基于CB形态学和灰度码分解的纸病检测
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摘要
传统纸病检测算法抗干扰能力差、定位不准确和运算复杂,针对该问题,提出了一种基于轮廓结构元素形态学和灰度码分解的纸病检测算法。首先,采用多尺度CB形态滤波算法对纸病图像进行滤波,再进行灰度码分解,最后运用多结构元素CB形态学提取重要位面图的边缘。仿真结果表明,该算法运算简单,具有较好的抗干扰能力,并能够较准确地定位纸病缺陷。
Traditional paper defect detection algorithms have the problem of poor anti-interference ability, inaccurate positioning, complex computation. Considering this, a paper defect detection algorithm based on CB morphology and graycode decomposition is presented. Firstly, the noise of the images containing paper defects is filtered by multi-scale CB morphology. Then, the filtered images are decomposed by gray-code decomposition. Finally, the edge of the important bitplane is detected by multi-structural elements CB morphology. The simulation results show that, this method is easily calculated, has a better anti-interference ability, and can accurately locate the paper defects.
Traditional paper defect detection algorithms have the problem of poor anti-interference ability, inaccurate positioning, complex computation. Considering this, a paper defect detection algorithm based on CB morphology and graycode decomposition is presented. Firstly, the noise of the images containing paper defects is filtered by multi-scale CB morphology. Then, the filtered images are decomposed by gray-code decomposition. Finally, the edge of the important bitplane is detected by multi-structural elements CB morphology. The simulation results show that, this method is easily calculated, has a better anti-interference ability, and can accurately locate the paper defects.
引文
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[4]?elik H?,Dülger L C,Topalbekiroglu M.Fabric defect detection using linear filtering and morphological operations[J].Indian Journal of Fibre&Textile Research,2014,39(3):254-259.
[5]陈珺,王亦红.基于机器视觉的低对比度纸病识别算法研究[J].中国造纸学报,2013,28(2):29-33.
[6]殷燕屏,熊智新,胡慕伊.基于阈值分割及分形特征的纸病图像识别算法研究[J].中国造纸学报,2011,26(4):41-45.
[7]Fathi A,Monadjemi A H,Mahmoudi F.Defect detection of tiles with combined undecimated wavelet transform and GLCM features[J].International Journal of Soft Computing&Engineering,2012,2(2).
[8]张学兰,李军,孟范孔.一种基于机器视觉的纸病识别方法[J].中国造纸学报,2013,28(1):48-52.
[9]亢洁,杨刚.自适应权重形态学边缘检测算法仿真研究[J].计算机工程与应用,2010,46(17):163-165.
[10]Chen D,Zhang L Q,Wang Z,et al.A mathematical morphology-based multi-level filter of Li DAR data for generating DTMs[J].Science China,2013,56(10):1-14.
[11]董贤军,汤晓安,张海英,等.CB形态学的边缘检测算法研究[J].计算机工程与应用,2010,46(10):144-146.
[12]蒋薇薇,鲁昌华,郭铭铭.一种改进CB形态学的图像滤波分析研究[J].计算机工程与应用,2012,48(35):143-146.
[13]王向阳,胡峰丽.一种基于重要位平面的鲁棒图像检索算法[J].中国图象图形学报,2007,12(9):1647-1652.
[14]李宝峰,窦勇.位平面编码存储优化算法及FPGA设计[J].计算机辅助设计与图形学学报,2008,20(12):1535-1540.
[15]任洪娥,戴琳琳,张建.基于位平面变换的数字图像加密算法[J].计算机工程,2013,39(6):185-189.
[16]赵珊,翟海霞.基于位平面分布特征的图像检索算法[J].光子学报,2009,38(8):2150-2154.
[17]Priya S,Paul V.Defect detection in woven fabric using weighted morphology[C]//International Conference on Computing Communication&Networking Technologies,2012:1-6.
[18]杨婷婷,顾梅花,章为川,等.彩色图像边缘检测研究综述[J].计算机应用研究,2015(9):2566-2571.