Literature DB >> 23572836

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

Krishna Kumar Patel1, A Kar, S N Jha, M A Khan.   

Abstract

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.

Entities:  

Keywords:  Food and agricultural products; Image analysis; Image processing; Machine vision; Quality inspection

Year:  2011        PMID: 23572836      PMCID: PMC3550871          DOI: 10.1007/s13197-011-0321-4

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


  6 in total

1.  Automatic measurement of pores and porosity in pork ham and their correlations with processing time, water content and texture.

Authors:  Cheng-Jin Du; Da-Wen Sun
Journal:  Meat Sci       Date:  2005-10-24       Impact factor: 5.209

2.  Evaluation of pork color by using computer vision.

Authors:  J Lu; J Tan; P Shatadal; D E Gerrard
Journal:  Meat Sci       Date:  2000-09       Impact factor: 5.209

3.  Image segmentation by histogram thresholding using fuzzy sets.

Authors:  Orlando J Tobias; Rui Seara
Journal:  IEEE Trans Image Process       Date:  2002       Impact factor: 10.856

4.  A computational approach to edge detection.

Authors:  J Canny
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  1986-06       Impact factor: 6.226

5.  Use of flow cytometry for determination of differential leukocyte counts in bovine blood.

Authors:  N C Jain; M J Paape; R H Miller
Journal:  Am J Vet Res       Date:  1991-04       Impact factor: 1.156

6.  Experimental and bioinformatics comparison of gene expression between T cells from TIL of liver cancer and T cells from UniGene.

Authors:  Biaoru Li; Supriya Perabekam; Ge Liu; Mei Yin; Shiwen Song; Alan Larson
Journal:  J Gastroenterol       Date:  2002       Impact factor: 7.527

  6 in total
  10 in total

1.  Kinetics of the crust thickness development of bread during baking.

Authors:  Alireza Soleimani Pour-Damanab; A Jafary; Sh Rafiee
Journal:  J Food Sci Technol       Date:  2012-10-24       Impact factor: 2.701

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

Authors:  Krishna Kumar Patel; A Kar; M A Khan
Journal:  J Food Sci Technol       Date:  2019-02-07       Impact factor: 2.701

3.  Novel non-destructive quality assessment techniques of onion bulbs: a comparative study.

Authors:  Md Nahidul Islam; Glenn Nielsen; Søren Stærke; Anders Kjær; Bjarke Jørgensen; Merete Edelenbos
Journal:  J Food Sci Technol       Date:  2018-06-19       Impact factor: 2.701

4.  Evaluation of plum fruit maturity by image processing techniques.

Authors:  Harpuneet Kaur; B K Sawhney; S K Jawandha
Journal:  J Food Sci Technol       Date:  2018-05-19       Impact factor: 2.701

5.  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

Review 6.  Application of Machine Vision System in Food Detection.

Authors:  Zhifei Xiao; Jilai Wang; Lu Han; Shubiao Guo; Qinghao Cui
Journal:  Front Nutr       Date:  2022-05-11

7.  Fluorescent films based on PVDF doped with carbon dots for evaluation of UVA protection of sunscreens and fabrication of cool white LEDs.

Authors:  Daniel Hernández-Rivera; Simei Darinel Torres-Landa; Miriam Rangel-Ayala; Vivechana Agarwal
Journal:  RSC Adv       Date:  2021-10-05       Impact factor: 4.036

8.  In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging.

Authors:  Mohd Firdaus Ibrahim; Fathinul Syahir Ahmad Sa'ad; Ammar Zakaria; Ali Yeon Md Shakaff
Journal:  Sensors (Basel)       Date:  2016-10-27       Impact factor: 3.576

Review 9.  Deep learning and machine vision for food processing: A survey.

Authors:  Lili Zhu; Petros Spachos; Erica Pensini; Konstantinos N Plataniotis
Journal:  Curr Res Food Sci       Date:  2021-04-15

10.  Electronic Eye Based on RGB Analysis for the Identification of Tequilas.

Authors:  Anais Gómez; Diana Bueno; Juan Manuel Gutiérrez
Journal:  Biosensors (Basel)       Date:  2021-03-02
  10 in total

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