CN112974303A - 一种基于高光谱的果品品质检测方法、设备及介质 - Google Patents
一种基于高光谱的果品品质检测方法、设备及介质 Download PDFInfo
- Publication number
- CN112974303A CN112974303A CN202110453992.3A CN202110453992A CN112974303A CN 112974303 A CN112974303 A CN 112974303A CN 202110453992 A CN202110453992 A CN 202110453992A CN 112974303 A CN112974303 A CN 112974303A
- Authority
- CN
- China
- Prior art keywords
- fruit
- hyperspectral image
- image
- production line
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 235000013399 edible fruits Nutrition 0.000 title claims abstract description 333
- 238000001514 detection method Methods 0.000 title claims abstract description 117
- 238000004519 manufacturing process Methods 0.000 claims abstract description 74
- 239000000447 pesticide residue Substances 0.000 claims abstract description 50
- 238000000034 method Methods 0.000 claims description 66
- 238000001228 spectrum Methods 0.000 claims description 41
- 230000007547 defect Effects 0.000 claims description 40
- 238000012545 processing Methods 0.000 claims description 34
- 230000008569 process Effects 0.000 claims description 23
- 238000001914 filtration Methods 0.000 claims description 15
- 238000010606 normalization Methods 0.000 claims description 15
- 238000003860 storage Methods 0.000 claims description 12
- 238000000513 principal component analysis Methods 0.000 claims description 11
- 238000012847 principal component analysis method Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 6
- 239000000126 substance Substances 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 12
- 238000004590 computer program Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 7
- 241000220225 Malus Species 0.000 description 6
- 235000013305 food Nutrition 0.000 description 5
- 235000013311 vegetables Nutrition 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000000701 chemical imaging Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 230000003595 spectral effect Effects 0.000 description 4
- 238000012795 verification Methods 0.000 description 4
- 235000021016 apples Nutrition 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000002310 reflectometry Methods 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 239000000243 solution Substances 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000012898 sample dilution Substances 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 235000005224 Eucalyptus bridgesiana Nutrition 0.000 description 1
- 244000239638 Eucalyptus bridgesiana Species 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 229960001948 caffeine Drugs 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 235000021022 fresh fruits Nutrition 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000010238 partial least squares regression Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- RYYVLZVUVIJVGH-UHFFFAOYSA-N trimethylxanthine Natural products CN1C(=O)N(C)C(=O)C2=C1N=CN2C RYYVLZVUVIJVGH-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
Description
