Image Processing for the Identification of Leaf Disease
Keywords:
Image Processing, Leaf Disease Detection, Corn Diseases, CNN, Feature Extraction, SegmentationAbstract
This paper explores the application of image processing techniques for the detection and classification of plant leaf diseases, which is crucial for maintaining agricultural productivity. The study focuses on corn, a significant crop economically, and addresses the challenges posed by various corn leaf diseases. Advanced image processing methodologies, such as image acquisition, preprocessing, segmentation, and feature extraction, are utilized to enhance disease identification accuracy. Techniques like color transformation, noise removal, k-means clustering, and Otsu’s thresholding are employed to segment and analyze affected leaf areas.
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