A semi-automatic method for the discrimination of diseased regions in detached leaf images using fuzzy c-means clustering

Author

Sekulska-Nalewajko, Joanna ; Goclawski, Jaroslaw

Author_Institution

Comput. Eng. Dept., Tech. Univ. of Lodz, Lodz, Poland

fYear

2011

fDate

11-14 May 2011

Firstpage

172

Lastpage

175

Abstract

This paper describes the segmentation method of stained leaf images for the purpose of the detection of leaf regions with anti-pathogen reaction colour products. The segmentation consist in the image conversion to HSV colour space and fuzzy c-means clustering in hue-saturation space to distinguish several pixels classes. These classes are then merged at the interactive stage into two final classes, where one of them determines the searched diseased areas.

Keywords

image colour analysis; image segmentation; pattern clustering; HSV colour space; anti-pathogen reaction colour products; detached leaf images; fuzzy C-means clustering; fuzzy c-means clustering; hue saturation space; image conversion; image pixels classes; image segmentation; leaf regions detection; semi automatic method; stained leaf images; Blades; Clustering algorithms; Image color analysis; Image segmentation; MATLAB; Pixel; Cucurbita plants; HSV colour space; fungal infection; fuzzy c-means clustering; reactive oxygen species;

fLanguage

English

Publisher

ieee

Conference_Titel

Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2011 Proceedings of VIIth International Conference on

Conference_Location

Polyana

Print_ISBN

978-1-4577-0639-4

Electronic_ISBN

978-966-2191-18-9

Type

conf

Filename

5960329