应用灰板校正提高计算机视觉预测棉花植株含水量的精确度
|
摘要
利用灰板校正以消除棉花不同生育期图片颜色特征值的亮度差异,建立适用于不同生育期预测植株含水量的通用模型,以提高运用计算机视觉技术进行棉花植株含水量预测的精度。研究结果表明,由灰板校正前、后颜色特征值G-B建立的最佳预测模型,决定系数分别为0.746和0.782。有效性检验结果表明,灰板校正前、后计算预测值与实测值的决定系数分别为0.739和0.783;RMSE分别为2.218和2.03,RE分别为2.13%和1.79%。基于计算机视觉提取的冠层图片颜色特征值能够预测植株含水量,应用灰板校正颜色特征值能够提高模型预测精度,可为提高计算机视觉预测植株水分状况的精度提供技术支撑和方法补充。
This paper aimed at establishing a rapid, non-destructive and low-cost model to predict cotton water content for whole growth stages based on computer-vision technology. The data of color characteristic parameters extracted from cotton canopy digital image of different growth periods were adjusted by gray board in order to eliminate differences in brightness and to improve the prediction precision of the model. The best prediction model is established based on color characteristic parameters G-B by original data or gray board corrected data, the coefficient of determination for the two models was 0.746 and 0.782, respectively. Validation test indicated that the prediction accuracy of models based on gray broad calibrated data was improved comparing to model established by original data. The coefficient of determination between measured plant water content and predicted value was 0.739 and 0.783, respectively; the root mean square error(RMSE) was 2.218 and 2.030; the relative error(RE) between predicted values and measured values were 2.13% and 1.79%. Our results showed that the application of computer vision may predict cotton water content and the color value adjusted by gray board may improve the model prediction accuracy.This research provided a simple, higher precision technical support and new method for diagnosis of plant water status based on computer vision.
This paper aimed at establishing a rapid, non-destructive and low-cost model to predict cotton water content for whole growth stages based on computer-vision technology. The data of color characteristic parameters extracted from cotton canopy digital image of different growth periods were adjusted by gray board in order to eliminate differences in brightness and to improve the prediction precision of the model. The best prediction model is established based on color characteristic parameters G-B by original data or gray board corrected data, the coefficient of determination for the two models was 0.746 and 0.782, respectively. Validation test indicated that the prediction accuracy of models based on gray broad calibrated data was improved comparing to model established by original data. The coefficient of determination between measured plant water content and predicted value was 0.739 and 0.783, respectively; the root mean square error(RMSE) was 2.218 and 2.030; the relative error(RE) between predicted values and measured values were 2.13% and 1.79%. Our results showed that the application of computer vision may predict cotton water content and the color value adjusted by gray board may improve the model prediction accuracy.This research provided a simple, higher precision technical support and new method for diagnosis of plant water status based on computer vision.
引文
[1]王方永,王克如,王崇桃,等.基于图像识别的棉花水分状况诊断研究[J].石河子大学学报:自然科学版,2007,25(4):404-407.Wang Fangyong,Wang Keru,Wang Chongtao,et al.Diagnosis of cotton water status based on image recognition[J].Journal of Shihezi University:Natural Science,2007,25(4):404-407.
[2]苏毅,王克如,李少昆,等.棉花植株水分含量的高光谱监测模型研究[J].棉花学报,2010,22(6):554-560.Su Yi,Wang Keru,Li Shaokun,et al.Monitoring models of the plant water content based on cotton canopy hyperspectral reflectance[J].Cotton Science,2010,22(6):554-560.
[3]刘小军,田永超,姚霞,等.基于高光谱的水稻叶片含水量监测研究[J].中国农业科学,2012,45(3):435-442.Liu Xiaojun,Tian Yongchao,Yao Xia,et al.Monitoring leaf water content based on hyperspectra in rice[J].Scientia Agriculture Sinica,2012,45(3):435-442.
[4]Kramer P J.Water relations of plants[M].New York:New York Press,1983.
[5]章杰,刘江娜,邓晓艳,等.干旱对特早熟陆地棉光合特性与产量的影响[J].新疆农业科学,2010,47(7):1397-1401.Zhang Jie,Liu Jiangna,Deng Xiaoyan,et al.Effects of drought on photosynthetic characteristics and yield of early maturing up land cotton[J].Xinjiang Agricultural Sciences,2010,47(7):1397-1401.
