Segmentation and classification of tobacco seedling diseases
作者： D. S. Guru , P. B. Mallikarjuna , S. Manjunath
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摘要: In this paper, we present a novel algorithm for extracting lesion area and application of neural network to classify seedling diseases such as anthracnose frog-eye spots on tobacco leaves. The areas with leaf seedlings are segmented by contrast stretching transformation an adjustable parameter morphological operations. First order statistical texture features extracted from detect diagnose the disease type. These then used classification purpose. A Probabilistic Neural Network (PNN) is employed corroborate efficacy proposed model have conducted experimentation dataset 800 leaves which captured in uncontrolled lighting conditions. methodology presented herein effectively detected classified lesions upto accuracy 88.5933%. Further recommended compared Gray Level Co-occurrence Matrix (GLCM) based bring out their superiorities.
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