[1]于舒春,董静宜. 模糊图像中仪表盘修正力 Snake 模型检测[J].哈尔滨理工大学学报,2018,(02):65-69.[doi:10. 15938/j. jhust. 2018. 02. 012]
 YU Shu-chun,DONG Jing-yi. Detection of Dashboard in Fuzzy Image by Correction Force Snake Model[J].哈尔滨理工大学学报,2018,(02):65-69.[doi:10. 15938/j. jhust. 2018. 02. 012]
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 模糊图像中仪表盘修正力 Snake 模型检测
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《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

卷:
期数:
2018年02期
页码:
65-69
栏目:
材料科学与工程
出版日期:
2018-04-25

文章信息/Info

Title:
 Detection of Dashboard in Fuzzy Image by Correction Force Snake Model
文章编号:
1007-2683( 2018) 02-0065-05
作者:
 于舒春 董静宜
 哈尔滨理工大学 测控技术与仪器黑龙江省高校重点实验室,黑龙江 哈尔滨 150080)
Author(s):
 YU Shu-chun DONG Jing-yi
 ( Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology,Harbin 150080,China)
关键词:
 模糊图像仪表盘Snake 模型准确率
Keywords:
 fuzzy imagedashboardSnake modelaccuracy rate
分类号:
TP391
DOI:
10. 15938/j. jhust. 2018. 02. 012
文献标志码:
A
摘要:
 针对模糊图像中仪表盘检测准确率不高的问题,提出了一种基于修正力的改进 Snake 模型。首先,采用 Hough 变换确定模糊图像中仪表盘所在的区域。其次,以 Hough 变换检测到的 区域边界为 Snake 算法的初始边界,引入修正力参数,扩大 Snake 算法的控制范围,调整能量函数 对目标曲线的连续控制,实现模糊图像中仪表盘的精确定位。实验结果表明,基于修正力的改进 Snake 算法,对于模糊图像中的仪表盘检测准确率,比传统 Snake 算法提升近20%。
Abstract:
 In order to solve the problem that the accuracy of the dashboard detection in fuzzy images is not high,an improved Snake model based on the correction force is proposed. First,the Hough transform is used to determine the area of the dashboard in the fuzzy image. Secondly,the boundary area detected by Hough transform is the initial boundary of Snake algorithm. The correction force parameter is introduced to expand the control range of Snake algorithm,adjust the continuous control of energy function to the target curve,and achieve the precise location of the dashboard in the fuzzy image. The experimental results show that the improved Snake algorithm
based on the correction force is nearly 20% better than the traditional Snake algorithm for the accuracy of the
dashboard detection in the fuzzy image.

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更新日期/Last Update: 2018-06-30