20.7.3.7.7 Vegetables Detection, Vegetable Inspection, Roots, Potatoes

Heinemann, P.H., Pathare, N.P., Morrow, C.T.,
An Automated Inspection Station for Machine-Vision Grading of Potatoes,
MVA(9), No. 1, 1996, pp. 14-19.
Springer DOI 9608
BibRef

Zhou, L.Y., Chalana, V., Kim, Y.,
PC-Based Machine Vision System for Real-Time Computer-Aided Potato Inspection,
IJIST(9), No. 6, 1998, pp. 423-433. 9812
BibRef

Zeng, G.[Guang], Birchfield, S.T.[Stanley T.], Wells, C.E.[Christina E.],
Detecting and Measuring Fine Roots in Minirhizotron Images Using Matched Filtering and Local Entropy Thresholding,
MVA(17), No. 4, September 2006, pp. 265-278.
Springer DOI 0608
BibRef

Zeng, G.[Guang], Birchfield, S.T.[Stanley T.], Wells, C.E.[Christina E.],
Rapid automated detection of roots in minirhizotron images,
MVA(21), No. 3, April 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Cai, J.H.[Jin-Hai], Miklavcic, S.,
Surface fitting for individual image thresholding and beyond,
IET-IPR(7), No. 6, August 2013, pp. 596-605.
DOI Link 1312
background-foreground segmentation. botany BibRef

Kumar, P.[Pankaj], Cai, J.H.[Jin-Hai], Miklavcic, S.[Stan],
Root crown detection using statistics of Zernike moments,
ICARCV12(1130-1135).
IEEE DOI 1304
BibRef
And:
Automated Detection of Root Crowns Using Gaussian Mixture Model and Bayes Classification,
DICTA12(1-7).
IEEE DOI 1303
rice, corn, grass. BibRef

Mairhofer, S.[Stefan], Johnson, J.[James], Sturrock, C.J.[Craig J.], Bennett, M.J.[Malcolm J.], Mooney, S.J.[Sacha J.], Pridmore, T.P.[Tony P.],
Visual tracking for the recovery of multiple interacting plant root systems from X-ray CT images,
MVA(27), No. 5, July 2016, pp. 721-734.
Springer DOI 1608
BibRef

Peebles, M., Lim, S.H., Streeter, L., Duke, M., Au, C.K.,
Ground Plane Segmentation of Time-of-Flight Images for Asparagus Harvesting,
IVCNZ18(1-6)
IEEE DOI 1902
Clutter, Cameras, Image segmentation, Real-time systems, Mathematical model, asparagus, ground plane segmentation BibRef

Soltaninejad, M., Sturrock, C.J., Griffiths, M., Pridmore, T.P., Pound, M.P.,
Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks,
IP(29), 2020, pp. 6667-6679.
IEEE DOI 2007
Image segmentation, Computed tomography, Soil, Image resolution, Decoding, Biomedical imaging, plant phenotyping BibRef

Yu, G.[Guohao], Zare, A.[Alina], Sheng, H.[Hudanyun], Matamala, R.[Roser], Reyes-Cabrera, J.[Joel], Fritschi, F.B.[Felix B.], Juenger, T.E.[Thomas E.],
Root identification in minirhizotron imagery with multiple instance learning,
MVA(31), No. 6, August 2020, pp. Article43.
Springer DOI 2008
BibRef

Jayanthi, M.G., Shashikumar, D.R.[Dandinashivara Revanna],
Cucumber disease detection using adaptively regularised kernel-based fuzzy C-means and probabilistic neural network,
IJCVR(10), No. 5, 2020, pp. 385-411.
DOI Link 2009
BibRef

