面向工程仿生的介观尺度动物肢体量化分析方法
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摘要
为了量化分析介观尺度(0.1~1.0 mm)动物肢体的几何结构特征,使用计算机视觉技术代替人的视觉鉴别过程,本研究将具有介观尺度几何特征的典型臭蜣螂(Copris ochus Motschulsky)前足胫节端齿选为研究对象,提出了一种量化分析方法.该方法使用数码体视显微镜获取数字图像,使用软件Matlab作为程序的设计平台,设计程序排除数字图像中的干扰和噪声,并从图像中识别、检测,提取出臭蜣螂前足胫节端齿的外缘轮廓二维点云,以量化分析动物肢体的几何特征,最后验证该方法的准确性和可重复性.对于669×727像素的体视显微镜数字图像,对端齿外缘轮廓进行提取后,可获得约1 500外缘轮廓点,而且在灰度直方图示出的范围内选择不同的阈值没有明显改变曲线拟合的结果,证实了相对于传统方法,数字图像处理和计算机视觉分析方法能够准确有效地反映臭蜣螂的前足胫节端齿的外缘轮廓几何特征.
To quantitatively analyze the structural characteristics of meso-scaled(0. 1 ~ 1. 0 mm) animal organs,the computer vision technology was exploited to substitute the human visual identification process.The foreleg end-tooth of typical soil animal-dung beetle(Copris ochus Motschulsky) with meso-scaled characteristics were taken as research object to propose a quantitative analysis method. The meso-scale animal organ outer margin contour points were extracted from stereomicroscope image by the proposed method. The stereomicroscope image of bionic object animal organ was prepared,and the Matlab software was used as platform to design program for reducing interference and noise. The outer contour of two-dimensional point cloud of dung beetle foreleg end tooth was identified and extracted from the stereomicroscope image to quantitatively analyze geometrical structure. The accuracy and the repeatability of the proposed method were verified. The results show that the outer edge profile of foreleg end tooth can be extracted from stereomicroscopy image with 669 × 727 pixels,and about 1 500 outer edge contour points are obtained. The selection of different thresholds in the gray scale histogram range does not significantly alter the results of curve fitting. It is confirmed that compared to the traditional method,the digital image processing and computer vision analysis method is efficient and accurate to quantitatively analyze geometrical characteristic features of dung beetle foreleg end-tooth.
To quantitatively analyze the structural characteristics of meso-scaled(0. 1 ~ 1. 0 mm) animal organs,the computer vision technology was exploited to substitute the human visual identification process.The foreleg end-tooth of typical soil animal-dung beetle(Copris ochus Motschulsky) with meso-scaled characteristics were taken as research object to propose a quantitative analysis method. The meso-scale animal organ outer margin contour points were extracted from stereomicroscope image by the proposed method. The stereomicroscope image of bionic object animal organ was prepared,and the Matlab software was used as platform to design program for reducing interference and noise. The outer contour of two-dimensional point cloud of dung beetle foreleg end tooth was identified and extracted from the stereomicroscope image to quantitatively analyze geometrical structure. The accuracy and the repeatability of the proposed method were verified. The results show that the outer edge profile of foreleg end tooth can be extracted from stereomicroscopy image with 669 × 727 pixels,and about 1 500 outer edge contour points are obtained. The selection of different thresholds in the gray scale histogram range does not significantly alter the results of curve fitting. It is confirmed that compared to the traditional method,the digital image processing and computer vision analysis method is efficient and accurate to quantitatively analyze geometrical characteristic features of dung beetle foreleg end-tooth.
引文
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[25]REN L Q.Progress in the bionic study on anti-adhesion and resistance reduction of terrain machines[J].Science in China Series E:Technological Sciences,2009,52(2):273-284.
[26]TONG J,ZHANG Z H,CHEN D H,et al.A method for quantitative analysis of geometrical structure of animal organs in meso-scale:the dung beetle foreleg end tooth as a case example[C]∥Proceedings of the 4th International Conference of Bionic Engineering,2014:3-16.
[2]REN L Q,TONG J,LI J Q,et al.SW-soil and water:soil adhesion and biomimetics of soil-engaging components:a review[J].Journal of Agricultural Engineering Research,2001,79(3):239-263.
[3]ZHANG Z H,TONG J,CHEN D H,et al.Bionically inspired serrated structure for improving efficiency of micro-topography preparation[J].IAEJ,2015,24(4):11-23.
[4]TONG J,MOAYAD B Z,REN L Q,et al.Biomimetics in soft terrain machines:a review[J].International Agricultural Engineering,2004,13(1):71-86.
[5]LI S W,TONG J,ZHANG S J,et al.Reverse Engineering and Engineering Bionics[J].Transactions of the Chinese Society for Agricultural Machinery,2004,35(3):109-112
[6]SHAH S A,SANTAGO P,RUBIN B K,et al.Quantification of biopolymer filament structure[J].Ultramicroscopy,2005,104(3/4):244-254.
[7]YUAN C,LIN E,MILLARD J,et al.Closed contour edge detection of blood vessel lumen and outer wall boundaries in black-blood MR images[J].Magnetic Resonance Imaging,1999,17(2):257-266.
