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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 the shortest Euclidean distance. The touching...
On automatic modulation there are two approaches, decision-theoretic and statistical pattern. An automatic modulation recognition system to recognize four digital signal classes as: MASK, MFSK, MPSK, MQAM is proposed in this paper, which using decision-theoretic based feature set addition to statistical pattern based feature set with VLBP(variable learning rate back-propagation)BP neural network and...
For detecting rice disease early and accurately, we presented an application of image processing techniques and Support Vector Machine (SVM) for detecting rice diseases. Rice disease spots were segmented and their shape and texture features were extracted. The SVM method was employed to classify rice bacterial leaf blight, rice sheath blight and rice blast. The results showed that SVM could effectively...
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