Appeltans, S.[Simon], Pieters, J.G.[Jan G.], Mouazen, A.M.[Abdul M.],
Detection of Leek Rust Disease under Field Conditions Using Hyperspectral Proximal Sensing and Machine Learning,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Farrar, M.B.[Michael B.], Wallace, H.M.[Helen M.], Brooks, P.[Peter], Yule, C.M.[Catherine M.], Tahmasbian, I.[Iman], Dunn, P.K.[Peter K.], Bai, S.H.[Shahla Hosseini],
A Performance Evaluation of Vis/NIR Hyperspectral Imaging to Predict Curcumin Concentration in Fresh Turmeric Rhizomes,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Lu, Y.W.[Ya-Wen], Wang, Y.X.[Yu-Xing], Parikh, D.[Devarth], Khan, A.[Awais], Lu, G.Y.[Guo-Yu],
Simultaneous Direct Depth Estimation and Synthesis Stereo for Single Image Plant Root Reconstruction,
IP(30), 2021, pp. 4883-4893.
IEEE DOI 2106
Image reconstruction, Estimation, Solid modeling, Shape, Cameras, Periodic structures, single image depth estimation BibRef

Fernández, C.I.[Claudio I.], Leblon, B.[Brigitte], Wang, J.F.[Jin-Fei], Haddadi, A.[Ata], Wang, K.[Keri],
Detecting Infected Cucumber Plants with Close-Range Multispectral Imagery,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Psiroukis, V.[Vasilis], Espejo-Garcia, B.[Borja], Chitos, A.[Andreas], Dedousis, A.[Athanasios], Karantzalos, K.[Konstantinos], Fountas, S.[Spyros],
Assessment of Different Object Detectors for the Maturity Level Classification of Broccoli Crops Using UAV Imagery,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Moualeu-Ngangué, D.[Dany], Bötzl, M.[Maria], Stützel, H.[Hartmut],
First Form, Then Function: 3D Reconstruction of Cucumber Plants (Cucumis sativus L.) Allows Early Detection of Stress Effects through Leaf Dimensions,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Guo, Y.[Yan], Xia, H.M.[Hao-Ming], Zhao, X.Y.[Xiao-Yang], Qiao, L.X.[Long-Xin], Qin, Y.C.[Yao-Chen],
Estimate the Earliest Phenophase for Garlic Mapping Using Time Series Landsat 8/9 Images,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Cardellicchio, A., Solimani, F., Dimauro, G., Summerer, S., Renò, V.,
Patch-based probabilistic identification of plant roots using convolutional neural networks,
PRL(183), 2024, pp. 125-132.
Elsevier DOI 2406
Deep learning, Root system architecture, Convolutional neural network BibRef

Singh, G.[Gursewak], Slonecki, T.[Tyler], Wadl, P.[Philip], Flessner, M.[Michael], Sosnoskie, L.[Lynn], Hatterman-Valenti, H.[Harlene], Gage, K.[Karla], Cutulle, M.[Matthew],
Implementing Digital Multispectral 3D Scanning Technology for Rapid Assessment of Hemp (Cannabis sativa L.) Weed Competitive Traits,
RS(16), No. 13, 2024, pp. 2375.
DOI Link 2407
BibRef

Masuzawa, H.[Hiroaki], Nakano, C.[Chuo], Miura, J.[Jun],
CG-based dataset generation and adversarial image conversion for deep cucumber recognition,
MVA23(1-5)
DOI Link 2403
Deep learning, Image recognition, Machine vision, Adversarial machine learning BibRef

Wang, Y.K.[Yi-Kai], Dong, Y.P.[Yin-Peng], Sun, F.C.[Fu-Chun], Yang, X.[Xiao],
Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos,
ICCV23(13844-13854)
IEEE DOI Code:
WWW Link. 2401
BibRef

Song, H.[Hao], Panjvani, K.[Karim], Liu, Z.G.[Zhi-Gang], Amar, H.[Huzaifa], Kochian, L.[Leon], Ye, S.J.[Sheng-Jian], Yang, X.[Xuan], Feurtado, J.A.[J. Allan], Chavda, K.[Krunal], Huatatoca, K.A.C.[Karina Angela Chimbo], Eramian, M.[Mark],
Plant Root Occlusion Inpainting with Generative Adversarial Network,
CVPPA23(531-539)
IEEE DOI 2401
BibRef

