Automatic Detection of Pathogenic Diseases on Leaves

Automatic Detection of Pathogenic Diseases on Leaves
Author(s):
K.L.KARTHEEK, T. ANIL RAJU
Keywords:
leaf images, color segmentation using k-means clustering, textural features, co-occurrence matrix.
Abstract
Automatic detection of pathogenic disease in plants is becoming an important research topic in the pattern recognition. It is essential for monitoring large fields of crops, and thus automatically detects the symptoms of diseases as soon as they appear on plant leaves. Many conventional methods are not effective for disease recognition in plants because of the complexity in processing; one way to overcome this problem is to characterize the pixel being classified by parameters measuring the spatial organization of the pixels in its neighborhood. In this study, textural parameters of one-step and two-step encoded images were calculated in the form of a vector. These parameters were subject to the probabilistic neural networks classifier to decide which class image belonging to. Results show that the encoding method is a proper way to compress an image without losing textural information. It reduces the size of data and thereby reducing the computation time characteristics.. The proposed algorithm’s efficiency can successfully detect.
Article Details
Unique Paper ID: 143940 Publication Volume & Issue: Volume 3, Issue 4 Page(s): 105 - 110
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org