×
验证码:
换一张
忘记密码?
记住我
CORC
首页
科研机构
检索
知识图谱
申请加入
托管服务
登录
注册
在结果中检索
科研机构
长春光学精密机械与物... [1]
内容类型
会议论文 [1]
发表日期
2009 [1]
×
知识图谱
CORC
开始提交
已提交作品
待认领作品
已认领作品
未提交全文
收藏管理
QQ客服
官方微博
反馈留言
浏览/检索结果:
共1条,第1-1条
帮助
已选(
0
)
清除
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
作者升序
作者降序
题名升序
题名降序
发表日期升序
发表日期降序
提交时间升序
提交时间降序
Real-time motive vehicle detection with adaptive background updating model and HSV colour space (EI CONFERENCE)
会议论文
4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, November 19, 2008 - November 21, 2008, Chengdu, China
Rong-Hui Z.
;
Bai Y.
;
Hong-guang J.
;
Chen T.
收藏
  |  
浏览/下载:57/0
  |  
提交时间:2013/03/25
In the transportation monitor system
we set up the area of interest (AOI) of the vehicle model and adjust the size of AOI dynamically in order to track vehicle accurately. The results of experiment show that
motive vehicle detection by adopting digital image is one of key technologies. To detect motive vehicle accurately
the arithmetic proposed in the paper can suppress shadow availably
we establish an adaptive background updating model firstly. Noise is suppressed by using modality filter
detect motive vehicle accurately and satisfy real-time motive vehicle tracking. 2009 SPIE.
and we obtain binary image by using maximum entropy to choose dynamic adaptive threshold. Based on positive information of shadow and aspect feature of motive vehicle
we adopt HSV colour space and double threshold to solve the problem of vehicle shadow. According to prediction result of Kalman filtering
©版权所有 ©2017 CSpace - Powered by
CSpace