Gillert, A.[Alexander], Peters, B.[Bo], von Lukas, U.F.[Uwe Freiherr], Kreyling, J.[Jürgen], Blume-Werry, G.[Gesche],
Tracking Growth and Decay of Plant Roots in Minirhizotron Images,
WACV23(3688-3697)
IEEE DOI 2302
Codes, Neural networks, User interfaces, Monitoring, Applications: Environmental monitoring/climate change/ecology, Agriculture BibRef

Yang, S.[Si], Zheng, L.H.[Li-Hua], Chen, X.Y.L.[Xie-Yuan-Li], Zabawa, L.[Laura], Zhang, M.[Man], Wang, M.J.[Min-Juan],
Transfer Learning from Synthetic In-vitro Soybean Pods Dataset for In-situ Segmentation of On-branch Soybean Pods,
AgriVision22(1665-1674)
IEEE DOI 2210
Training, Image segmentation, Analytical models, Visualization, Image synthesis, Computational modeling, Transfer learning, Plant phenotyping BibRef

Lu, Y.W.[Ya-Wen], Lu, G.Y.[Guo-Yu],
3D Modeling Beneath Ground: Plant Root Detection and Reconstruction Based on Ground-Penetrating Radar,
WACV22(697-706)
IEEE DOI 2202
Geometry, Ground penetrating radar, Shape, Convolution, Instruments, Neural networks, Remote Sensing , Vision for Aerial/Drone/Underwater/Ground Vehicles BibRef

Möller, B.[Birgit], Schreck, B.[Berit], Posch, S.[Stefan],
Analysis of Arabidopsis Root Images: Studies on CNNs and Skeleton-Based Root Topology,
CVPPA21(1294-1302)
IEEE DOI 2112
Image segmentation, Time series analysis, Semantics, Systems architecture, Skeleton, Topology BibRef

Gillert, A.[Alexander], Peters, B.[Bo], von Lukas, U.F.[Uwe Freiherr], Kreyling, J.[Jürgen],
Identification and Measurement of Individual Roots in Minirhizotron Images of Dense Root Systems,
CVPPA21(1323-1331)
IEEE DOI 2112
Image segmentation, Head, Semantics, Estimation, Humidity, Length measurement, Skeleton BibRef

Horn, J.[Jannis], Zhao, Y.[Yi], Wandel, N.[Nils], Landl, M.[Magdalena], Schnepf, A.[Andrea], Behnke, S.[Sven],
Robust Skeletonization for Plant Root Structure Reconstruction from MRI,
ICPR21(10689-10696)
IEEE DOI 2105
Soil measurements, Magnetic resonance imaging, Semantics, Soil, Task analysis BibRef

Ufuktepe, D.K., Palaniappan, K., Elmali, M., Baskin, T.I.,
Rtip: A Fully Automated Root Tip Tracker For Measuring Plant Growth With Intermittent Perturbations,
ICIP20(2516-2520)
IEEE DOI 2011
Perturbation methods, Microscopy, Tracking, Image resolution, Feature extraction, Kinematics, Plant growth, Shi-Tomasi features, Video Tracking BibRef

Masuda, T.,
3D Shape Reconstruction of Plant Roots in a Cylindrical Tank From Multiview Images,
3D-Wild19(2149-2157)
IEEE DOI 2004
cameras, edge detection, feature extraction, image matching, image reconstruction, ray tracing, multiple views BibRef

Tabb, A., Duncan, K.E., Topp, C.N.,
Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets,
WACV18(586-595)
IEEE DOI 1806
Plant roots. computerised tomography, image segmentation, medical image processing, X-ray imaging BibRef

Belan, P.A., Araújo, S.A., Alves, W.A.L.,
An Intelligent Vision-Based System Applied to Visual Quality Inspection of Beans,
ICIAR16(801-809).
Springer DOI 1608
BibRef

Araújo, S.A., Alves, W.A.L., Belan, P.A., Anselmo, K.P.,
A Computer Vision System for Automatic Classification of Most Consumed Brazilian Beans,
ISVC15(II: 45-53).
Springer DOI 1601
BibRef

