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 USD A 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.
Original language | English (US) |
---|---|
Pages (from-to) | 901-906 |
Number of pages | 6 |
Journal | Applied Engineering in Agriculture |
Volume | 11 |
Issue number | 6 |
State | Published - Nov 1995 |
All Science Journal Classification (ASJC) codes
- General Engineering