一个基于像素编组和逐级质量控制的线段检测算子

针对现有线段提取算法存在的不足,提出了一个点元梯度特征引导下的线段检测算子,在编组的前、中和后三大环节进行逐级质量控制.基于梯度最优并结合邻近性、方向性等规则控制“欠提取”错误,采用假设检验方法控制“过提取”错误.多源数据实验表明,提出的算法在编组中不易受到弱梯度像素或噪声的干扰,与经典的线段提取算子相比,在线段提取的效率和稳健性都有一定的优势,有利于实现从场景到结构的重要视觉符号描述....

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Bibliographic Details
Published in红外与毫米波学报 Vol. 35; no. 6; pp. 681 - 687
Main Author 李畅 魏东
Format Journal Article
LanguageChinese
Published 华中师范大学城市与环境科学学院,湖北武汉430079 2016
华中师范大学地理过程分析与模拟湖北省重点实验室,湖北武汉430079
Subjects
假设检验
像素编组
欠提取
线段检测
质量控制
过提取
false negative
假设检验
quality control
hypothesis testing
过提取
欠提取
pixels grouping
质量控制
false positive
线段检测
像素编组
line segment detector
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Summary:针对现有线段提取算法存在的不足,提出了一个点元梯度特征引导下的线段检测算子,在编组的前、中和后三大环节进行逐级质量控制.基于梯度最优并结合邻近性、方向性等规则控制“欠提取”错误,采用假设检验方法控制“过提取”错误.多源数据实验表明,提出的算法在编组中不易受到弱梯度像素或噪声的干扰,与经典的线段提取算子相比,在线段提取的效率和稳健性都有一定的优势,有利于实现从场景到结构的重要视觉符号描述.
Bibliography:To resolve the ＂false negative＂ and ＂false positive＂ problems in the current line segment de- tectors, we proposed a novel line segment detector which organizes pixels under the guidance of pix-els＇ gradient and improves reliability by step-by-step quality control. Before organizing pixels, initial optimized seed points were extracted according to image gradient. Under organizing, in order to solve the bad performance, e.g. noise of weak gradient, pixels were grouped and connected by considering proximity, orientation and gradient optimization to control false negative. After organizing pixels, chain division and hypothesis testing for quality control were employed to avoid false positive. When compared with state-of-the-art algorithms by visible light and color infrared （CIR） images, such as Probability Hough Transform （ PHT）, EDlines and LSD （ Line Segment Detector）, the proposed algo- rithm has advantages in efficiency and robustness, so it is of great significance for digital photogramme- try, computer vi
ISSN:1001-9014
DOI:10.11972/j.issn.1001-9014.2016.06.009