International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 178 - Issue 49 |
Published: Sep 2019 |
Authors: Ranjit K. N. Naveen C. Chethan H. K. |
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Ranjit K. N. Naveen C. Chethan H. K. . Fruit Disease Categorization based on Color, Texture and Shape Features. International Journal of Computer Applications. 178, 49 (Sep 2019), 16-19. DOI=10.5120/ijca2019919401
@article{ 10.5120/ijca2019919401, author = { Ranjit K. N. Naveen C. Chethan H. K. }, title = { Fruit Disease Categorization based on Color, Texture and Shape Features }, journal = { International Journal of Computer Applications }, year = { 2019 }, volume = { 178 }, number = { 49 }, pages = { 16-19 }, doi = { 10.5120/ijca2019919401 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2019 %A Ranjit K. N. Naveen C. Chethan H. K. %T Fruit Disease Categorization based on Color, Texture and Shape Features%T %J International Journal of Computer Applications %V 178 %N 49 %P 16-19 %R 10.5120/ijca2019919401 %I Foundation of Computer Science (FCS), NY, USA
Nowadays digitization and automation of machine in agriculture field plays prominent role. In this paper, we have proposed method to classify fruit as diseased and non-diseased. Firstly, we used K means clustering method for segmentation of diseased regions. Later, we used to extract shape, color and texture features on segmented diseased regions. We have collected fruit diseased images from internet to create dataset and totally we have collect 2500 images from 10 fruit classes. We have conducted extensive experimentation using Artificial Neural Network and results shows that proposed method gives better performance compared to SVM and KNN.