Call For Paper Volume:8 Issue:12 Dec'2021 |

Recognizing the rice diseases detection based on SVM based techniques

Publication Date : 14/07/2018


DOI : 10.21884/IJMTER.2018.5176.VJVCG

Author(s) :

S.Abisha , T. Jayasree.


Volume/Issue :
Volume 5
,
Issue 7
(07 - 2018)



Abstract :

Rice leaf diseases can be detected and recognized automatically. The propose a new method, combining super pixels, expectation maximization (EM) algorithm, and logarithmic frequency pyramid of histograms of orientation gradients (PHOG), to recognize rice diseases. The proposed method is first, the super pixel operation is used to divide a diseased leaf image into a number of compact regions, which can dramatically accelerate the convergence speed of the EM algorithm that is adopted to segment the diseased leaf regions and obtain the lesion image. Second, the logarithmic frequency PHOG features are extracted from the segmented lesion image. Finally, Support Vector Machines (SVMs) are performed to classify and recognize different rice diseases. Conducted on a database of rice diseased leaf images, experimental results show the proposed method is effective and feasible for recognizing rice diseases.


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Recognizing the rice diseases detection based on SVM based techniques

July 9, 2018