[8]ANORAGANINGRUM D.Cell segmentation with median filter and mathematical morphology operation[C]∥Proceedings of the Image Analysis and Processing,1999:1043-1046.
[9]黄星奕,李剑,姜松.基于计算机视觉的稻谷品种识别技术的研究[J].江苏大学学报(自然科学版),2004,25(2):102-104.HUANG X Y,LI J,JIANG S.Study on identification of rice varieties using computer vision[J].Journal of Jiangsu University(Natural Science Edition),2004,25(2):102-104.(in Chinese)
[10]万鹏,孙瑜,孙永海.基于计算机视觉的大米粒形识别方法[J].吉林大学学报(工学版),2008,38(2):489-492.WAN P,SUN Y,SUN Y H.Recognition method of rice kernel shape based on computer vision[J].Journal ofJilin University(Engineering and Technology Edition),2008,38(2):489-492.(in Chinese)
[11]杨焱,刘飒,廉世彬,等.基于计算机视觉的果树害虫的形态特征分析[J].吉林大学学报(工学版),2013,43(S1):235-238.YANG Y,LIU S,LIAN S B,et al.Analysis of fruit tree pests morphological characteristics based on computer vision[J].Journal of Jilin University(Engineering and Technology Edition),2013,43(S1):235-238.(in Chinese)
[12]屠康,潘磊庆,杨佳丽,等.基于计算机视觉的鸡蛋污斑检测[J].江苏大学学报(自然科学版),2007,28(3):189-192.TU K,PAN L Q,YANG J L,et al.Dirt detection on brown eggs based on computer vision[J].Journal of Jiangsu University(Natural Science Edition),2007,28(3):189-192.(in Chinese)
[13]黄星奕,林建荣,赵杰文.苹果果梗和缺陷的识别技术研究[J].江苏大学学报(自然科学版),2004,25(3):193-195.HUANG X Y,LIN J R,ZHAO J W.Identification technique for stem-end and blemish in apples[J].Journal of Jiangsu University(Natural Science Edition),2004,25(3):193-195.(in Chinese)
[14]宋志刚,王龙山,陈向伟.利用数字图像处理技术检测锥螺纹[J].吉林大学学报(工学版),2004,34(2):248-251.SONG Z G,WANG L S,CHEN X W.Detection of conical thread with digital image processing technology[J].Journal of Jilin University(Engineering and Technology Edition),2004,34(2):248-251.(in Chinese)
[15]张立斌,苏建,田云锋.利用计算机视觉检测汽车车轮定位参数[J].吉林大学学报(工学版),2003,33(2):32-34.ZHANG L B,SU J,TIAN Y F.Study on testing automobile alignment based on computer vision[J].Journal of Jilin University(Engineering and Technology Edition),2003,33(2):32-34.(in Chinese)
[16]何世权,肖宏,樊丁,等.高频焊管错边缺陷的图像处理及特征提取[J].江苏大学学报(自然科学版),2012,33(4):449-452.HE S Q,XIAO H,FAN D,et al.Image processing and feature extracting of welding seam misalignment for highfrequency welded pipe[J].Journal of Jiangsu University(Natural Science Edition),2012,33(4):449-452.(in Chinese)
[17]王国林,殷旻,梁晨.图像处理技术在轮胎接地几何特征测量中的应用[J].江苏大学学报(自然科学版),2017,38(2):139-143.WANG G L,YIN M,LIANG C.Measurement system of tire footprint geometric parameters based on image processing[J].Journal of Jiangsu University(Natural Science Edition),2017,38(2):139-143.(in Chinese)
[18]GONZALEZ R C,WOODS R E,EDDINS S L.Digital image processing using MATLAB[M].2nd.New Jersey:Pearson Prentice Hall,2009.
[19]董文晓.基于CCD相机测量的LED显示屏亮度和色度均匀性算法研究[D].西安:西安电子科技大学,2012.
[20]高雷.交会对接逼近阶段飞行器空中位置和姿态的视觉测量[D].长沙:国防科学技术大学,2010.
[21]钱基业.图像处理算法及其在板形识别中的应用[D].重庆:重庆大学,2007.
[22]谢小亮.基于图像处理技术的自动报靶系统[D].重庆:重庆大学,2012.
[23]LARKINS D,BRIAN H W.Introductory computational science using MATLAB and image processing[J].Procedia Computer Science,2010,1(1):913-919.
[24]CUI F Y,ZOU L J,SONG B.Edge feature extraction based on digital image processing techniques[C]∥Proceedings of the 2008 IEEE International Conference on Automation and Logistics,2008:2320-2324.
[25]REN L Q.Progress in the bionic study on anti-adhesion and resistance reduction of terrain machines[J].Science in China Series E:Technological Sciences,2009,52(2):273-284.
[26]TONG J,ZHANG Z H,CHEN D H,et al.A method for quantitative analysis of geometrical structure of animal organs in meso-scale:the dung beetle foreleg end tooth as a case example[C]∥Proceedings of the 4th International Conference of Bionic Engineering,2014:3-16.