基于形态学图像检测的机械手移栽穴苗识别技术

针对机械移栽穴苗过程中如何有效识别出根系受损的幼苗, 进而及时进行分类、补救这一实际问题, 提出一种基于机器视觉的移栽穴苗识别方法。该方法根据机械手移栽穴苗特点, 对比检测图像土壤基质面积与基准面积; 进而通过测定土壤基质完整率, 判断样本合格与否。文中从理论和实际的角度说明了形态学图像处理方法处理穴苗移栽图像特点, 设计了机械手移栽穴苗识别在线测试系统。最后, 对基于形态学图像检测方法的机械手移栽穴苗识别技术和普通图像检测方法进行对比实验。结果表明, 本文提出的形态学检测方法对一个72孔穴盘合格检出率提高了6.6%, 不合格检出率提高了54.5%。同时, 一个穴苗的平均处理时间约为1.82 s。结果表明提出的方法可靠, 耗时较短, 能够匹配机械手移栽流水线作业时间上的要求, 并满足实时处理要求。

Abstract

How to discover and remedy the damaged seedlings quickly in batch processing seedlings by automatic transplanting technology was researched. A recognition method of seedlings in mechanical transplanting processing based on machine vision was proposed. Based on the characteristics of mechanical transplanting seedlings, the method was used to measure soil matrix intact rate of seedlings by comparison of the image areas between soil matrix and benchmark. By which the samples were qualified or not could be judged. Then, the image characteristics processed by morphological image processing method in mechanical transplanting seedlings were described from the theory and practice and an online testing system for recognition of mechanical transplanting seedlings was designed. Finally, the manipulator transplanting seedling method based on morphological image detection and the common image detection method were compared. Experimental results indicate that the morphological detection method proposed in this paper for a seedling tray containing 72 holes increases the detection rate by 6.6%, and unqualified detection rate by 54.5%. At the same time, the average time that processes one seeding is about 1.82 s. It is shown that the proposed method is reliable, short time-consuming, satisfied with the requirement of real-time processing.

参考文献

[1] FENG Q C, ZHAO C J, JIANG K, et al..Design and test of tray-seedling sorting transplanter[J]. Int J Agric & Biol En., 2015, 8(2): 14-20.

[2] 刘效亮, 李其昀. 育苗移栽机械化发展方向[J]. 山东理工大学学报：自然科学版, 2003, 17(3): 108-110.

LIU X L, LI Q Y. Development tendency of bowl-rear transplanting mechanization[J]. Journal of Shandong University of Technology(Sci & Tech), 2003, 17(3): 108-110. (in Chinese)

[3] 潘启明. 国内外移栽机技术现状和发展趋势[J]. 安徽农业科学, 2013, 41(31): 12478-12479, 12496.

PAN Q M. Current situation and development trend of domestic and foreign transplanting machine technology [J]. Journal of Anhui Agricultural Science, 2013, 41(31): 12478-12479, 12496. (in Chinese)

[4] CHOI W C, KIM D C, RYU I H, et al.. Development of a seedling pick-up device for vegetable transplanters [J]. Transactions of the Asae, 2002, 45(1): 13-19.

[5] 刘炜, 刘继展. 穴盘苗移栽机器人末端执行器综述[J]. 农机化研究, 2013, (7): 6-10.

LIU W, LIU J ZH. Review of end-effectors in tray seedlings transplanting robot[J]. Journal of Agricultural Mechanization Research, 2013, (7): 6-10. (in Chinese)

[6] 刘大纹, 肖英奎, 于海业. 运动仿真系统中嵌入式计算机技术应用[J]. 农业机械学报, 2007, 38(6): 161-163, 177.

LIU D W, XIAO Y K, YU H Y. Application of the embedded computer technique in motion simulation system[J]. Transactions of the Chinese Society of Agricultural Machinery, 2007, 38(6): 161-163, 177. (in Chinese)

[7] 王跃勇, 于海业. 穴盘幼苗机械手取苗基质完整率影响因素试验与分析[J]. 农业工程学报, 2015, 31(14): 65-71.

WANG Y Y, YU H Y. Experiment and analysis of impact factors for soil matrix intact rate of manipulator for picking-up plug seedlings[J]. Transactions of Chinese Society of Agricultural Engineering, 2015, 31(14): 65-71. (in Chinese)

[8] 董微, 周增产, 卜云龙, 等. 穴盘苗自动移栽机研发与应用[J]. 农业工程, 2014, 4(7): 120-124.

DONG W, ZHOU Z H, BU Y L, et al.. Research and Application of Potted Tray Seedlings Automatic Transplanting Machine[J]. Agricultural Engineering, 2014, 4(7): 120-124. (in Chinese)

[9] 胡飞, 尹文庆, 陈彩蓉, 等. 基于机器视觉的穴盘幼苗识别与定位研究[J]. 西北农林科技大学学报：自然科学版, 2013, 41(5): 183-188.

HU F, YIN W Q, CHEN C R, et al..Recognition and localization of plug seedling based on machine vision[J]. Journal of Northwest A & F University (Nat. Sci. Ed. ), 2013, 41(5): 183-188. (in Chinese)

[10] 童俊华. 蔬菜钵苗穴盘间移栽执行器设计、移栽信息监测与路径规划[D]. 杭州: 浙江大学, 2014, 9.

