Nondestructive Quality Evaluation Techniques
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K RatishRamanan | S AjayVino | J MeethaNesam | R. Mahendran | R. Mahendran | K. RatishRamanan. | S. AjayVino | J. MeethaNesam
[1] Peter Meinlschmidt,et al. Thermographic techniques and adapted algorithms for automatic detection of foreign bodies in food , 2003, SPIE Defense + Commercial Sensing.
[2] P. Zerbini. Emerging technologies for non-destructive quality evaluation of fruit , 2006 .
[3] Colm P. O'Donnell,et al. Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .
[4] Lembe S. Magwaza,et al. Non-destructive characterization and volume estimation of pomegranate fruit external and internal morphological fractions using X-ray computed tomography , 2016 .
[5] D. Jayas,et al. Detection of fungal infection in five different pulses using near-infrared hyperspectral imaging , 2016 .
[6] Gamal ElMasry,et al. Principles of Hyperspectral Imaging Technology , 2010 .
[7] Digvir S. Jayas,et al. Classification of vitreousness in durum wheat using soft X-rays and transmitted light images , 2006 .
[8] Gamal ElMasry,et al. Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging , 2011 .
[9] Anton du Plessis,et al. Non-destructive Estimation of Maize (Zea mays L.) Kernel Hardness by Means of an X-ray Micro-computed Tomography (μCT) Density Calibration , 2015, Food and Bioprocess Technology.
[10] Sunil K Mathanker,et al. X-Ray Applications in Food and Agriculture: A Review , 2013 .
[11] Christoph Reh. An Overview of Nondestructive Sensor Technology in Practice: The User's View , 2008 .
[12] Noel D.G. White,et al. Assessment of soft X-ray imaging for detection of fungal infection in wheat , 2009 .
[13] R. C. Murry,et al. Christensen's physics of diagnostic radiology , 1990 .
[14] Rafael Font,et al. Quantification of glucosinolates in leaves of leaf rape (Brassica napus ssp. pabularia) by near-infrared spectroscopy. , 2005, Phytochemistry.
[15] Xiwei Wang,et al. Structuring Image Templates for Identification of Foreign Object in Food in Shielding Packages Based On Wavelet Transforms , 2010 .
[16] Natsuko Toyofuku,et al. X-ray detection of defects and contaminants in the food industry , 2008 .
[17] Aldo Cipriano,et al. Automated fish bone detection using X-ray imaging , 2011 .
[18] Irwin R. Donis-González,et al. Internal characterisation of fresh agricultural products using traditional and ultrafast electron beam X-ray computed tomography imaging☆ , 2014 .
[19] Jan Sijbers,et al. A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs , 2016 .
[20] Franz Pfeiffer,et al. Novelty detection of foreign objects in food using multi-modal X-ray imaging , 2016 .
[21] J. Abbott. Quality measurement of fruits and vegetables , 1999 .
[22] F. J. García-Ramos,et al. Non-destructive technologies for fruit and vegetable size determination - a review , 2009 .
[23] Shyam Narayan Jha,et al. Nondestructive Evaluation of Food Quality , 2010 .
[24] Di Wu,et al. Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications , 2013 .
[25] Noel D.G. White,et al. Detection techniques for stored-product insects in grain , 2007 .
[26] Nachiket Kotwaliwale,et al. Radiography, CT and MRI , 2010 .
[27] Guang Li,et al. Tea Classification Based on Artificial Olfaction Using Bionic Olfactory Neural Network , 2006, ISNN.
[28] E A Navajas,et al. Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. , 2010, Meat science.
[29] Efstathios Z. Panagou,et al. Data mining derived from food analyses using non-invasive/non-destructive analytical techniques; determination of food authenticity, quality & safety in tandem with computer science disciplines , 2016 .
[30] A. Peirs,et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .
[31] Assessment of intramuscular fat level and distribution in beef muscles using X-ray microcomputed tomography. , 2010, Meat science.
[32] Hanna Piekarska-Boniecka,et al. Detection of the granary weevil based on X-ray images of damaged wheat kernels , 2014 .
[33] Behrouz Tousi,et al. Usage of Fruit Response to Both Force and Forced Vibration Applied to Assess Fruit Firmness-a Review , 2011 .
[34] Martine Wevers,et al. Comparison of X-ray CT and MRI of watercore disorder of different apple cultivars , 2014 .
[35] Sundaram Gunasekaran,et al. Computer Vision Systems , 2010 .
[36] K. Alagusundaram,et al. Quality analysis of mango fruit with fruit fly insect by non-destructive soft X-ray method. , 2015 .
[37] Yibin Ying,et al. Food Safety Evaluation Based on Near Infrared Spectroscopy and Imaging: A Review , 2016, Critical reviews in food science and nutrition.
[38] Noel D.G. White,et al. Detection of fungal infection and Ochratoxin A contamination in stored barley using near-infrared hyperspectral imaging , 2016 .
[39] Da-Wen Sun,et al. Improving quality inspection of food products by computer vision: a review , 2004 .
[40] S. Jha. Near Infrared Spectroscopy , 2010 .
[41] Yong He,et al. Theory and application of near infrared reflectance spectroscopy in determination of food quality , 2007 .
[42] Andrew Webb,et al. Introduction to Medical Imaging: Physics, Engineering and Clinical Applications , 2010 .
[43] Neeraj Seth,et al. X-ray imaging methods for internal quality evaluation of agricultural produce , 2011, Journal of Food Science and Technology.
[44] Quansheng Chen,et al. Recent advances in emerging imaging techniques for non-destructive detection of food quality and safety , 2013 .
[45] Marcelo Blanco,et al. NIR spectroscopy: a rapid-response analytical tool , 2002 .