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A Fast and Efficient Shape Descriptor for an Advanced Weed Type Classification Approach

Tannouche, AdilSbai, KhalidRahmoune, MiloudZoubir, AmineAgounoune, RachidSaadani, RachidRahmani, Abdelali
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Juni 2016
DOI10.11591/ijece.v6i3.pp1168-1175

Abstrak

In weed management, the distinction between monocots and dicots species is an important issue. Indeed, the yield is much higher with the application of a selective treatment instead of using a broadcast herbicide overall the parcel. This article presents a fast shape descriptor designed to distinguish between these two families of weeds. The efficiency of the descriptor is evaluated by analyzing data with the pattern recognition process known as the discriminant factor analysis (DFA). Excellent results have been obtained in the differentiation between these two weed species

Kata Kunci

Precision AgricultureInstrumentation and ControlMachine vision.Shape descriptorMachine visionReal-time image processingWeed type classificationPrecision agriculture.

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A Fast and Efficient Shape Descriptor for an Advanced Weed Type Classification Approach | International Journal of Electrical and Computer Engineering (IJECE) | Publiora