DocumentCode :
982908
Title :
Automatic detection and classification of grains of pollen based on shape and texture
Author :
Rodríguez-Damián, María ; Cernadas, Eva ; Formella, Arno ; Fernández-Delgado, Manuel ; De Sá-Otero, Pilar
Author_Institution :
Dept. of Comput. Sci., Univ. de Vigo, Ourense
Volume :
36
Issue :
4
fYear :
2006
fDate :
7/1/2006 12:00:00 AM
Firstpage :
531
Lastpage :
542
Abstract :
Palynological data are used in a wide range of applications. Some studies describe the benefits of the development of a computer system to pollinic analysis. The system should involve the detection of the pollen grains on a slice, and their classification. This paper presents a system that realizes both tasks. The latter is based on the combination of shape and texture analysis. In relation to shape parameters, different ways to understand the contours are presented. The resulting system is evaluated for the discrimination of species of the Urticaceae family which are quite similar. The performance achieved is 89% of correct pollen grain classification
Keywords :
botany; computer vision; image classification; image segmentation; image texture; Urticaceae family; computer vision; image segmentation; palynological data; pollen grain classification; pollen grain detection; pollinic analysis; shape analysis; texture analysis; Air safety; Application software; Food technology; Geology; Image reconstruction; Numerical analysis; Object recognition; Optical microscopy; Scanning electron microscopy; Shape; Pollen classification; pollen grain; segmentation; shape analysis;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/TSMCC.2005.855426
Filename :
1643845
Link To Document :
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