An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized r...An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.展开更多
A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation inf...A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation information is attained with a winner-take-all rule. Subsequently, the resulting orientation mapping array is operated by uniform local binary pattern. Accordingly, LBOCode image is achieved which contains palmprint orientation information in pixel level. Further we divide the LBOCode image into several equal-size and nonoverlapping regions, and extract the statistical code histogram from each region independently, which builds a global description of palmprint in regional level. In matching stage, the matching score between two palmprints is achieved by calculating the two spatial enhanced histograms＇ dissimilarity, which brings the benefit of computational simplicity. Experimental results demonstrate that the proposed method achieves more promising recognition performance compared with that of several state-of-the-art methods.展开更多
In the context of object oriented video coding, the encoding of segmentation maps defined by contour networks is particularly critical. In this paper, we present a lossy contour network encoding algorithm where both t...In the context of object oriented video coding, the encoding of segmentation maps defined by contour networks is particularly critical. In this paper, we present a lossy contour network encoding algorithm where both the rate distortion contour encoding based on maximum operator and the prediction error for the current frame based on quadratic motion model are combined into a optimal polygon contour network compression scheme. The bit rate for the contour network can be further reduced by about 20% in comparison with that in the optimal polygonal boundary encoding scheme using maximum operator in the rate distortion sense.展开更多
文摘An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.
基金supported partly by the National Grand Fundamental Research 973 Program of China under Grant No. 2004CB318005the Doctoral Candidate Outstanding Innovation Foundation under Grant No.141092522the Fundamental Research Funds under Grant No.2009YJS025
文摘A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation information is attained with a winner-take-all rule. Subsequently, the resulting orientation mapping array is operated by uniform local binary pattern. Accordingly, LBOCode image is achieved which contains palmprint orientation information in pixel level. Further we divide the LBOCode image into several equal-size and nonoverlapping regions, and extract the statistical code histogram from each region independently, which builds a global description of palmprint in regional level. In matching stage, the matching score between two palmprints is achieved by calculating the two spatial enhanced histograms＇ dissimilarity, which brings the benefit of computational simplicity. Experimental results demonstrate that the proposed method achieves more promising recognition performance compared with that of several state-of-the-art methods.
基金upported by the National Natural Science Foundation of China!( 6 95 72 0 2 3)bytheKeyProjectfromtheShanghaiEducationComm
文摘In the context of object oriented video coding, the encoding of segmentation maps defined by contour networks is particularly critical. In this paper, we present a lossy contour network encoding algorithm where both the rate distortion contour encoding based on maximum operator and the prediction error for the current frame based on quadratic motion model are combined into a optimal polygon contour network compression scheme. The bit rate for the contour network can be further reduced by about 20% in comparison with that in the optimal polygonal boundary encoding scheme using maximum operator in the rate distortion sense.
