计算机科学 ›› 2018, Vol. 45 ›› Issue (4): 106-111.doi: 10.11896/j.issn.1002-137X.2018.04.016

• 2017年全国理论计算机科学学术年会 • 上一篇    下一篇

基于多生长时期模板匹配的玉米螟识别方法

刘博艺,唐湘滟,程杰仁   

  1. 海南大学信息科学技术学院 海口570228;中国科学院大学 北京100000,海南大学信息科学技术学院 海口570228,海南大学信息科学技术学院 海口570228;海南大学南海海洋资源利用国家重点实验室 海口570228
  • 出版日期:2018-04-15 发布日期:2018-05-11
  • 基金资助:
    本文受国家自然科学基金(61363071,61762033),海南省自然科学基金(617048),海南大学博士启动基金(kyqd1328),海南大学青年基金(qnjj14444),海南大学研究生实践创新项目基金资助

Recognition Method for Corn Borer Based on Templates Matching in Muliple Growth Periods

LIU Bo-yi, TANG Xiang-yan and CHENG Jie-ren   

  • Online:2018-04-15 Published:2018-05-11

摘要: 玉米螟是玉米种植中的主要虫害之一。为了解决人工识别的劳动强度大,且识别不够准确、及时的问题,文中提出了一种在自然场景下基于多生长时期模板匹配的不同生长时期亚洲玉米螟的识别方法。该方法首先对获取到的图像进行数学形态学预处理;其次利用直方图反向映射法和多模板图像得到总的概率图像;然后利用约束空间的大津法对二值图像进行轮廓提取,并根据周长和面积特征进行初步筛选;最后结合基准轮廓,利用Hu矩等特征选出符合亚洲玉米螟特征的轮廓,进而得出识别结果并以三角形标记。实验和理论分析证明,在复杂自然场景图像中,该方法不仅时效性强,而且具有很好的识别准确度,能够有效降低不同生长时期的玉米螟颜色变化带来的影响。

关键词: 虫害识别,玉米螟,直方图反向映射,模板匹配,Hu矩

Abstract: Corn borer is one of main pests encountered in the corn.In order to solve the problems of high labor intensity,inaccuracy,and being not in time in artificial recognition,a novel identification method for Asiatic corn borer was proposed under natural scenes in this paper,which is based on reverse mapping of histogram and multi-template matching of contours.Firstly,this method performs mathematical morphology preprocessing for the obtained image.Secondly,the total probability image is obtained by using reverse mapping of histogram method and multi-template images,and then image contour can be extracted quickly and accurately by using constraint Otsu,and can be preliminary filtrated according to the perimeter and area characteristics of corn borer.Finally,the contours matched with the characteristics of Asiatic corn borer are selected by using Hu moment characters between multiple reference contours and the obtained target contours,and then identification results with triangle mark are obtained.The experimental results and theoretical analysis show that the proposed method has high timeliness and high recognition accuracy in complex natural scenes.

Key words: Insect pests recognition,Corn borer,Reverse mapping of histogram,Template matching,Hu moment

