A Study of Image Processing on Identifying Cucumber Disease

Abstract

Abstract. Plant disease has been a major constraining factor in the production of cucumber，the traditional diagnostic methods usually take a long time, and the control period is often missed. We take computer image processing as a method, preprocessing the images of more than 100 sheets of collected samples of cucumber leaves, using the region growing method to extract scab area of leaves to get three feature parameters of shape, color and texture. And then, through the establishment of BP neural network pattern, the model identification accuracy of cucumber leaf disease can reach 80%. The experiment shows that by using this method, the diseases of cucumber leaves can be identified more quickly and accurately. And the feature extraction and automatic diagnosis of cucumber leaf disease can be achieved.

IDENTIFICATION OF HEALTHY AND DISEASED PADDY LEAVES USING kNNCLASSIFIER

“…Random forest classifier has given good result among the different classifier used by the authors. Only shape, a combination of shape and color features of the first and second set have been used for random forest classifier.In [24] proposed a method for identification of the leaf diseases in cucumber plant and obtained 80% accuracy using Back Propagation Neural Networks (BPNN). A pre-processing median filter has been applied for denoising.…”