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Proceedings Paper

Classification of fresh aromatic coconuts by using polynomial regression
Author(s): Suppachai Madue; Thanate Khaorapapong; Montri Karnjanadecha; Somchai Limsiroratana
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Paper Abstract

This paper present the classification of fresh aromatic coconuts into 3 types: single layer, double layer and one and a half layer by inspecting colors at the bottom of coconuts. We take the photos the bottom of coconuts in RGB mode, change the colors into the HSV mode, and then place 4 circles into the image. The 20 photos of each type are used to generate the relation of the rings for each type by using polynomial regression. Finally, we use the polynomial equations to test new 100 fresh aromatic coconuts, the result is 11.76% errors for single layer, 18.6% for one and a half layer and 18.18% error for double layers.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460R (26 February 2010); doi: 10.1117/12.853422
Show Author Affiliations
Suppachai Madue, Prince of Songkla Univ. (Thailand)
Thanate Khaorapapong, Prince of Songkla Univ. (Thailand)
Montri Karnjanadecha, Prince of Songkla Univ. (Thailand)
Somchai Limsiroratana, Prince of Songkla Univ. (Thailand)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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