[6]薛利红,罗卫红,曹卫星,等.作物水分和氮素光谱诊断研究进展[J].遥感学报,2003,7(1):73-80.Xue Lihong,Luo Weihong,Cao Weixing,et al.Research progress on the water and nitrogen detection using spectral reflectance[J].Journal of Remote Sensing,2003,7(1):73-80.
[7]Meyer G E,Anthony S,Shelton D P,et al.Electronic image analysis of crop residue on cover soil[J].Trans of the ASAE,1988,31(3):968-973.
[8]罗锡文,臧英,周志艳.精细农业中农情信息采集技术的研究进展[J].农业工程学报,2006,22(1):167-173.Luo Xiwen,Zang Ying,Zhou Zhiyan.Research progress in farming information acquisition technique for precision agriculture[J].Transactions of the Chinese Society of Agricultural Engineering,2006,22(1):167-173.
[9]程麒,黄春燕,王登伟,等.基于红外热图像的棉花冠层水分胁迫指数与光合特性的关系[J].棉花学报,2012,24(4):341-347.Cheng Qi,Huang Chunyan,Wang Dengwei,et al.Correlation between cotton canopy CWSI and photosynthesis characteristics based on infrared thermography[J].Cotton Science,2012,24(4):341-347.
[10]顾清,邓劲松,陆超,等.基于光谱和形状特征的水稻扫描叶片氮素营养诊断[J].农业机械学报,2012(8):170-174.Gu Qing,Deng Jingsong,Lu Chao,et al.Diagnosis of rice nitrogen nutrition based on spectral and shape characteristics of scanning leaves[J].Transactions of the Chinese Society of Agricultural Machinery,2012(8):170-174.
[11]Ahmad I S,Reid J F.Evaluation of color representations for maize images[J].Journal of Agricultural Engineering Research,1996,63(3):185-195.
[12]李亚兵,毛树春,韩迎春,等.不同棉花群体冠层数字图像颜色变化特征研究[J].棉花学报,2012,24(6):541-547.Li Yabing,Mao Shuchun,Han Yingchun,et al.Study on the color characteristics variation of cotton canopy digital images[J].Cotton Science,2012,24(6):541-547.
[13]韦皆顶,费树岷,汪木兰,等.基于HSV彩色模型的自然场景下棉花图像分割策略研究[J].棉花学报,2008,20(1):34-38.Wei Jieding,Fei Shumin,Wang Mulan,et al.Research on the segmentation strategy of the cotton images on the natural condition based upon the HSV color-space model[J].Cotton Science,2008,20(1):34-38.
[14]Stephen O,Harahiko M.Classication of water stress in Sunagoke Moss using color texture and neural networks[J].Environment Control in Biology,2008,46(1):21-29.
[15]Takayama K,Nishina H.Early detection of water stress in tomato plants based on projected plant area[J].Environment Control in Biology,2007,45(4):241-249.
[16]Karcher D E,Richardson M D.Quantifying turf grass color us ing digital image analysis[J].Crop Science,2003,43(3):943-951.
[17]Tao Linmi,Xu Guangyou.Color in machine vision and its application[J].Chinese Science Bulletin,2001,46(17):1411-1421.
[18]王克如,李少昆,王崇桃,等.用机器视觉技术获取棉花叶片叶绿素浓度[J].作物学报,2006,32(1):34-40.Wang Keru,Li Shaokun,Wang Chongtao,et al.Acquired chlorophyll concentration of cotton leaves with technology of machine vision[J].Acta Agronomica Sinica,2006,32(1):34-40.
[19]危常州.基于对象特征的作物冠层图像识别系统:中国.2006SR08794[P].2006-04-06.Wei Changzhou.The crop canopy image recognition system based on object feature:China.2006SR08794[P].2006-07-06.
[20]雷咏雯,王娟,郭金强,等.一种基于图像分析提取作物冠层生物学参数的方法与验证[J].西北农业学报,2006,15(3):45-49.Lei Yongwen,Wang Juan,Guo Jinqiang,et al.Digital image analysis for estimating crop canopy parameters based on object features and on farming validation[J].Acta Agriculture Boreali-Occidentalis Sinica,2006,15(3):45-49.
[21]戴频勋,巩如梅,雷载兴,等.在摄影过程中正确使用标准灰板[J].影视技术,2005(1):17-20.Dai Pinxun,Gong Rumei,Lei Zaixing,et al.Corrected use the standard grey board during the process of photography[J].The Film and Television Technology,2005(1):17-20.
