Paddy Diseases Identification with Texture Analysis using Fractal Descriptors Based on Fourier Spectrum

Abstract

The efforts to increasing the quantity and quality of rice production are obstructed by the paddy disease. This research attempted to identify the four major paddy diseases in Indonesia (leaf blast, brown spot, bacterial leaf blight, and tungro) using fractal descripton to analyze the texture of the lesions. The lesion images were extracted manually. The descripton of 'S' component of each lesion images then used in classification process using probabilistic neural networks. This techniques achieved at least 83.00°/e accuracy when identifying the diseases. This method has a potential to be used as one of the feature if it combined with other features, especially when two diseases with relatively same color involved.