Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.
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José Blasco | Nuria Aleixos | Sergio Cubero | Sandra Munera | Enrique Molto | S. Cubero | J. Blasco | E. Moltó | N. Aleixos | S. Munera
[1] Julio Nogales-Bueno,et al. Comparative study on the use of anthocyanin profile, color image analysis and near-infrared hyperspectral imaging as tools to discriminate between four autochthonous red grape cultivars from La Rioja (Spain). , 2015, Talanta.
[2] Won Suk Lee,et al. An optimum method for real-time in-field detection of Huanglongbing disease using a vision sensor , 2015, Comput. Electron. Agric..
[3] V. Alchanatis,et al. Hyperspectral imaging of intact bell peppers , 2014 .
[4] L. Wu,et al. Development and experiment on automatic grading equipment for kiwi. , 2013 .
[5] Chun-Chieh Yang,et al. Development of multispectral imaging algorithm for detection of frass on mature red tomatoes , 2014 .
[6] Robert W. G. Hunt,et al. Measuring Colour: Hunt/Measuring Colour , 2011 .
[7] J. Qin,et al. Detection of citrus canker using hyperspectral reflectance imaging with spectral information divergence , 2009 .
[8] Shintaroh Ohashi,et al. Detection of external insect infestations in jujube fruit using hyperspectral reflectance imaging , 2011 .
[9] Antonietta Baiano,et al. Application of hyperspectral imaging for prediction of physico-chemical and sensory characteristics of table grapes , 2012 .
[10] Yi-Chao Yang,et al. Rapid detection of anthocyanin content in lychee pericarp during storage using hyperspectral imaging coupled with model fusion , 2015 .
[11] Jorge Chanona-Pérez,et al. Computer Vision System Applied to Classification of “Manila” Mangoes During Ripening Process , 2014, Food and Bioprocess Technology.
[12] F. Albert,et al. In-Line Estimation of the Standard Colour Index of Citrus Fruits Using a Computer Vision System Developed For a Mobile Platform , 2013, Food and Bioprocess Technology.
[13] Julio Nogales-Bueno,et al. Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image: a preliminary approach. , 2014, Food chemistry.
[14] G. Camps-Valls,et al. Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins , 2008 .
[15] Xuhui Zhao,et al. Development of a two-band spectral imaging system for real-time citrus canker detection , 2012 .
[16] Aboul Ella Hassanien,et al. Using machine learning techniques for evaluating tomato ripeness , 2015, Expert Syst. Appl..
[17] F. Albert,et al. Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform , 2014, Precision Agriculture.
[18] José Blasco,et al. Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features , 2009 .
[19] J. B. Li,et al. Machine vision technology for detecting the external defects of fruits — a review , 2015 .
[20] Jifeng Ning,et al. Predicting the anthocyanin content of wine grapes by NIR hyperspectral imaging. , 2015, Food chemistry.
[21] José Blasco,et al. Astringency assessment of persimmon by hyperspectral imaging , 2017 .
[22] José Blasco,et al. In-line sorting of irregular potatoes by using automated computer-based machine vision system , 2012 .
[23] Sumio Kawano,et al. Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes , 2013 .
[24] Olivier Sire,et al. Identification of foodborne pathogens within food matrices by IR spectroscopy , 2011 .
[25] V. Alchanatis,et al. Review: Sensing technologies for precision specialty crop production , 2010 .
[26] A. Peirs,et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .
[27] J. Blasco,et al. Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment , 2012, Food and Bioprocess Technology.
[28] Umezuruike Linus Opara,et al. Estimating blueberry mechanical properties based on random frog selected hyperspectral data , 2015 .
[29] Javier Calpe-Maravilla,et al. Design of a configurable multispectral imaging system based on an AOTF , 2011, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.
[30] Bernard Gosselin,et al. Original paper: Automatic grading of Bi-colored apples by multispectral machine vision , 2011 .
[31] Ning Wang,et al. Studies on banana fruit quality and maturity stages using hyperspectral imaging , 2012 .
[32] Lazhar Khriji,et al. Detecting surface cracks on dates using color imaging technique , 2013 .
[33] José Blasco,et al. Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision , 2009 .
[34] Jorge Chanona-Pérez,et al. Early detection of mechanical damage in mango using NIR hyperspectral images and machine learning , 2014 .
[35] E. Tollner,et al. Shortwave infrared hyperspectral imaging for detecting sour skin (Burkholderiacepacia)-infected onions , 2012 .
[36] J. Satheesh Kumar,et al. Assessment of banana fruit maturity by image processing technique , 2015 .
[37] Nuria Aleixos,et al. Erratum to: Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables , 2011 .
[38] Moon S. Kim,et al. Detection of cuticle defects on cherry tomatoes using hyperspectral fluorescence imagery , 2013 .
[39] Nuria Aleixos,et al. Selection of Optimal Wavelength Features for Decay Detection in Citrus Fruit Using the ROC Curve and Neural Networks , 2013, Food and Bioprocess Technology.
[40] Ling Bei,et al. Acousto-optic tunable filters: fundamentals and applications as applied to chemical analysis techniques [review article] , 2004 .
[41] José Blasco,et al. Citrus sorting by identification of the most common defects using multispectral computer vision , 2007 .
[42] José Blasco,et al. Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers , 2013 .
[43] Paul Geladi,et al. Calibration Standards and Image Calibration , 2007 .
[44] Won Suk Lee,et al. An evaluation of a vision-based sensor performance in Huanglongbing disease identification , 2015 .
