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	Real-time video compressing under DSP/BIOS (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2009 - Medical Imaging, Parallel Processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image Processing and Pattern Recognition, October 30, 2009 - November 1, 2009, Yichang, China Chen Q.-P.; Li G.-J. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 This paper presents real-time MPEG-4 Simple Profile video compressing based on the DSP processor. The programming framework of video compressing is constructed using TMS320C6416 Microprocessor the architecture level optimizations are used to improve software pipeline. The system used DSP/BIOS to realize multi-thread scheduling. The whole system realizes high speed transition of a great deal of data. Experimental results show the encoder can realize real-time encoding of 768*576 TDS510 simulator and PC. It uses embedded real-time operating system DSP/BIOS and the API functions to build periodic function 25 frame/s video images. 2009 Copyright SPIE - The International Society for Optical Engineering. tasks and interruptions etcs. Realize real-time video compressing. To the questions of data transferring among the system. Based on the architecture of the C64x DSP utilized double buffer switched and EDMA data transfer controller to transit data from external memory to internal and realize data transition and processing at the same time
	A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE) 会议论文 OAI收割 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China Zhao X.; Fu D.; Zhai L. 收藏 \| 浏览/下载：68/0 \| 提交时间：2013/03/25 Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First decompose and reconstruct the image by wavelet packet. Before constructing the image use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented showing the quality of the proposed method. 2008 IEEE.
	High-accuracy real-time automatic thresholding for centroid tracker (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Zhang Y. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 Many of the video image trackers today use the centroid as the tracking point. In engineering we can get several key pairs of peaks which can include the target and the background around it and use the method of Otsu to get intensity thresholds from them. According to the thresholds it give a great help for us to get a glancing size a target's centroid is computed from a binary image to reduce the processing time. Hence thresholding of gray level image to binary image is a decisive step in centroid tracking. How to choose the feat thresholds in clutter is still an intractability problem unsolved today. This paper introduces a high-accuracy real-time automatic thresholding method for centroid tracker. It works well for variety types of target tracking in clutter. The core of this method is to get the entire information contained in the histogram we can gain the binary image and get the centroid from it. To track the target so that we can compare the size of the object in the current frame with the former. If the change is little such as the number of the peaks the paper also suggests subjoining an eyeshot-window we consider the object has been tracked well. Otherwise their height just like our eyes focus on a target if the change is bigger than usual position and other properties in the histogram. Combine with this histogram analysis we will not miss it unless it is out of our eyeshot we should analyze the inflection in the histogram to find out what happened to the object. In general the impression will help us to extract the target in clutter and track it and we will wait its emergence since it has been covered. To obtain the impression what we have to do is turning the analysis into codes for the tracker to determine a feat threshold. The paper will show the steps in detail. The paper also discusses the hardware architecture which can meet the speed requirement. the paper offers a idea comes from the method of Snakes
	federal open agent system platform 会议论文 OAI收割 Conference of the World-Academy-of-Science-Engineering-and-Technology, Prague, CZECH REPUBLIC, AUG 25-27, Wang Hong-Bing; Fan Zhi-Hua; She Chun-Dong \| 收藏 \| 浏览/下载：11/0 \| 提交时间：2011/07/28 Open Agent System High Level Architecture Heterogeneous Agents Wrapper
	Research and implementation of object model in HLA 会议论文 OAI收割 4th International Conference on Virtual Reality and Its Applications in Industry, Tianjin, China, October 23-25, 2003 作者: Zhang X(张霞); Huang SB(黄莎白) 收藏 \| 浏览/下载：27/0 \| 提交时间：2012/06/06 high level architecture object model federation object model simulation object model