Machine vision system: a tool for quality inspection of food and agricultural products

被引:0
作者
Krishna Kumar Patel
A. Kar
S. N. Jha
M. A. Khan
机构
[1] Indian Agricultural Research Institute,Division of Post Harvest Technology
[2] CIPHET,undefined
[3] AMU,undefined
来源
Journal of Food Science and Technology | 2012年 / 49卷
关键词
Machine vision; Image processing; Image analysis; Quality inspection; Food and agricultural products;
D O I
暂无
中图分类号
学科分类号
摘要
Quality inspection of food and agricultural produce are difficult and labor intensive. Simultaneously, with increased expectations for food products of high quality and safety standards, the need for accurate, fast and objective quality determination of these characteristics in food products continues to grow. However, these operations generally in India are manual which is costly as well as unreliable because human decision in identifying quality factors such as appearance, flavor, nutrient, texture, etc., is inconsistent, subjective and slow. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. This inspection approach based on image analysis and processing has found a variety of different applications in the food industry. Considerable research has highlighted its potential for the inspection and grading of fruits and vegetables, grain quality and characteristic examination and quality evaluation of other food products like bakery products, pizza, cheese, and noodles etc. The objective of this paper is to provide in depth introduction of machine vision system, its components and recent work reported on food and agricultural produce.
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页码:123 / 141
页数:18
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共 340 条
  • [51] Crowe TG(2000)Colour vision in forest and wood engineering Landwards 55 2-885
  • [52] Delwiche MJ(1992)Thinning methodologies-a comprehensive survey IEEE Trans Pattern Anal Mach Intell 14 869-130
  • [53] Crowe TG(1998)Defects segmentation on ‘Golden Delicious’ apples by using colour machine vision Comput Electron Agric 20 117-102
  • [54] Delwiche MJ(1993)Computer vision and agricultural robotics for disease control: the potato operation Comput Electron Agric 9 85-9
  • [55] Daley W(1994)Potato operation: automatic detection of potato diseases Proc SPIE 2345 2-282
  • [56] Carey R(2002)Experimental and bioinformatics comparison of gene expression between T cells from TIL of liver cancer and T cells from UniGene J Gastroenterol 37 275-612
  • [57] Thomson C(1996)Detection of vegetation stress via a new high resolution fluorescence imaging system J Plant Physiol 148 599-95
  • [58] Das K(1996)Machine vision techniques for measuring the canopy of tomato seedling J Agric Eng Res 65 85-789
  • [59] Evans MD(2008)Image processing techniques for lemons and tomatoes classification Bragantia campinas 67 785-353
  • [60] Davidson VJ(1996)Het bepalen van het ontwikkelingsstadium bij dechampignon met computer beeldanalyse Champignoncultuur 40 347-60