The Application Study of Apple Color Grading by Particle Swarm Optimization Neural Networks

Author

Ji, Haiyan ; Yuan, Jinli

Author_Institution

Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing

Volume

1

fYear

0

fDate

0-0 0

Firstpage

2651

Lastpage

2654

Abstract

Color is an important index of fruit´s external quality, and is studying object of fruit sorting. The apple surface images were acquired by computer vision technology, image´s RGB format was converted to HIS format, and hue of every pixel was calculated to get the hue histogram of whole apple. Hue histogram was simplified as appearance times average at seven sub-ranges, and this seven appearance times average was regarded as characteristic parameters of apple color grading. The neural networks were trained by particle swarm optimization (PSO) algorithm, and the apple color was graded with the trained networks. For 16 apples, the grading correctness rate was 94%. The method achieves very high grading speed, gets high precision and has practical value

Keywords

agricultural products; computer vision; image classification; image colour analysis; neural nets; particle swarm optimisation; HIS format; apple color grading; apple surface images; computer vision; fruit sorting; hue histogram; image RGB format; neural networks; particle swarm optimization; pixel hue; Computer vision; Educational institutions; Electronic mail; Histograms; Image converters; Intelligent control; Neural networks; Particle swarm optimization; Pixel; Sorting; Apple color grading; Computer vision; Neural networks; Particle swarm optimization (PSO) algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712843

Filename

1712843