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Trends in Food Science & Technology 15 (2004) 230–249

Review

Recent developments in the applications of image processing techniques for food quality evaluation
Cheng-Jin Du and Da-Wen Sun*
FRCFT Group, Department of Agricultural and Food Engineering, University College Dublin, National University of Ireland, Earlsfort Terrace, Dublin 2, Ireland (tel.: +353-1-716-5528; fax: +353-1-4752119;e-mail: dawen.sun@ucd.ie)

Introduction
In the food industry, some quality evaluation is still performed manually by trained inspectors, which is tedious, laborious, costly and inherently unreliable due to its subjective nature. Increased demands for objectivity, consistency and efficiency have necessitated the introduction of computer-based image processing techniques. Recently, computer visionemploying image processing techniques has been developed rapidly, which can quantitatively characterize complex size, shape, colour and texture properties of foods. Image processing systems play a more and more important role in the food quality evaluation by maintaining accuracy and consistency while eliminating the subjectivity of manual inspections. They offer flexibility in application and can bereasonable substitutes for the human visual decision-making process. In order to develop an automated system for food quality evaluation, image processing techniques are often combined with mechanical and instrumental devices to replace human manipulative effort in the performance of a given process. In such a system, the image processing system is the centre, which controls the operation of themachinery. Li, Wang, and Gu (2002) developed an automated system for apple surface defect detection, which consisted of a feeding unit, an apple uniform spacing unit, a machine vision system, and a sorting conveyor. The apples were fed to the machine vision system for the defect inspection with the feeding and uniform spacing conveyors, and graded with the sorting unit. Mechanization is a remainingchallenge in applying machine vision for food quality evaluation, especially for those easily bruised and marked when they are in contact with hard surfaces. This paper will focus on the image processing techniques. The mechanical techniques for handling and packaging will not be discussed in detail here, interested readers can refer to the papers and books on this topic for details. Theapplication potential of image processing techniques to the food industry has long been recognised (Tillet, 1990). The food industry ranks among the top ten industries using image processing techniques (Gunasekaran, 1996), which have been proven successful for the objective and non-destructive evaluation of several food products (Timmermans, 1998). The basic theory of computer vision technology for foodquality

Image processing techniques have been applied increasingly for food quality evaluation in recent years. This paper reviews recent advances in image processing techniques for food quality evaluation, which include charge coupled device camera, ultrasound, magnetic resonance imaging, computed tomography, and electrical tomography for image acquisition; pixel and local pre-processingapproaches for image pre-processing; thresholding-based, gradient-based, region-based, and classification-based methods for image segmentation; size, shape, colour, and texture features for object measurement; and statistical, fuzzy logic, and neural network methods for classification. The promise of image processing techniques for food quality evaluation is demonstrated, and some issues which need to beresolved or investigated further to expedite the application of image processing technologies for food quality evaluation are also discussed. # 2003 Elsevier Ltd. All rights reserved.
* Corresponding author.
0924-2244/$ - see front matter # 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.tifs.2003.10.006

C.-J. Du and D.-W. Sun / Trends in Food Science & Technology 15 (2004) 230–249

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