Janusch, I.[Ines], Kropatsch, W.G.[Walter G.],
Reeb Graphs Through Local Binary Patterns,
GbRPR15(54-63).
Springer DOI 1511
BibRef

Janusch, I.[Ines], Kropatsch, W.G.[Walter G.], Busch, W.[Wolfgang], Ristova, D.[Daniela],
Representing Roots on the Basis of Reeb Graphs in Plant Phenotyping,
PlantType14(75-88).
Springer DOI 1504
BibRef

Mairhofer, S.[Stefan], Sturrock, C.J.[Craig J.], Bennett, M.J.[Malcolm J.], Mooney, S.J.[Sacha J.], Pridmore, T.P.[Tony P.],
Visual Object Tracking for the Extraction of Multiple Interacting Plant Root Systems,
PlantType14(89-104).
Springer DOI 1504
BibRef

Nakini, T.K.D.[Tushar Kanta Das], de Souza, G.N.[Guilherme N.],
Distortion Correction in 3D-Modeling of Root Systems for Plant Phenotyping,
PlantType14(140-157).
Springer DOI 1504
BibRef

Dacal-Nieto, A.[Angel], Formella, A.[Arno], Carrión, P.[Pilar], Vazquez-Fernandez, E.[Esteban], Fernández-Delgado, M.[Manuel],
Common Scab Detection on Potatoes Using an Infrared Hyperspectral Imaging System,
CIAP11(II: 303-312).
Springer DOI 1109
BibRef
And:
Non-destructive Detection of Hollow Heart in Potatoes Using Hyperspectral Imaging,
CAIP11(II: 180-187).
Springer DOI 1109
BibRef

Barnes, M.[Michael], Cielniak, G.[Grzegorz], Duckett, T.[Tom],
Minimalist AdaBoost for Blemish Identification in Potatoes,
ICCVG10(I: 209-216).
Springer DOI 1009
BibRef
Earlier: A1, A3, A2:
Boosting minimalist classifiers for blemish detection in potatoes,
IVCNZ09(397-402).
IEEE DOI 0911
BibRef

Perciano, T.[Talita], Hirata, R.[Roberto], de Castro Jorge, L.A.[Lúcio André],
Ridge Linking Using an Adaptive Oriented Mask Applied to Plant Root Images with Thin Structures,
CIARP10(378-385).
Springer DOI 1011
BibRef

Wang, H.M.[Hong-Mei],
Impact of Magnetic Field on Mung Bean Ultraweak Luminescence,
CISP09(1-3).
IEEE DOI 0910
BibRef

Qi, L.Y.[Li-Yong], Yang, Q.H.[Qing-Hua], Bao, G.J.[Guan-Jun], Xun, Y.[Yi], Zhang, L.[Libin],
A Dynamic Threshold Segmentation Algorithm for Cucumber Identification in Greenhouse,
CISP09(1-4).
IEEE DOI 0910
BibRef

Mühlich, M.[Matthias], Truhn, D.[Daniel], Nagel, K.[Kerstin], Walter, A.[Achim], Scharr, H.[Hanno], Aach, T.[Til],
Measuring Plant Root Growth,
DAGM08(xx-yy).
Springer DOI 0806
BibRef

Erz, G.[Gregor], Posch, S.[Stefan],
A Region Based Seed Detection for Root Detection in Minirhizotron Images,
DAGM03(482-489).
Springer DOI 0310
BibRef

Kirchgessner, N., Spies, H., Scharr, H., Schurr, U.,
Root growth analysis in physiological coordinates,
CIAP01(589-594).
IEEE DOI 0210
BibRef

Huang, Q., Jain, A.K., Stockman, G.C., Smucker, A.J.M.,
Automatic image analysis of plant root structures,
ICPR92(II:569-572).
IEEE DOI 9208
BibRef

Lefebvre, M., Gil, S., Glassey, M.A., Baur, C., Pun, T.,
3D Computer Vision for Agrotics: The Potato Operation, An Overview,
ICPR92(I:207-210).
IEEE DOI BibRef 9200

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Tomato Detection, Tomato Plants .