机构

• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [1]

内容类型

• 会议论文 [1]

发表日期

• 2006 [1]

学科主题

筛选

浏览/检索结果: 共1条，第1-1条 帮助 限定条件 内容类型：会议论文     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 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：25/0  |  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