Claims (10)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110453992.3A CN112974303B (zh) | 2021-04-26 | 2021-04-26 | 一种基于高光谱的果品品质检测方法、设备及介质 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110453992.3A CN112974303B (zh) | 2021-04-26 | 2021-04-26 | 一种基于高光谱的果品品质检测方法、设备及介质 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112974303A true CN112974303A (zh) | 2021-06-18 |
CN112974303B CN112974303B (zh) | 2022-11-08 |
Family
ID=76340153
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110453992.3A Active CN112974303B (zh) | 2021-04-26 | 2021-04-26 | 一种基于高光谱的果品品质检测方法、设备及介质 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112974303B (zh) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115758888A (zh) * | 2022-11-17 | 2023-03-07 | 厦门智康力奇数字科技有限公司 | 一种基于多机器学习算法融合的农产品安全风险评估方法 |
CN115780321A (zh) * | 2022-12-07 | 2023-03-14 | 江西绿萌科技控股有限公司 | 一种水果分级选择方法、装置、终端设备及存储介质 |
US11887351B1 (en) | 2023-07-26 | 2024-01-30 | Timea IGNAT | System and method for hyperspectral image-based quality control analysis of crop loads |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1603013A (zh) * | 2004-11-02 | 2005-04-06 | 江苏大学 | 基于三个摄像***在线水果品质检测分级的装置与方法 |
CN1837788A (zh) * | 2006-03-24 | 2006-09-27 | 浙江大学 | 基于光特性的水果内部品质在线无损检测方法和装置 |
CN101920245A (zh) * | 2009-10-27 | 2010-12-22 | 华东交通大学 | 基于可见近红外光谱的水果糖酸度在线检测与分选生产线 |
CN203170604U (zh) * | 2013-04-18 | 2013-09-04 | 北京农业智能装备技术研究中心 | 基于图像处理的小型农产品分选机 |
CN104598886A (zh) * | 2015-01-23 | 2015-05-06 | 中国矿业大学(北京) | 一种用近红外高光谱图像识别霉变花生的方法 |
CN105170485A (zh) * | 2015-10-07 | 2015-12-23 | 西北农林科技大学 | 一种猕猴桃检测分级装置 |
CN106525732A (zh) * | 2016-10-25 | 2017-03-22 | 沈阳农业大学 | 基于高光谱成像技术的苹果内外品质快速无损检测方法 |
CN109187378A (zh) * | 2018-10-17 | 2019-01-11 | 四川农业大学 | 基于高光谱图像的猕猴桃可溶性固形物含量无损检测方法 |
CN111507939A (zh) * | 2020-03-12 | 2020-08-07 | 深圳大学 | 一种水果外部缺陷类型的检测方法、装置和终端 |
CN111537469A (zh) * | 2020-06-04 | 2020-08-14 | 哈尔滨理工大学 | 一种基于近红外技术的苹果品质快速无损检测方法 |
CN111774324A (zh) * | 2020-07-22 | 2020-10-16 | 浙江德菲洛智能机械制造有限公司 | 一种针对大型果蔬的紧凑型多品质自动分选装置 |
-
2021
- 2021-04-26 CN CN202110453992.3A patent/CN112974303B/zh active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1603013A (zh) * | 2004-11-02 | 2005-04-06 | 江苏大学 | 基于三个摄像***在线水果品质检测分级的装置与方法 |
CN1837788A (zh) * | 2006-03-24 | 2006-09-27 | 浙江大学 | 基于光特性的水果内部品质在线无损检测方法和装置 |
CN101920245A (zh) * | 2009-10-27 | 2010-12-22 | 华东交通大学 | 基于可见近红外光谱的水果糖酸度在线检测与分选生产线 |
CN203170604U (zh) * | 2013-04-18 | 2013-09-04 | 北京农业智能装备技术研究中心 | 基于图像处理的小型农产品分选机 |
CN104598886A (zh) * | 2015-01-23 | 2015-05-06 | 中国矿业大学(北京) | 一种用近红外高光谱图像识别霉变花生的方法 |
CN105170485A (zh) * | 2015-10-07 | 2015-12-23 | 西北农林科技大学 | 一种猕猴桃检测分级装置 |
CN106525732A (zh) * | 2016-10-25 | 2017-03-22 | 沈阳农业大学 | 基于高光谱成像技术的苹果内外品质快速无损检测方法 |
CN109187378A (zh) * | 2018-10-17 | 2019-01-11 | 四川农业大学 | 基于高光谱图像的猕猴桃可溶性固形物含量无损检测方法 |
CN111507939A (zh) * | 2020-03-12 | 2020-08-07 | 深圳大学 | 一种水果外部缺陷类型的检测方法、装置和终端 |
CN111537469A (zh) * | 2020-06-04 | 2020-08-14 | 哈尔滨理工大学 | 一种基于近红外技术的苹果品质快速无损检测方法 |
CN111774324A (zh) * | 2020-07-22 | 2020-10-16 | 浙江德菲洛智能机械制造有限公司 | 一种针对大型果蔬的紧凑型多品质自动分选装置 |
Non-Patent Citations (2)
Title |
---|
杨仁欣: "高光谱图像预处理方法研究及进展", 《广西师范学院学报:自然科学版》, vol. 32, no. 1, 31 March 2015 (2015-03-31), pages 28 - 32 * |
管晓梅 等: "基于高光谱技术的果糖检测优化算法和可视化方法", 《光电子.激光》, vol. 29, no. 2, 27 February 2018 (2018-02-27), pages 173 - 180 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115758888A (zh) * | 2022-11-17 | 2023-03-07 | 厦门智康力奇数字科技有限公司 | 一种基于多机器学习算法融合的农产品安全风险评估方法 |
