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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #318107
Research Project: Nondestructive Quality Assessment and Grading of Fruits and Vegetables

Location: Sugarbeet and Bean Research

Title: Chapter 11. Quality evaluation of apple by computer vision

Author
item LU, YUZHEN - Michigan State University
item Lu, Renfu

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 6/1/2015
Publication Date: 5/1/2016
Citation: Lu, Y., Lu, R. 2016. Quality evaluation of apple by computer vision. 2nd Edition In: Sun, D. editor. Computer Vision Technology for Food Quality Evaluation. London, United Kingdom: Elsevier. p. 273-303.

Interpretive Summary:

Technical Abstract: Apple is one of the most consumed fruits in the world, and there is a critical need for enhanced computer vision technology for quality assessment of apples. This chapter gives a comprehensive review on recent advances in various computer vision techniques for detecting surface and internal defects and assessing texture and flavour in apples. While color imaging is being widely used for sorting and grading apples for color and size, it is insufficient for detecting surface defects like bruise. Thermal, X-ray, and magnetic resonance imaging are promising for internal defect detection; however, equipment cost and inspection speed are still the main hurdle for their commercial adoption. Much recent research has been focused on hyper- and multi-spectral imaging, especially spectral scattering, for assessing external and internal quality of apples. Cost effective imaging technology has recently been developed for pre-sorting apples in the orchard to achieve cost savings for the apple industry.