Showing papers by "Nagaaki Ohyama published in 2006"

Experimental evaluation of fingerprint verification system based on double random phase encoding.

Abstract: We proposed a smart card holder authentication system that combines fingerprint verification with PIN verification by applying a double random phase encoding scheme. In this system, the probability of accurate verification of an authorized individual reduces when the fingerprint is shifted significantly. In this paper, a review of the proposed system is presented and preprocessing for improving the false rejection rate is proposed. In the proposed method, the position difference between two fingerprint images is estimated by using an optimized template for core detection. When the estimated difference exceeds the permissible level, the user inputs the fingerprint again. The effectiveness of the proposed method is confirmed by a computational experiment; its results show that the false rejection rate is improved.

High-fidelity video and still-image communication based on spectral information: Natural Vision system and its applications

Abstract: In addition to the great advancement of high-resolution and large-screen imaging technology, the issue of color is now receiving considerable attention as another aspect than the image resolution. It is difficult to reproduce the original color of subject in conventional imaging systems, and that obstructs the applications of visual communication systems in telemedicine, electronic commerce, and digital museum. To breakthrough the limitation of conventional RGB 3-primary systems, "Natural Vision" project aims at an innovative video and still-image communication technology with highfidelity color reproduction capability, based on spectral information. This paper summarizes the results of NV project including the development of multispectral and multiprimary imaging technologies and the experimental investigations on the applications to medicine, digital archives, electronic commerce, and computer graphics.

Multispectral Image Compression for Improvement of Colorimetric and Spectral Reproducibility by Nonlinear Spectral Transform

Abstract: The article proposes a multispectral image compression scheme using nonlinear spectral transform for better colorimetric and spectral reproducibility. In the method, we show the reduction of colorimetric error under a defined viewing illuminant and also that spectral accuracy can be improved simultaneously using a nonlinear spectral transform called Labplus, which takes into account the nonlinearity of human color vision. Moreover, we show that the addition of diagonal matrices to Labplus can further preserve the spectral accuracy and has a generalized effect of improving the colorimetric accuracy under other viewing illuminants than the defined one. Finally, we discuss the usage of the first-order Markov model to form the analysis vectors for the higher order channels in Labplus to reduce the computational complexity. We implement a multispectral image compression system that integrates Labplus with JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for a 16-band multispectral image show the effectiveness of the proposed scheme.

Multispectral image compression for high fidelity colorimetric and spectral reproduction

Abstract: The article aims to provide a solution for multispectral image compression for high color reproducibility with preservation to spectral accuracy. In the method previously proposed to reduce the colorimetric error of the reconstructed multispectral image, a weighting matrix is incorporated to Karhunen-Loeve transform (KLT) as the spectral transform for multispectral image compression, which accounts for the color matching functions of human observers as well as the viewing illuminants. However, the colorimetric improvements are obtained on the cost of degradation of spectral accuracy. In this paper, we show that the reduction of colorimetric error and the preservation of spectral accuracy is a tradeoff that can be controlled by adding a diagonal matrix that is composed of a scalar multiple of an identity matrix to the weighting matrix of KLT. As the result, the small values in the weighting matrix can be lifted up, thus reduce the spectral errors in the corresponding reconstructed multispectral image bands. We implement a multispectral image compression system that integrates the proposed spectral transforms with the addition of diagonal matrix and JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for three 16-band multispectral images show that spectral accuracy can be improved without loss of substantial color reproducibility if the magnitude of the scalar in the diagonal matrix is chosen appropriately.