Identification and classification of diseases in carrot vegetable using Discrete Wavelet Transform

Image processing has been proved to be a powerful tool for analysis in numerous fields and applications. Timely recognition of diseases is the main challenge in agriculture science. The present method uses naked eye observation to detect diseases which is less accurate and expensive for large farms. In this paper the system is proposed to identify and classify the diseases in carrot vegetable using the image processing techniques starting from image acquisition, preprocessing, testing, and training. Feature extraction is achieved through Discrete Wavelet Transform (DWT). The features are retrieved making use of the coefficients and then they are stored. These retrieved features stored in the database help to categorize the carrot vegetable disease using Probabilistic Neural Network.