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文章摘要
基于提升小波变换的指针式仪表图像边缘检测
Edge Detection of Analog Instrument ImageBased on Lifting Wavelet Transform
Received:November 30, 2013  Revised:November 30, 2013
DOI:
中文关键词: 指针式仪表  自动检测系统  提升小波变换  边缘检测  低通作用  小波系数方向性
英文关键词: pointer instrument  automatic detection system  lifting wavelet transform  edge detection  low-pass effect  the directional of wavelet coefficients
基金项目:
Author NameAffiliationE-mail
JIANG Jie CollegeSofSInformationSEngineering,SInnerSMongoliaSUniversitySofSScienceSandSTechnology jie5881@126.com 
YU Li-na* CollegeSofSInformationSEngineering,SInnerSMongoliaSUniversitySofSScienceSandSTechnology 731744324@qq.com 
GAO Chao CollegeSofSInformationSEngineering,SInnerSMongoliaSUniversitySofSScienceSandSTechnology  
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中文摘要:
      为解决工业中基于计算机视觉的指针式仪表自动检测系统中所涉及的图像边缘检测技术难点,分析了现有传统算法的不足之处,提出一种有效的基于提升小波变换的边缘检测算法。该算法利用提升小波变换尺度的低通作用,避免受高频噪声影响,在传统边缘检测算法的基础上,提取低频轮廓。利用小波系数的方向性,结合方向性边缘检测算子,获得高频边缘信息,从而得到准确清晰的图像边缘,为后续Hough变换准确的提取指针提供了有利保障。实验表明,该算法得到的图像边缘较传统Canny算法更清晰准确,无虚假边缘,应用于仪表自动检测系统中是可行的。
英文摘要:
      In order to solve the technical difficulties of the image edge detection involved in the pointer instrument automatic detection system based on computer vision industry, analysis of the shortcomings of existing traditional algorithms, propose an effective edge detection algorithm based on lifting wavelet transform. At first the algorithm avoided being affected by high-frequency noise using low-pass effect of lifting wavelet transform scale, and extracted low-frequency contour based on the algorithm of traditional edge detection. Using the directional of wavelet coefficients, combined with directional edge detection operator, accessed high-frequency edge information, so get clear and precise edge of image, and provided a favorable security for the extraction of accurate pointer using the Hough transform. Experiments show that the algorithm image edge was detected by the algorithm is more clear and accurate than the traditional Canny algorithm, and there is no false edge, and applying the algorithm to automatic detection system is feasible.
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