TONG J H. End-effector Design, Seedling Information Inspection and Path Planning for Transplanting between Vegetable Seedling Trays. ZheJiang University[D]. HangZhou: Zhejiang University, 2014, 9. (in Chinese).

[11] STROPPA R G, LEONARDI F FRIGATO R, et al.. Cartographic update through image digital processing by Mathematical Morphology techniques [C]. International Center for Remote Sensing of Environment, 2009: 1113-1115.

[12] MOSTAFA K, CHIANG J Y, HER I. Edge-detection method using binary morphology on hexagonal images[J]. The Imaging Science Journal, 2015, 63(3): 168-173.

[13] 张雄美, 易昭湘, 田淞, 等. 结合形态学属性断面与支持向量机的合成孔径雷达图像变化检测[J]. 光学精密工程, 2014, 22(10): 2832-2839.

ZHANG X M, YI ZH X, TIAN S, et al.. Change detection of SAR images using morphologic attribute profile and support vector machine[J]. Opt. Precision Eng., 2014, 22(10): 2832-2839. (in Chinese)

[14] 王卫星, 田利平, 王悦. 基于改进的图论最小生成树及骨架距离直方图分割细胞图像[J]. 光学精密工程, 2013, 21(9): 2464-2472.

WANG W X, TIAN L P, WANG Y. Segmentation of cell images based on improved graph MST and skeleton distance mapping[J]. Opt. Precision Eng., 2013, 21(9): 2464-2472. (in Chinese)

[15] 邹北骥, 张思剑, 朱承璋. 彩色眼底图像视盘自动定位与分割[J]. 光学精密工程, 2013, 21(4): 1187-1195.

ZOU B J, ZHANG S J, ZHU CH ZH. Automatic localization and segmentation of optic disk in color fundus image[J]. Opt. Precision Eng., 2013, 21(4): 1187-1195. (in Chinese)

[16] 王灿进, 孙涛, 石宁宁, 等. 基于双隐含层BP算法的激光主动成像识别系统[J]. 光学精密工程, 2014, 22(6): 1639-1647.

WANG C J, SUN T, SHI N N. et al.. Laser active imaging and recognition system based on double hidden layer BP algorithm[J]. Opt. Precision Eng., 2014, 22(6): 1639-1647. (in Chinese)

[17] 裘祖荣, 陈浩玉, 胡文川, 等. 嵌入式线结构光角度视觉检测及误差补偿[J]. 光学精密工程, 2013, 21(10): 2480-2487.

QIU Z R, CHEN H Y, HU W CH. et al.. Embedded ankle vision inspection and error compensation for line structured lights[J]. Opt. Precision Eng., 2013, 21(10): 2480-2487. (in Chinese)

[18] 韩延祥, 张志胜, 郝飞, 等. 灰度序列图像中基于纹理特征的移动阴影检测[J]. 光学精密工程, 2013, 21(11): 2931-2942.

HAN Y X, ZHANG ZH SH, HAO F. et al.. Shadow detection based on texture features in gray sequence images[J]. Opt. Precision Eng., 2013, 21(11): 2931-2942. (in Chinese)

[19] 余金栋, 张宪民. 用于线纹显微图像的边缘检测算法[J]. 光学精密工程, 2015, 23(1): 271-281.

YU J D, ZHANG X M. Edge detection algorithm for lines on microscopic image[J]. Opt. Precision Eng., 2015, 23(1): 271-281. (in Chinese)

[20] 刘明峰, 胡先朋, 廖宜涛, 等. 不同油菜品种适栽期机械化移栽植株形态特征研究[J]. 农业工程学报, 2015, 31(增1): 79-88.

LIU M F, HU X P, LIAO Y T, et al..Morphological parameters characteristics of mechanically transplanted plant in suitable transplanting period for different rape varieties[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(Supp1): 79-88 . (in Chinese)

[21] AN D k, LI M Z, ZHANG L. Measurement of tomato leaf area using computer image processing technology [J]. SENSOR LETTERS, 2010, 8(10): 56-60.

[22] QI L, MA X, LIAO X L, et al..An easy measurement method of foliar morphological parameters using image processing technique [C]. American Society of Agricultural and Biological Engineers, 2011(5): 4075-4082.

[23] XUE T, LIU X W, JIN Y X, et al..Bubbles image processing and parameters measurement based on the high-speed photography[C]. International Symposium on Precision Engineering Measurements and Instrumentation, Li jiang, China, (ISPEMI), 2011: 8321.

[24] ZENG D M, CUI W, LIANG L J. An image processing based system for leaf parameter measuring[C]. International Symposium on Photonics and Optoelectronics, 2012: 1-4.

[25] RAFAEL C. GONZALEZ, RICHARD E. et al.. Digital Image Processing Using MATLAB[M]. Beijing: Electronics Industry Press, 2009.

王跃勇, 于海业, 刘媛媛. 基于形态学图像检测的机械手移栽穴苗识别技术[J]. 光学精密工程, 2016, 24(3): 651. WANG Yue-yong, YU Hai-ye, LIU Yuan-yuan. Recognition of seedlings in mechanical transplanting processing by Morphological image detection[J]. Optics and Precision Engineering, 2016, 24(3): 651.

基于形态学图像检测的机械手移栽穴苗识别技术

关于本站 Cookie 的使用提示

全站搜索

基于形态学图像检测的机械手移栽穴苗识别技术

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索