Computer vision-based analysis of foods: A non-destructive colour measurement tool to monitor quality and safety


ATAÇ MOGOL B., GÖKMEN V.

JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, vol.94, no.7, pp.1259-1263, 2014 (Peer-Reviewed Journal) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 94 Issue: 7
  • Publication Date: 2014
  • Doi Number: 10.1002/jsfa.6500
  • Journal Name: JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.1259-1263
  • Keywords: segmentation, mean and featured information, food quality and safety, computer vision-based image analysis, colour measurement, DIGITAL IMAGE-ANALYSIS, BREAD, ACRYLAMIDE

Abstract

Computer vision-based image analysis has been widely used in food industry to monitor food quality. It allows low-cost and non-contact measurements of colour to be performed. In this paper, two computer vision-based image analysis approaches are discussed to extract mean colour or featured colour information from the digital images of foods. These types of information may be of particular importance as colour indicates certain chemical changes or physical properties in foods. As exemplified here, the mean CIE a(*) value or browning ratio determined by means of computer vision-based image analysis algorithms can be correlated with acrylamide content of potato chips or cookies. Or, porosity index as an important physical property of breadcrumb can be calculated easily. In this respect, computer vision-based image analysis provides a useful tool for automatic inspection of food products in a manufacturing line, and it can be actively involved in the decision-making process where rapid quality/safety evaluation is needed. (c) 2013 Society of Chemical Industry