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Research Article
Identification of Sugarcane Nodes Using Image Processing and Machine Vision Technology

K. Moshashai, M. Almasi, S. Minaei and A.M. Borghei

International Journal of Agricultural Research, 2008, 3(5), 357-364.

Abstract

An algorithm was designed for mechanizing sugarcane planting by machine vision system and image processing method. This algorithm uses convolution, threshold and look-up table operations for identification of sugarcane nods and sends the cut-point position of two consecutive nodes to microcontroller. The recognition algorithm which was used with right sobel matrix has 2.08±0.30% error. The right sobel matrix was assigned as the best mask matrix with the variance and standard deviation of 8.82 and 2.97, respectively. The precision of nods identification in sugarcane stalk by mentioned algorithm was estimated to be 97.92±0.3%. The test of this image processing method showed that the total running time of one image processing was less than 0.500 sec.

ASCI-ID: 32-3

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