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