[22]王娟,危常州,王肖娟,等.采用灰板校正的计算机视觉预测棉花叶绿素含量[J].农业工程学报,2013,29(24):173-180.Wang Juan,Wei Changzhou,Wang Xiaojuan,et al.Estimation of chlorophyll contents in cotton leaves using computer vision based on gray board[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(24):173-180.
[23]吉雪芸,李毅.基于RGB向HSB转换的色调设计系统的探讨及实现[J].保定师范专科学校学报,2007,20(4):12-14.Ji Xueyun,Li Yi.Investigation and discussion of color-design systematic based on RGB to HSB transformation[J].Journal of Baoding Teachers College,2007,20(4):12-14.
[24]Gupta S D,Ibaraki Y,Pattanayak A K.Development of a digital image analysis method for real-time estimation of chlorophyll content in micro propagated potato plants[J].Plant Biotechnology Reports,2013,7(1):91-97.
[25]Jia Liangliang,Chen Xinping,Zhang Fusuo,et al.Use of digital camera to assess nitrogen status of winter wheat in the northern China plain[J].Journal of Plant Nutrition,2004,27(3):441-450.
[26]Kutner M H,Nachtsheim C J,Neter J,et al.Applied linear statistical models[M].5th ed.Chicago,IL:Mc Graw Hill,2005:w1-23
[27]苏金明,傅荣华,周建斌.统计软件SPSS for Windows实用指南[M].北京:电子工业出版社,2000:185-231.Su Jinming,Fu Ronghua,Zhou Jianbin.Statistical software SPSS for Windows a practical guide[M].Beijing:Electronic Industry Press,2000:185-231.
[28]袁道军,刘安国,原保忠,等.基于计算机视觉技术的油菜冠层营养信息监测[J].农业工程学报,2009,25(12):174-179.Yuan Daojun,Liu Anguo,Yuan Baozhong,et al.Nutrition information extraction of rape canopy based on computer-vision technology[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(12):174-179.
[29]蔡鸿昌,崔海信,宋卫堂,等.颜色模型在蔬菜谈氮素诊断中的应用前景探讨[J].农业工程学报,2005,21(增):113-117.Cai Hongchang,Cui Haixin,Song Weitang,et al.Review on application of color model in monitoring nitrogen status of vegetables[J].Transactions of the Chinese Society of Agricultural Engineering,2005,21(S1):113-117.
[30]李江波,饶秀勤,应义斌.基于照度￣反射模型的脐橙表面缺陷检测[J].农业工程学报,2011,27(7):338-342.Li Jiangbo,Rao Xiuqin,Ying Yibin.Detection of navel surface defects based on illumination-reflectance model[J].Transactions of the CSAE,2011,27(7):338-342.
[31]李江波,饶秀勤,应义斌.水果表面亮度不均校正及单阈值缺陷提取研究[J].农业机械学报,2011,42(8):159-163.Li Jiangbo,Rao Xiuqin,Ying Yibin.Correction algorithm of illumination nonuniformity on fruit surface and Defects Extraction Using Single Threshold Value[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(8):159-163.
[32]李锦卫,廖桂平.作物图像光照亮度补偿方法[J].农机化研究,2012(8):26-30.Li JInwei,Liao Guiping.Illumination compensation algorithm for crop image[J].Journal of Agricultural Mechanization Research,2012(8):26-30.
[33]应义斌,付峰.水果品质机器视觉检测中的图像颜色变换模型[J].农业机械学报,2004,35(1):85-89.Ying Yibin,Fu Feng.Color transformation model of fruit image in process of non-destructive quality inspection based on ma chine vision[J].Transactions of the Chinese Society for Agricultural Machinery,2004,35(1):85-89.
[2]苏毅,王克如,李少昆,等.棉花植株水分含量的高光谱监测模型研究[J].棉花学报,2010,22(6):554-560.Su Yi,Wang Keru,Li Shaokun,et al.Monitoring models of the plant water content based on cotton canopy hyperspectral reflectance[J].Cotton Science,2010,22(6):554-560.
[3]刘小军,田永超,姚霞,等.基于高光谱的水稻叶片含水量监测研究[J].中国农业科学,2012,45(3):435-442.Liu Xiaojun,Tian Yongchao,Yao Xia,et al.Monitoring leaf water content based on hyperspectra in rice[J].Scientia Agriculture Sinica,2012,45(3):435-442.