[1] WEI T S,ZHU W F,PANG M H,et al.Influence of the damage of cotton bollworm and corn borer to ear rot in corn [J].Journal of Maize Sciences,2013,21(4):116-118.(in Chinese) 魏铁松,朱维芳,庞民好,等.棉铃虫和玉米螟危害对玉米穗腐病的影响[J].玉米科学,2013,21(4):116-118.
[2] LIU F,SHEN Z R,ZHANG J W,et al.Automatic insect identification based on color characters [J].Chinese Bulletin of Entomology,2008,45(1):150-153.(in Chinese) 刘芳,沈佐锐,张建伟,等.基于颜色特征的昆虫自动鉴定方法[J].昆虫知识,2008,45(1):150-153.
[3] ZHU L Q,ZHANG Z,ZHANG P Y.Image identification of insects based on color histogram and dual tree complex wavelet transform (DTCWT) [J].Acta Entomologica Sinica,2010,53(1):91-97.
[4] ZHU L Q,ZHANG Z.Automatic insect classification based on local mean colour feature and Supported Vector Machines [J].Oriental Insects,2012,46(3-4):260-269.
[5] ZHU L Q,ZHANG D X,ZHANG Z.Feature description of lepidopteran insect wing images based on WLD and HoC and its application in species recognition [J].Acta Entomologica Sinica,2015,58(4):419-426.(in Chinese) 竺乐庆,张大兴,张真.基于韦伯局部描述子和颜色直方图的鳞翅目昆虫翅图像特征描述与种类识别[J].昆虫学报,2015,58(4):419-426.
[6] ZHU L,ZHANG Z.Using CART and LLC for image recognition of Lepidoptera [J].Pan-Pacific Entomologist,2013,89(3):176-186.
[7] ZHU L Q,ZHANG D X,ZHANG Z.Recognition of lepidopteran species based on color name and Opponent SIFT features [J].Acta Entomologica Sinica,2015,58(12):1331-1337.(in Chinese) 竺乐庆,张大兴,张真.基于颜色名和OpponentSIFT特征的鳞翅目昆虫图像识别[J].昆虫学报,2015,58(12):1331-1337.
[8] TIAN J,HU Q X,MA X Y.Color image segmentation of plant lesion using improved C-V model based on Gaussian distribution [J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(16):166-173.(in Chinese) 田杰,胡秋霞,马孝义.基于高斯分布改进 CV 模型的植物病斑彩色图像分割[J].农业工程学报,2013,29(16):166-173.
[9] ZONG J X,YANG Y W,ZHAO W,et al.Research on insects recognition based on image analysis [J].Science Technology and Engineering,2014,14 (19):194-200.(in Chinese) 宗精学,杨余旺,赵炜,等.基于图像分析的病虫识别研究[J].科学技术与工程,2014,14 (19):194-200.
[10] ZHAO Y C,HU Z H,BAI Y,et al.An accurate segmentation approach for disease and pest based on DRLSE guided by texture difference[J].Transactions of the Chinese Society for Agriculture Machinery,2015,46(2):14-19.(in Chinese) 赵瑶池,胡祝华,白勇,等.基于纹理差异度引导的DRLSE病虫害图像精准分割方法[J].农业机械学报,2015,46(2):14-19.
[11] ZHAO Y C,HU Z H.Segmentation of fruit with diseases innatural scenes based on logarithmic similarity constraint Otsu [J].Transactions of the Chinese Society for Agriculture Machinery,2015,46(11):9-15.(in Chinese) 赵瑶池,胡祝华.基于对数相似度约束Otsu的自然场景病害果实图像分割[J].农业机械学报,2015,46(11):9-15.
[12] LI Z,HONG T S,ZENG X Y,et al.Citrus red mite image target identification based on K-means clustering[J].Transactions of the Chinese Society of Agricultural Engineering,2013,28(23):147-153.(in Chinese) 李震,洪添胜,曾祥业,等.基于K-means聚类的柑橘红蜘蛛图像目标识别[J].农业工程学报,2013,28(23):147-153.
[13] PANG X M,MIN Z J,KAN J M.Color image segmentation based on HSI and LAB color space [J].Journal of Guangxi University(Natural Science Edition),2011,36(6):976-980.(in Chinese) 庞晓敏,闵子建,阚江明.基于HSI和LAB颜色空间的彩色图像分割[J].广西大学学报(自然科学版),2011,36(6):976-980.
[14] HAN Z Z,ZHAO Y G,YANG J Z.Detection of embryo based on independent components for kernel RGB images in maize[J].Transactions of the CSAE,2010,26(3):222-226.(in Chinese) 韩仲志,赵友刚,杨锦忠.基于籽粒RGB图像独立分量的玉米胚部特征检测[J].农业工程学报,2010,26(3):222-226.
[15] SWAIN M J,BALLARD D H.Color indexing [J].International Journal of Computer Vision,1991,7(1):11-32.
[16] OTSU N.A threshold selection method from gray-level histogram [J].IEEE Transactions on Systems,Man and Cyberne-tics,1979,9(1):62-66.
[17] XU X Y,SONG E M,JIN L H.Characteristic analysis ofthreshold based on Otsu criterion [J].Acta Electronica Sinica,2009,37(12):2716-2719.(in Chinese) 许向阳,宋恩民,金良海.Otsu准则的阈值性质分析[J].电子学报,2009,7(12):2716-2719.
[18] HU M K.Visual pattern recognition by moment invariants[J].Ire Transaction on Information Theory,1962,8(2):179-187.
[19] LIU J,GENG G H,REN Z B.Plant pest recognition system based on multi-structure element morphology[J].Computer Engineering and Design,2009,30(6):1488-1490.(in Chinese) 刘军,耿国华,任治斌.基于多结构元素的农作物病虫识别系统[J].计算机工程与设计,2009,30(6):1488-1490.

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