期刊：
Proceedings of SPIE - The International Society for Optical Engineering,2009年7496 ISSN：0277-786X
通讯作者：
Liu, L.(ll710915@yahoo.com.cn)
作者机构：
[Liu, Li] School of Computer Science and Technology, University of South China, HengYang 421001;[Peng, Fuyuan; Yang, Luo; Liu, Li] Department of Telecommunication, HuaZhong Science and Technology University, WuHan 430076
通讯机构：
School of Computer Science and Technology, University of South China, China
会议名称：
MIPPR 2009: Pattern Recognition and Computer Vision
会议时间：
Yichang, China
会议论文集名称：
MIPPR 2009: Pattern Recognition and Computer Vision
摘要：
The image information change law with the change of scale parameter is first studied in terms of regarding ramp edge and step edge as measurement of image information. Then the paper proposes a kind of adaptive recursive algorithm of scale parameter with the module of visual characters. The information of the image is uniformly distributed among each layer in the algorithm. The method can avoid the problem of complicated computation or over- distortion because of losing too much key information. The experimental results show that the uniformly distributed information is more reasonable for human to perceive an image which will be useful for higher-level image processing technologies such as object recognition.
期刊：
Journal of Computational Information Systems,2009年5(1):17-27 ISSN：1553-9105
通讯作者：
Wan, Y.(wypzll@163.com)
作者机构：
[Yang, Tianming; Wang, Fang; Wan, Yaping; Feng, Dan] School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;[Wan, Yaping; Liu, Li] School of Computer Science and Technology, Nanhua University, Hengyang 421001, China
通讯机构：
School of Computer Science and Technology, Huazhong University of Science and Technology, China
摘要：
Stable local feature detection is a fundamental component of many stereo vision problems such as 3-D reconstruction, object localization, and object tracking. A robust method for extracting scale-invariant feature points is presented. First, the Harris corners in three-level pyramid are extracted. Then, the points detected at the highest level of the pyramid are correctly propagated to the lower level by pyramid based scale invariant (PBSI) method. The corners detected repeatedly in different levels are chosen as final feature points. Finally, the characteristic scale is obtained based on maximum entropy method. The experimental results show that the algorithm has low computation cost, strong antinoise capability, and excellent performance in the presence of significant scale changes.
会议名称：
Multimedia and Ubiquitous Engineering, 2008. MUE 2008. International Conference on
摘要：
Designing storage systems to provide high availability in the face of failures needs the use of various data protection techniques, such as dual-controller RAID. The failure of RAID controller may cause RAID storage system to fail to respond to ongoing requests and to no longer be available to new requests. Heartbeat is used to detect controllers whether survival. So, the heartbeat cycle's impact on the high availability of a dual-controller hot-standby system has become the key of current research. To address the problem of fixed setting heartbeat in building high availability system currently, a self-adaptive heartbeat model of dual-controller, which can adjust heartbeat cycle based on the frequency of data read-write request, is designed to improve the high availability of dual-controller RAID storage system. Based on this model, the high availability stochastic Petri net model of fault detection was established and used to evaluate the effect of the availability. In addition, we define a SHA (self-adaptive heart ability) parameter to scale the ability of system heartbeat cycle to adapt to the environment when high availability system is at a changing environment of read and write requests. The results show that, relatively speaking with fixed configuration, the design can enhance dual controller RAID system high availability.
作者机构：
[彭复员] Department of Telecommunication, Huazhong Science and Technology University, Wuhan 430076, China;[赵坤; 万亚平] Department of Computer Science and Technology, Nanhua University, Hengyang 421001, China;[刘立] Department of Telecommunication, Huazhong Science and Technology University, Wuhan 430076, China, Department of Computer Science and Technology, Nanhua University, Hengyang 421001, China
通讯机构：
[Liu, L.] D;Department of Telecommunication, Huazhong Science and Technology University, China
摘要：
Contour information is regarded as important characteristic in computer vision. It is difficult to extract Contour information from the non-structural object due to its complicated structure. This paper present a novel concept of Multi-Scale Entropy (MSE) based on traditional Entropy that can be used to perform reliable extracting contours from non-structured objects such as smoking and rocks. The variety of image information amount was presented dynamically by this means. The Multi-Scale Entropy Difference (MSED) can present the break part of the image gray information and recognize the boundary of object and background effectively. Finally the non-structural object contours was extracted by Maximal Multi-Scale Entropy Difference (MMSED). Experiments have shown that the operator can extract stable contours from non-structural objects and eliminate the interior complex texture structure effectively.
