Classification of fresh aromatic coconuts by using polynomial regression

Suppachai Madue; Thanate Khaorapapong; Montri Karnjanadecha; Somchai Limsiroratana

doi:10.1117/12.853422

26 February 2010 Classification of fresh aromatic coconuts by using polynomial regression

Suppachai Madue, Thanate Khaorapapong, Montri Karnjanadecha, Somchai Limsiroratana

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75460R (2010) https://doi.org/10.1117/12.853422
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

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.

Citation Download Citation

Suppachai Madue, Thanate Khaorapapong, Montri Karnjanadecha, and Somchai Limsiroratana "Classification of fresh aromatic coconuts by using polynomial regression", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460R (26 February 2010); https://doi.org/10.1117/12.853422

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