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Digital image processing-based automatic detection algorithm of cross joint trace and its application in mining roadway excavation practice 被引量:1

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摘要 This paper proposes a digital image processing-based detection algorithm for cross joint traces of coal roadway heading face.Initially,the acquired images were preprocessed,i.e.,adaptive correction was conducted for non-uniform illumination images based on the 2D gamma function.The edge detection algorithm was then applied to extract the edges of the structural plane,followed by the filtration of the non-structural plane noises.Moreover,the Hough transform algorithm was applied to extract the linear edges;finally,the edges were locally connected in accordance with the angle and distance criteria.The experimental results show that this algorithm can be used to reduce the noise caused by non-uniform illumination and avoid the mutual interference of multi-scale edges,so as to effectively extract the traces of the cross joint.Furthermore,Q-system and rock mass rating(RMR),were applied to conduct a quantitative evaluation on the stand-up time of unsupported roof in the four test images.The Q-system quality scores are 26.7,43.3,3.1,and 6.7,and the RMR quality scores are 56.84,58.73,48.42,and 51.42,respectively.The stand-up time of unsupported roofs with a span of 4.6 m are 30,36,7.7 and 14 d,respectively.
出处 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2022年第6期1219-1231,共13页 矿业科学技术学报(英文版)
基金 supported by the National Natural Scieince Foundation of China(Nos.52004204 and 52034007).
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  • 1俞磊,吴立德.边缘检测中断边、伪边与结构点的处理[J].模式识别与人工智能,1995,8(2):165-170. 被引量:11
  • 2Jang Jeong-Hun,Hong Ki-Sang.Fast Line Segment Grouping Method for Finding Globally More Favorable Line Segments[J].Pattern Recognition,2002,35(10):2235-2247.
  • 3Van de Weterin H,Van Overveld K.Chain Codes and Their Application in Curve Design[J].Graphical Models and Image Processing,1996,58(5):464-470.
  • 4Bandera A,Urdiales C,Arrebola F,et al.2D Object Recognition Based on Curvature Functions Obtained from Local Histograms of the Contour Chain Code[J].Pattern Recognition Letters,1999,32(20):49-55.
  • 5Liu Yuncai,Huang T S.Determining Straight Line Correspondences from Intensity Images[J].Pattern Recognition,1991,24(6).
  • 6Boldt M,Weiss R,Riseman E.Token-based Extraction of Straight Lines[J].IEEE Transaction on System,Man,and Cybernetics,1989,19(6):1581-1594.
  • 7Kaneko T.Line Structure Extraction from Line-drawing Images[J].Pattern Recognition,1992,25(9):963-973.
  • 8李牧,闫继红,李戈,赵杰.自适应Canny算子边缘检测技术[J].哈尔滨工程大学学报,2007,28(9):1002-1007. 被引量:88
  • 9李翊华,胡匡祜,苏万芳.一种提取微血管边缘曲线角点策略[J].中国生物医学工程学报,1998,17(4):293-294. 被引量:4
  • 10李福文,金伟其,陈伟力,曹扬,王霞,王岭雪.基于Retinex模型的彩色图像全局增强算法[J].北京理工大学学报,2010,30(8):947-951. 被引量:29

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