[45] Da-Wen Sun,et al. Hyperspectral imaging for food quality analysis and control , 2010 .
[46] Jiangbo Li,et al. Automatic detection of common surface defects on oranges using combined lighting transform and image ratio methods , 2013 .
[47] Wei Liu,et al. Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit. , 2015, Food chemistry.
[48] Xuhui Zhao,et al. Effect of fruit harvest time on citrus canker detection using hyperspectral reflectance imaging , 2010 .
[49] Xuhui Zhao,et al. Multispectral Detection of Citrus Canker Using Hyperspectral Band Selection , 2011 .
[50] Hiroshi Okamoto,et al. Detection of potato tubers using an ultraviolet imaging-based machine vision system , 2010 .
[51] Renfu Lu,et al. Prediction of firmness and soluble solids content of blueberries using hyperspectral reflectance imaging , 2013 .
[52] Helmar Schubert,et al. Food particle technology. Part II: Some specific cases , 1987 .
[53] Mahdi Ghasemi-Varnamkhasti,et al. Detecting maturity of persimmon fruit based on image processing technique , 2015 .
[54] Jiewen Zhao,et al. Detection of Bruise on Pear by Hyperspectral Imaging Sensor with Different Classification Algorithms , 2010 .
[55] Ernest W. Tollner,et al. A liquid crystal tunable filter based shortwave infrared spectral imaging system: Design and integration , 2012 .
[56] A. Gowen,et al. Prediction of polyphenol oxidase activity using visible near-infrared hyperspectral imaging on mushroom (Agaricus bisporus) caps. , 2010, Journal of agricultural and food chemistry.
[57] Won Suk Lee,et al. Automated Systems Based on Machine Vision for Inspecting Citrus Fruits from the Field to Postharvest—a Review , 2016, Food and Bioprocess Technology.
[58] P. Baranowski,et al. Supervised classification of bruised apples with respect to the time after bruising on the basis of hyperspectral imaging data , 2013 .
[59] Antonio J. Serrano,et al. Comparison of ROC Feature Selection Method for the Detection of Decay in Citrus Fruit Using Hyperspectral Images , 2013, Food and Bioprocess Technology.
[60] D. L. Peterson,et al. Identifying defects in images of rotating apples , 2005 .
[61] Vincent Baeten,et al. Determination of the olive maturity index of intact fruits using image analysis , 2015, Journal of Food Science and Technology.
[62] Stephen R. Delwiche,et al. Hyperspectral near-infrared imaging for the detection of physical damages of pear , 2014 .
[63] José Blasco,et al. Original paper: Automatic sorting of satsuma ( Citrus unshiu ) segments using computer vision and morphological features , 2009 .
[64] Colm P. O'Donnell,et al. Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .
[65] A. Baltazar,et al. Bayesian classification of ripening stages of tomato fruit using acoustic impact and colorimeter sensor data , 2008 .
[66] H. P. W. Jayasuriya,et al. Development of a low cost machine vision system for sorting of tomatoes , 2013 .
[67] José Blasco,et al. Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm , 2007 .
[68] Renfu Lu,et al. Assessment of internal quality of blueberries using hyperspectral transmittance and reflectance images with whole spectra or selected wavelengths , 2014 .
[69] José Blasco,et al. Multispectral inspection of citrus in real-time using machine vision and digital signal processors , 2002 .
[70] Zhao Jiewen,et al. Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits , 2018 .
[71] Marino Uceda,et al. A sensor-software based on artificial neural network for the optimization of olive oil elaboration process , 2008 .
[72] Nahum Gat,et al. Imaging spectroscopy using tunable filters: a review , 2000, SPIE Defense + Commercial Sensing.
[73] Digvir S. Jayas,et al. Near infrared (NIR) hyperspectral imaging to classify fungal infected date fruits , 2014 .
[74] Mahmoud Omid,et al. Determination of Cherry Color Parameters during Ripening by Artificial Neural Network Assisted Image Processing Technique , 2015 .
[75] D. Lorente,et al. Development of a Hyperspectral Computer Vision System Based on Two Liquid Crystal Tuneable Filters for Fruit Inspection. Application to Detect Citrus Fruits Decay , 2014, Food and Bioprocess Technology.
[76] Moon S. Kim,et al. Red to far-red multispectral fluorescence image fusion for detection of fecal contamination on apples , 2012 .
[77] Moon S Kim,et al. Using parabolic mirrors for complete imaging of apple surfaces. , 2009, Bioresource technology.
[78] Vincent Leemans,et al. A real-time grading method of apples based on features extracted from defects , 2004 .
[79] Moon S. Kim,et al. A comparison of hyperspectral reflectance and fluorescence imaging techniques for detection of contaminants on spinach leaves , 2014 .
[80] Yong He,et al. Identification of crack features in fresh jujube using Vis/NIR hyperspectral imaging combined with image processing , 2014 .
[81] Javier Calpe-Maravilla,et al. Analysis of acousto-optic tunable filter performance for imaging applications , 2010 .
[82] Naoshi Kondo,et al. Development of a Mobile Grading Machine for Citrus Fruit , 2011 .
[83] Zou Xiaobo,et al. In-line detection of apple defects using three color cameras system , 2010 .
[84] Robert T. Furbank,et al. Detection of decay in fresh-cut lettuce using hyperspectral imaging and chlorophyll fluorescence imaging , 2015 .
[85] José Blasco,et al. Detecting rottenness caused by Penicillium genus fungi in citrus fruits using machine learning techniques , 2012, Expert Syst. Appl..