Jessada Karnjana

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This paper proposes an audio watermarking scheme based on singular-spectrum analysis (SSA) and differential evolution. In our framework, a watermark is embedded into an audio signal by modifying the amplitude of some oscillatory components which are decomposed by SSA, and a parameter set for the modification is determined by differential evolution. Test(More)
Typically, the conventional image enhancement methods have a problem concerning the over- enhancement in an image which contains both less-visible and nicely-visible areas in common. To solve such a problem, we propose a novel contrast enhancement method based on a non-linear scaling function and the singular value decomposition (SVD). The SVD is used to(More)
This paper proposes an inaudible and robust audio-information-hiding scheme based on the singular-spectrum analysis (SSA) and a psychoacoustic model. SSA is used to decompose the host signals into several additive oscillatory components. The hidden information is embedded into the host signals by modifying amplitudes of some oscillatory components. To(More)
This paper reports comparative evaluations of the watermarking methods we previously proposed with four other methods. Three of the proposed methods are based on the concept of embedding inaudible watermarks into an original sound by controlling the phase characteristics of the sound in relation to the characteristics of cochlear delay (non-blind, blind,(More)
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