attack extens can enhanc robust undefin attack compar wellknown featurebas method propos method exhibit better perform robust digit watermark

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