With the expansion of satellite constellation,routing techniques for small-scale satellite networks have problems in routing overhead and forwarding efficiency.This paper proposes a vector segment routing method for l...With the expansion of satellite constellation,routing techniques for small-scale satellite networks have problems in routing overhead and forwarding efficiency.This paper proposes a vector segment routing method for large-scale multi layer satellite networks.A vector forwarding path is built based on the location between the source and the destination.Data packets are forwarded along this vector path,shielding the influence of satellite motion on routing forwarding.Then,a dynamic route maintenance strategy is suggested.In a multi layer satellite network,the low-orbit satellites are in charge of computing the routing tables for one area,and the routing paths are dynamically adjusted in the area in accordance with the network.The medium-orbit satellites maintain the connectivity of vector paths in multiple segmented areas.The forwarding mode based on the source and destination location improves the forwarding efficiency,and the segmented route maintenance mode decreases the routing overhead.The simulation results indicate that vector segment routing has significant performance advantages in end-to-end delay,packet loss rate,and throughput in a multi layer satellite network.We also simulate the impact of routing table update mechanism on network performance and overhead and give the performance of segmented vector routing in multi layer low-orbit satellite networks.展开更多
Minutiae-based fingerprint matching is the most commonly used in an automatic fingerprint identification system. In this paper, we propose a minutia matching method based on line segment vector. This method uses all t...Minutiae-based fingerprint matching is the most commonly used in an automatic fingerprint identification system. In this paper, we propose a minutia matching method based on line segment vector. This method uses all the detected minutiae （the ridge ending and the ridge bifurcation） in a fingerprint image to create a set of new vectors （line segment vector）. Using these vectors, we can determine a truer reference point more efficiently. In addition, this new minutiae vector can also increase the accuracy of the minutiae matching. By experiment on the public domain collections of fingerprint images fvc2004 DID set A and DB4 set A, the result shows that our algorithm can obtain an improved verification performance.展开更多
In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentati...In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance.展开更多
Image segmentation is a necessary step in image analysis. Support vector machine （SVM） approach is proposed to segment images and its segmentation performance is evaluated. Experimental results show that： the effec...Image segmentation is a necessary step in image analysis. Support vector machine （SVM） approach is proposed to segment images and its segmentation performance is evaluated. Experimental results show that： the effects of kernel function and model parameters on the segmentation performance are significant; SVM approach is less sensitive to noise in image segmentation; The segmentation performance of SVM approach is better than that of back-propagation multi-layer perceptron （BP-MLP） approach and fuzzy c-means （FCM） approach.展开更多
In this paper, we propose a fast centerline extraction method to be used for gradient and direction vector flow of active contours. The gradient and direction vector flow is a recently reported active contour model ca...In this paper, we propose a fast centerline extraction method to be used for gradient and direction vector flow of active contours. The gradient and direction vector flow is a recently reported active contour model capable of significantly improving the image segmentation performance especially for complex object shape, by seamlessly integrating gradient vector flow and prior directional information. Since the prior directional information is provided by manual line drawing, it can be inconvenient for inexperienced users who might have difficulty in finding the best place to draw the directional lines to achieve the best segmentation performance. This paper describes a method to overcome this problem by automatically extracting centerlines to guide the users for providing the right directional information. Experimental results on synthetic and real images demonstrate the feasibility of the proposed method.展开更多
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1806100in part by the Natural Science Foundation of China under Grant U19B2025 and Grant 62001347+1 种基金in part by the Key Research and Development Program of Shaanxi under Grants 2022ZDLGY05-02 and 2021KWZ-05in part by the Fundamental Research Funds for the Central Universities under Grant QTZX22161
文摘With the expansion of satellite constellation,routing techniques for small-scale satellite networks have problems in routing overhead and forwarding efficiency.This paper proposes a vector segment routing method for large-scale multi layer satellite networks.A vector forwarding path is built based on the location between the source and the destination.Data packets are forwarded along this vector path,shielding the influence of satellite motion on routing forwarding.Then,a dynamic route maintenance strategy is suggested.In a multi layer satellite network,the low-orbit satellites are in charge of computing the routing tables for one area,and the routing paths are dynamically adjusted in the area in accordance with the network.The medium-orbit satellites maintain the connectivity of vector paths in multiple segmented areas.The forwarding mode based on the source and destination location improves the forwarding efficiency,and the segmented route maintenance mode decreases the routing overhead.The simulation results indicate that vector segment routing has significant performance advantages in end-to-end delay,packet loss rate,and throughput in a multi layer satellite network.We also simulate the impact of routing table update mechanism on network performance and overhead and give the performance of segmented vector routing in multi layer low-orbit satellite networks.
文摘Minutiae-based fingerprint matching is the most commonly used in an automatic fingerprint identification system. In this paper, we propose a minutia matching method based on line segment vector. This method uses all the detected minutiae （the ridge ending and the ridge bifurcation） in a fingerprint image to create a set of new vectors （line segment vector）. Using these vectors, we can determine a truer reference point more efficiently. In addition, this new minutiae vector can also increase the accuracy of the minutiae matching. By experiment on the public domain collections of fingerprint images fvc2004 DID set A and DB4 set A, the result shows that our algorithm can obtain an improved verification performance.
基金Project supported by the National Natural Science Foundation of China （Grant No.60572127）, the Development Foundation of Shanghai Municipal Commission of Education （Grant No.05AZ43）, and the Shanghai Leading Academic Discipline Project （Grant No.T0102）
文摘In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance.
基金Supported by the National Natural Science Foundation of China (No. 60475024)
文摘Image segmentation is a necessary step in image analysis. Support vector machine （SVM） approach is proposed to segment images and its segmentation performance is evaluated. Experimental results show that： the effects of kernel function and model parameters on the segmentation performance are significant; SVM approach is less sensitive to noise in image segmentation; The segmentation performance of SVM approach is better than that of back-propagation multi-layer perceptron （BP-MLP） approach and fuzzy c-means （FCM） approach.
文摘In this paper, we propose a fast centerline extraction method to be used for gradient and direction vector flow of active contours. The gradient and direction vector flow is a recently reported active contour model capable of significantly improving the image segmentation performance especially for complex object shape, by seamlessly integrating gradient vector flow and prior directional information. Since the prior directional information is provided by manual line drawing, it can be inconvenient for inexperienced users who might have difficulty in finding the best place to draw the directional lines to achieve the best segmentation performance. This paper describes a method to overcome this problem by automatically extracting centerlines to guide the users for providing the right directional information. Experimental results on synthetic and real images demonstrate the feasibility of the proposed method.
