基于多传感器信息融合的水果综合品质检测与分级
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摘要
由于单传感器获取信息不全,利用单一检测技术无法实现水果综合品质评价,多传感器信息融合成为水果分级分选的关键技术。介绍了信息融合的原理与方法,对多传感信息融合技术在水果品质检测中的应用进行了综述,旨在为水果分级分选提供技术参考。
Because of the incomplete information obtained by single sensor, the comprehensive quality evaluation of fruit could not be realized by using single detection technology. Multi-sensor information fusion had become the key technology of fruit grading. In this paper, the principle and method of information fusion were introduced, and the application of multi-sensor information fusion technology in fruit quality inspection was summarized. The purpose was to provide technical reference for fruit grading and sorting.
Because of the incomplete information obtained by single sensor, the comprehensive quality evaluation of fruit could not be realized by using single detection technology. Multi-sensor information fusion had become the key technology of fruit grading. In this paper, the principle and method of information fusion were introduced, and the application of multi-sensor information fusion technology in fruit quality inspection was summarized. The purpose was to provide technical reference for fruit grading and sorting.
引文
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[14]徐赛,陆华忠,周志艳,等.基于高光谱与电子鼻融合的番石榴机械损伤识别方法[J].农业机械学报,2015,46(7):214-219.
[15]邹小波,赵杰文.计算机视觉、电子鼻、近红外光谱三技术融合的苹果品质检测研究[D].镇江:江苏大学,2008.
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[17]展慧,李小星,周竹,等.高云基于近红外光谱和机器视觉融合技术的板栗缺陷检测[J].农业工程学报,2011,27(2):345-349.
[18]李先锋,朱伟兴,花小朋,等.基于D-S证据理论的决策级多特征融合苹果分级方法[J].农业机械学报,2011,42(6):188-193.
[19]黄星奕,钱媚,徐富斌.基丁机器视觉和近红外光谱技术的杏干品质无损检测[J].农业程学报,2012,28(7):260-265.
[20]闫正虎,杨晓京.基于颜色和气味多传感器融合的催熟水果检测系统研究[D].昆明:昆明理工大学,2013.
[21]谈英,顾宝兴,姬长英,等.基于颜色和重量特征的苹果在线分级系统设计[J].计算机工程与应用,2016,52(2):219-222.
[2]邓巍,丁为民.多传感器信息融合技术在水果质量评价中的应用[C].中国农业工程学会2005年学术年会论文集,2005.
[3]杨慧.多传感器信息融合技术的研究与应用[D].哈尔滨:哈尔滨工程大学,2010.
[4]DULL G G.Nondestructive evaluation of quality of stored fruits and vegetables[J].Food Technol,1986,40(4):106-110.
[5]FILDES J M,CINAR A.Sensor fusion and intelligent control for food processing[C].ASAE,Food Processing Automation Conference IV,1995:67-72.
[6]STEINMETZ V,SEVILA F,BELLON-MAUREL V.A methodology for sensor fusion design:application to fruit quality assessment[J].J agric Engng Res,1999(74):21-31.
[7]ARMSTRONG P,RONE M L,BRUSEWITZ G H.Peach firmness determination using two different nondestructive vibrational sensing instruments[J].Transactions of the ASAE,1997,40(3):99-103.
[8]STEINMETZ V,ROGER J M,MOLTOH J.On-line fusion of color camera and spectrophotometer for sugar content prediction of Apples[J].J Agric Eng Res,1999(73):207-216.
[9]MENDOZA F,LU R,ARIANA D,et al.Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content[J].Postharvest Biology and Technology,2011,62(2):149-160.
[10]杨万利,沈明霞.基于红外和可见光图像融合技术的苹果早期瘀伤检测研究[D].南京:南京农业大学,2009.
[11]刘鹏,屠康,苏子鹏,等.基于多传感器融合技术的苹果成熟度检测研究[J].江苏农业学报,2010,26(3):670-672.
[12]李军良,王从庆.基于机器视觉和近红外光谱的水果品质分级研究[D].杭州:南京航空航天大学,2011.
[13]刘超,田海清.基于可见近红外光谱与机器视觉信息融合的河套蜜瓜糖度检测方法研究[D].呼和浩特:内蒙古农业大学,2014.
[14]徐赛,陆华忠,周志艳,等.基于高光谱与电子鼻融合的番石榴机械损伤识别方法[J].农业机械学报,2015,46(7):214-219.
[15]邹小波,赵杰文.计算机视觉、电子鼻、近红外光谱三技术融合的苹果品质检测研究[D].镇江:江苏大学,2008.
[16]王克俊,董海鹰.基于多信息融合的苹果智能分级技术研究[D].兰州:兰州交通大学,2009.
[17]展慧,李小星,周竹,等.高云基于近红外光谱和机器视觉融合技术的板栗缺陷检测[J].农业工程学报,2011,27(2):345-349.
[18]李先锋,朱伟兴,花小朋,等.基于D-S证据理论的决策级多特征融合苹果分级方法[J].农业机械学报,2011,42(6):188-193.
[19]黄星奕,钱媚,徐富斌.基丁机器视觉和近红外光谱技术的杏干品质无损检测[J].农业程学报,2012,28(7):260-265.
[20]闫正虎,杨晓京.基于颜色和气味多传感器融合的催熟水果检测系统研究[D].昆明:昆明理工大学,2013.
[21]谈英,顾宝兴,姬长英,等.基于颜色和重量特征的苹果在线分级系统设计[J].计算机工程与应用,2016,52(2):219-222.