Affordable Access

Automated strawberry grading system based on image processing

Authors
Journal
Computers and Electronics in Agriculture
0168-1699
Publisher
Elsevier
Publication Date
Volume
71
Identifiers
DOI: 10.1016/j.compag.2009.09.013
Keywords
  • Strawberry
  • Grading System
  • Image Processing
  • K-Means Clustering Method
  • The Dominant Colour Method
  • Multi-Attribute Decision Making Theory

Abstract

Abstract Using machine-vision technology to grade strawberries can increase the commercial value of the strawberry. The automated strawberry grading system has been set up based on three characteristics: shape, size and colour. The system can efficiently obtain the shape characteristic by drawing the lines and then class with K-means clustering method for the strawberry image. The colour of the strawberry adopts the Dominant Colour method into the a* channel, and the size is described by the largest fruit diameter. The strawberry automated grading system can use one, two or three characteristics to grade the strawberry into three or four grades. In order to solve the multicharacteristic problems, the multi-attribute Decision Making Theory was adopted in this system. The system applied a conveyer belt, a camera, an image box, two photoelectrical sensors, a leading screw driven by a motor, a gripper, two limit switches and so on. The system was controlled by the single-chip-microcomputer (SCM) and a computer. The results show that the strawberry size detection error is not more than 5%, the colour grading accuracy is 88.8%, and the shape classification accuracy is above 90%. The average time to grade one strawberry is below 3 s.

There are no comments yet on this publication. Be the first to share your thoughts.