中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共4条，第1-4条

帮助

条数/页：排序方式：
	The Impact of Media Multitasking Behavior on Information Processing Among College Freshmen 期刊论文 OAI收割 Lecture Notes in Electrical Engineering, Volume 1256 LNEE, Pages 3-11, 2024, 2024, 卷号: 1256, 页码: 3-11 作者: Yongmei Zhang; Ting Tao; Wenbin Gao; Ligang Wang; Chunlei Fan \| 收藏 \| 浏览/下载：9/0 \| 提交时间：2024/10/28 media multitasking behaviour information processing depth information processing performance
	Partial occlusion detection of object boundary (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009, May 5, 2009 - May 7, 2009, Singapore, Singapore 作者: Zhang J.; Zhang K.; Zhang K.; Zhang K.; Zhang K. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Partial occlusion is a difficult problem in computer vision since whether the object is changed or occluded is ambiguous especially when distinguishing it only from the object boundary. In this paper we proposed a novel idea to solve this problem by taking shape matching as a morphing processing. A mass-spring model is constructed from the point set which is sampled from a template (or reference) object boundary by moving it to a target object which is deformed and/or occluded. From the morphing processing sufficient information can be obtained and an accurate detection of occlusion is performed. By using of the proposed method the application scope of occlusion detection is expanded while other method cannot be performed which need color texture or motion information. The experiments performed on synthetic and real world images proved the satisfactory performance of the proposed method. 2009 IEEE.
	Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wu Y.-H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Displacement estimation is a fundamental problem in Real-time video image processing. It can be typically approached by theories based on features in spatial domain. This paper presents an algorithm which improves the theory for estimating the moving object's displacement in spatial domain by its Fourier transform frequency spectrum. Because of the characters of Fourier transform the result is based on all the features in the image. Utilizing shift theorem of Fourier transform and auto-registration the algorithm employs the phase spectrum difference in polar coordinate of two frame images sequence with the moving target1 2. The method needn't transform frequency spectrum to spatial domain after calculation comparing with the traditional algorithm which has to search Direc peak and it reduces processing time. Since the technique proposed uses all the image information including all the white noise in the image especially and it's hard to overcome the aliasing from noises but the technique can be an effective way to analyze the result in little white noise by the different characters between high and low frequency bands. It can give the displacement of moving target within 1 pixel of accuracy. Experimental evidence of this performance is presented and the mathematical reasons behind these characteristics are explained in depth. It is proved that the algorithm is fast and simple and can be used in image tracking and video image processing.
	AE signal processing and DSP implementation based on wavelet packet analysis (EI CONFERENCE) 会议论文 OAI收割 ICMIT 2005: Information Systems and Signal Processing, September 20, 2005 - September 23, 2005, Changchun, China 作者: Zhao J.; Wang K. 收藏 \| 浏览/下载：13/0 \| 提交时间：2013/03/25 To improve the accuracy of AE (Acoustic Emission) testing the wavelet packet analysis was introduced to process the AE signals. Extraction of the fault characteristic information would be influenced greatly if the faulted AE signal was not effectively denoised. Based on discussing the fast searching algorithm of BWPB (Best Wavelet Packet Basis) adopting Shannon entropy a new method based on BWPB was presented to denoise the AE signal from the faulted composite plate. Analyzing was performed on the denoised signal and the fault characteristic information was exacted. To improve the real-time performance of the wavelet packet analysis algorithm it was performed on the DSP (Digital Signal Processing) chip TMS320VC5409. The experimental results show that the algorithm can not only reduce the noise by 10dB but also effectively extract the faulted characteristics information from the AE signal.