[4]Kramer P J.Water relations of plants[M].New York:New York Press,1983.
[5]章杰,刘江娜,邓晓艳,等.干旱对特早熟陆地棉光合特性与产量的影响[J].新疆农业科学,2010,47(7):1397-1401.Zhang Jie,Liu Jiangna,Deng Xiaoyan,et al.Effects of drought on photosynthetic characteristics and yield of early maturing up land cotton[J].Xinjiang Agricultural Sciences,2010,47(7):1397-1401.
[6]薛利红,罗卫红,曹卫星,等.作物水分和氮素光谱诊断研究进展[J].遥感学报,2003,7(1):73-80.Xue Lihong,Luo Weihong,Cao Weixing,et al.Research progress on the water and nitrogen detection using spectral reflectance[J].Journal of Remote Sensing,2003,7(1):73-80.
[7]Meyer G E,Anthony S,Shelton D P,et al.Electronic image analysis of crop residue on cover soil[J].Trans of the ASAE,1988,31(3):968-973.
[8]罗锡文,臧英,周志艳.精细农业中农情信息采集技术的研究进展[J].农业工程学报,2006,22(1):167-173.Luo Xiwen,Zang Ying,Zhou Zhiyan.Research progress in farming information acquisition technique for precision agriculture[J].Transactions of the Chinese Society of Agricultural Engineering,2006,22(1):167-173.
[9]程麒,黄春燕,王登伟,等.基于红外热图像的棉花冠层水分胁迫指数与光合特性的关系[J].棉花学报,2012,24(4):341-347.Cheng Qi,Huang Chunyan,Wang Dengwei,et al.Correlation between cotton canopy CWSI and photosynthesis characteristics based on infrared thermography[J].Cotton Science,2012,24(4):341-347.
[10]顾清,邓劲松,陆超,等.基于光谱和形状特征的水稻扫描叶片氮素营养诊断[J].农业机械学报,2012(8):170-174.Gu Qing,Deng Jingsong,Lu Chao,et al.Diagnosis of rice nitrogen nutrition based on spectral and shape characteristics of scanning leaves[J].Transactions of the Chinese Society of Agricultural Machinery,2012(8):170-174.
[11]Ahmad I S,Reid J F.Evaluation of color representations for maize images[J].Journal of Agricultural Engineering Research,1996,63(3):185-195.
[12]李亚兵,毛树春,韩迎春,等.不同棉花群体冠层数字图像颜色变化特征研究[J].棉花学报,2012,24(6):541-547.Li Yabing,Mao Shuchun,Han Yingchun,et al.Study on the color characteristics variation of cotton canopy digital images[J].Cotton Science,2012,24(6):541-547.
[13]韦皆顶,费树岷,汪木兰,等.基于HSV彩色模型的自然场景下棉花图像分割策略研究[J].棉花学报,2008,20(1):34-38.Wei Jieding,Fei Shumin,Wang Mulan,et al.Research on the segmentation strategy of the cotton images on the natural condition based upon the HSV color-space model[J].Cotton Science,2008,20(1):34-38.
[14]Stephen O,Harahiko M.Classication of water stress in Sunagoke Moss using color texture and neural networks[J].Environment Control in Biology,2008,46(1):21-29.
[15]Takayama K,Nishina H.Early detection of water stress in tomato plants based on projected plant area[J].Environment Control in Biology,2007,45(4):241-249.
[16]Karcher D E,Richardson M D.Quantifying turf grass color us ing digital image analysis[J].Crop Science,2003,43(3):943-951.
[17]Tao Linmi,Xu Guangyou.Color in machine vision and its application[J].Chinese Science Bulletin,2001,46(17):1411-1421.
[18]王克如,李少昆,王崇桃,等.用机器视觉技术获取棉花叶片叶绿素浓度[J].作物学报,2006,32(1):34-40.Wang Keru,Li Shaokun,Wang Chongtao,et al.Acquired chlorophyll concentration of cotton leaves with technology of machine vision[J].Acta Agronomica Sinica,2006,32(1):34-40.
[19]危常州.基于对象特征的作物冠层图像识别系统:中国.2006SR08794[P].2006-04-06.Wei Changzhou.The crop canopy image recognition system based on object feature:China.2006SR08794[P].2006-07-06.