CN115758888B (zh) * | 2022-11-17 | 2024-04-23 | 厦门智康力奇数字科技有限公司 | 一种基于多机器学习算法融合的农产品安全风险评估方法 |
CN115780321A (zh) * | 2022-12-07 | 2023-03-14 | 江西绿萌科技控股有限公司 | 一种水果分级选择方法、装置、终端设备及存储介质 |
US11887351B1 (en) | 2023-07-26 | 2024-01-30 | Timea IGNAT | System and method for hyperspectral image-based quality control analysis of crop loads |
Also Published As
Publication number | Publication date |
---|---|
CN112974303B (zh) | 2022-11-08 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN112974303B (zh) | 一种基于高光谱的果品品质检测方法、设备及介质 | |
CN109100323B (zh) | 一种苹果水心病的透射光谱无损定量评价方法 | |
US8675989B2 (en) | Optimized orthonormal system and method for reducing dimensionality of hyperspectral images | |
Millan et al. | Image analysis‐based modelling for flower number estimation in grapevine | |
CN111414891B (zh) | 基于激光雷达与光学遥感的输电线路通道树高反演方法 | |
CN113160183B (zh) | 一种高光谱数据处理方法、设备及介质 | |
CN108335300A (zh) | 一种基于cnn的食品高光谱信息分析***与方法 | |
CN110555395A (zh) | 一种油菜冠层氮素含量等级分类评估方法 | |
Ulrici et al. | Automated identification and visualization of food defects using RGB imaging: Application to the detection of red skin defect of raw hams | |
CN116883674B (zh) | 多光谱图像去噪装置及使用该装置的食品品质检测*** | |
WO2023084543A1 (en) | System and method for leveraging neural network based hybrid feature extraction model for grain quality analysis | |
CN113125358B (zh) | 一种基于高光谱的食品农药残留检测方法、设备及介质 | |
CN112504977A (zh) | 茶叶含水率检测方法及其模型构建方法、介质和设备 | |
CN115223164A (zh) | 一种基于人工智能的甜瓜成熟度检测方法及*** | |
CN111751295A (zh) | 一种基于成像高光谱数据的小麦白粉病严重程度检测模型的建模方法及应用 | |
CN112964719B (zh) | 一种基于高光谱的食品果糖检测方法及装置 | |
CN114937038B (zh) | 面向可用性的遥感影像质量评价方法 | |
CN116468958A (zh) | 通信铁塔安全检测方法及*** | |
KR102576427B1 (ko) | 구름 이미지를 이용한 실시간 강수량 예측 장치, 이를 이용한 강수량 예측 방법 및 이를 제공하기 위한 컴퓨터 프로그램이 기록된 컴퓨터-판독가능매체 | |
CN113436096A (zh) | 一种基于像元标定的推扫式高光谱成像条带噪声消除方法 | |
CN112834454A (zh) | 基于近红外高光谱技术的冬枣检测方法 | |
CN111680258A (zh) | 监测作物涝渍胁迫程度的方法、装置、设备及存储介质 | |
CN111289516B (zh) | 植物叶片氨基酸含量检测方法及装置 | |
CN117054372B (zh) | 基于nirs与cv的茶叶品质等级检测方法和*** | |
CN114720436B (zh) | 基于荧光高光谱成像的农产品品质参数检测方法及设备 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A Method, Equipment, and Medium for High Spectral Fruit Quality Detection Effective date of registration: 20230519 Granted publication date: 20221108 Pledgee: Bank of Beijing Co.,Ltd. Jinan Branch Pledgor: Shandong Shenlan Zhipu Digital Technology Co.,Ltd. Registration number: Y2023980041054 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
PC01 | Cancellation of the registration of the contract for pledge of patent right |
Granted publication date: 20221108 Pledgee: Bank of Beijing Co.,Ltd. Jinan Branch Pledgor: Shandong Shenlan Zhipu Digital Technology Co.,Ltd. Registration number: Y2023980041054 |
|
PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A method, equipment, and medium for detecting fruit quality based on hyperspectral analysis Granted publication date: 20221108 Pledgee: Huaxia Bank Co.,Ltd. Jinan Branch Pledgor: Shandong Shenlan Zhipu Digital Technology Co.,Ltd. Registration number: Y2024980008356 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |