Machine Vision Inspection of Golden Delicious Apples

Abstract

A machine vision system was developed to form a basis for single-pass quality feature inspection and grading of Golden Delicious apples. The inspection criteria were based on USDA standards for fresh market apples. Image analysis algorithms were developed to assess and quantify the quality features of color, shape, and russet. Over 300 Golden Delicious apples were inspected by the machine vision system and the results were compared to a human inspector. The vision system was able to correctly classify 100% of the apples for color, 92.3% for shape, and 82.5% for russetting.