This document describes a method for detecting and classifying plant diseases using image processing and artificial neural networks. The method involves preprocessing images through grayscaling, resizing and filtering. K-means clustering is used to segment infected leaf regions. Features are extracted from segmented images and fed into feedforward and cascaded feedforward neural networks for disease classification. The method achieved accurate classification of several common plant diseases with fewer iterations and better performance than traditional feedforward backpropagation neural networks. This automatic disease detection approach could help improve agricultural productivity by facilitating early detection on large farms.