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Majid Dowlati

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Engineering and natural resources, Tuyserkan
Address: Tuyserkan Faculty of Engineering and Natural Resources
Phone: 09188540918

Research

Title
Application of machine-vision techniques to fish-quality assessment
Type
JournalPaper
Keywords
Defect; Fish; Image analysis; Image processing; Inspection; Machine vision; Non-destructive method; Quality assessment; Visible range
Year
2012
Journal TrAC - Trends in Analytical Chemistry
DOI
Researchers Majid Dowlati ، Seyed saeid Mohtasebi ، Miguel De la Guardia

Abstract

Machine vision is a non-destructive, rapid, economic, consistent and objective inspection tool and is also an evaluation technique based on image analysis and processing with a variety of applications. We review the use of machine vision and imaging technologies for fish-quality assessment. This review updates and condenses a representative selection of recent research and industrial solutions proposed in order to evaluate the general trends of machine vision and image processing in the visible range applied for inspection of fish and fish products. In order to determine freshness and composition, it is necessary to measure and to evaluate size and volume, to estimate weight, to measure shape parameters, to analyze skin and fillet in different color shades, to recognize fish species and sex, and to detect defects