[20]雷咏雯,王娟,郭金强,等.一种基于图像分析提取作物冠层生物学参数的方法与验证[J].西北农业学报,2006,15(3):45-49.Lei Yongwen,Wang Juan,Guo Jinqiang,et al.Digital image analysis for estimating crop canopy parameters based on object features and on farming validation[J].Acta Agriculture Boreali-Occidentalis Sinica,2006,15(3):45-49.
[21]戴频勋,巩如梅,雷载兴,等.在摄影过程中正确使用标准灰板[J].影视技术,2005(1):17-20.Dai Pinxun,Gong Rumei,Lei Zaixing,et al.Corrected use the standard grey board during the process of photography[J].The Film and Television Technology,2005(1):17-20.
[22]王娟,危常州,王肖娟,等.采用灰板校正的计算机视觉预测棉花叶绿素含量[J].农业工程学报,2013,29(24):173-180.Wang Juan,Wei Changzhou,Wang Xiaojuan,et al.Estimation of chlorophyll contents in cotton leaves using computer vision based on gray board[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(24):173-180.
[23]吉雪芸,李毅.基于RGB向HSB转换的色调设计系统的探讨及实现[J].保定师范专科学校学报,2007,20(4):12-14.Ji Xueyun,Li Yi.Investigation and discussion of color-design systematic based on RGB to HSB transformation[J].Journal of Baoding Teachers College,2007,20(4):12-14.
[24]Gupta S D,Ibaraki Y,Pattanayak A K.Development of a digital image analysis method for real-time estimation of chlorophyll content in micro propagated potato plants[J].Plant Biotechnology Reports,2013,7(1):91-97.
[25]Jia Liangliang,Chen Xinping,Zhang Fusuo,et al.Use of digital camera to assess nitrogen status of winter wheat in the northern China plain[J].Journal of Plant Nutrition,2004,27(3):441-450.
[26]Kutner M H,Nachtsheim C J,Neter J,et al.Applied linear statistical models[M].5th ed.Chicago,IL:Mc Graw Hill,2005:w1-23
[27]苏金明,傅荣华,周建斌.统计软件SPSS for Windows实用指南[M].北京:电子工业出版社,2000:185-231.Su Jinming,Fu Ronghua,Zhou Jianbin.Statistical software SPSS for Windows a practical guide[M].Beijing:Electronic Industry Press,2000:185-231.
[28]袁道军,刘安国,原保忠,等.基于计算机视觉技术的油菜冠层营养信息监测[J].农业工程学报,2009,25(12):174-179.Yuan Daojun,Liu Anguo,Yuan Baozhong,et al.Nutrition information extraction of rape canopy based on computer-vision technology[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(12):174-179.
[29]蔡鸿昌,崔海信,宋卫堂,等.颜色模型在蔬菜谈氮素诊断中的应用前景探讨[J].农业工程学报,2005,21(增):113-117.Cai Hongchang,Cui Haixin,Song Weitang,et al.Review on application of color model in monitoring nitrogen status of vegetables[J].Transactions of the Chinese Society of Agricultural Engineering,2005,21(S1):113-117.
[30]李江波,饶秀勤,应义斌.基于照度￣反射模型的脐橙表面缺陷检测[J].农业工程学报,2011,27(7):338-342.Li Jiangbo,Rao Xiuqin,Ying Yibin.Detection of navel surface defects based on illumination-reflectance model[J].Transactions of the CSAE,2011,27(7):338-342.
[31]李江波,饶秀勤,应义斌.水果表面亮度不均校正及单阈值缺陷提取研究[J].农业机械学报,2011,42(8):159-163.Li Jiangbo,Rao Xiuqin,Ying Yibin.Correction algorithm of illumination nonuniformity on fruit surface and Defects Extraction Using Single Threshold Value[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(8):159-163.
[32]李锦卫,廖桂平.作物图像光照亮度补偿方法[J].农机化研究,2012(8):26-30.Li JInwei,Liao Guiping.Illumination compensation algorithm for crop image[J].Journal of Agricultural Mechanization Research,2012(8):26-30.
[33]应义斌,付峰.水果品质机器视觉检测中的图像颜色变换模型[J].农业机械学报,2004,35(1):85-89.Ying Yibin,Fu Feng.Color transformation model of fruit image in process of non-destructive quality inspection based on ma chine vision[J].Transactions of the Chinese Society for Agricultural Machinery,2004,35(1):85-89.