Literature DB >> 30956309

Potential of reflected UV imaging technique for detection of defects on the surface area of mango.

Krishna Kumar Patel1,2, A Kar1, M A Khan2.   

Abstract

Surface defects such as mechanical damage, black lesion, latex stains and shriveling of mango fruit are very common and responsible for lowering of market prices as well as postharvest losses. Current research, thus, focused on the study of reflected ultraviolet imaging (UV) technique, its potential of detecting defected mangoes and to develop a computer vision system which could find the reflected area on injured or defected mango's surface. The visual visualization of the bruised areas was noticed different when viewed under 15 W fluorescent UV tube (100-400 nm) light by UV camera. Hidden defects on fruit's surface detected just after the image acquisition by UV camera and brightness enhancement. Defected or injured surface of mangoes recognized easily by reflected UV imaging at 400 nm band-pass filter. The seriousness of injuries which were not detected by RGB color camera, detected by reflected UV imaging technique exactly.

Entities:  

Keywords:  Computer vision; Mango defects; Non-destructive; Reflected imaging; Ultraviolet

Year:  2019        PMID: 30956309      PMCID: PMC6423210          DOI: 10.1007/s13197-019-03597-w

Source DB:  PubMed          Journal:  J Food Sci Technol        ISSN: 0022-1155            Impact factor:   2.701


  3 in total

1.  Mango Anthracnose: Economic Impact and Current Options For Integrated Managaement.

Authors:  Luis Felipe Arauz
Journal:  Plant Dis       Date:  2000-06       Impact factor: 4.438

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

Authors:  Krishna Kumar Patel; A Kar; S N Jha; M A Khan
Journal:  J Food Sci Technol       Date:  2011-04-09       Impact factor: 2.701

3.  Quality parameters of mango and potential of non-destructive techniques for their measurement - a review.

Authors:  S N Jha; K Narsaiah; A D Sharma; M Singh; S Bansal; R Kumar
Journal:  J Food Sci Technol       Date:  2010-02-06       Impact factor: 2.701

  3 in total
  1 in total

1.  Monochrome computer vision for detecting common external defects of mango.

Authors:  Krishna Kumar Patel; A Kar; M A Khan
Journal:  J Food Sci Technol       Date:  2021-01-06       Impact factor: 2.701

  1 in total

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