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Machine vision technology for detecting the external defects of fruits - a review

文献类型： 外文期刊

作者： Li, J. B. 1 ; Huang, W. Q. 1 ; Zhao, C. J. 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

关键词： Fruits;Machine vision;Colour imaging;Monochrome imaging;Hyperspectral imaging;External defects

期刊名称：IMAGING SCIENCE JOURNAL （ 影响因子：0.871； 五年影响因子：0.987 ）

ISSN： 1368-2199

年卷期： 2015 年 63 卷 5 期

页码：

收录情况： SCI

摘要： Machine vision is a rapid, consistent and objective inspection technique, which has expanded into many diverse industries. Its speed and accuracy provide one alternative for an automated, non-destructive and cost-effective technique to accomplish ever-increasing production and quality requirements. This method of inspection has found applications in the agricultural industry, including the inspection and grading of fruits. The presence of skin defects is one of the most influential factors in the price of fruit, since most consumer associate quality with a good appearance and the total absence of external defects. However, defect is more difficult than colour, shape and size to be inspected and graded. In this paper, current applications of machine vision in fruit external defects detection are briefly reviewed. Some detection technologies were presented. These technologies include image processing methods based on fruit two-dimensional and three-dimensional (3D) information, and hyperspectral and multispectral imaging. In addition, their advantages and disadvantages are also discussed. Development of multi-camera combination imaging systems will ensure that computer vision technique continues to meet the accuracy and quality requirements needed in this highly competitive and challenging fruit industry. However, reducing of processing time and merging analysis of different type of images will be still a challenge since the combination systems are more complicated in a real-time application.

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