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An automatic segmentation algorithm for touching rice grains images was proposed. Original gray image from rice inspection system was transformed into binary image and the edges of touching grains were extracted and de-noising was operated. This algorithm detected concave corner points of touching rice grains by a sector area and found corner point pairs by(More)
An adaptive learning rate Backpropagation Neural Network (BPNN) is proposed to image segmentation of rice disease spots. Rice blast is a common disease of rice and is tested in this paper. Firstly, the combination of different color feature parameters is selected as the input of the BPNN. Secondly, a BPNN with 5 input, 10 hidden neurons and 1 output is(More)
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