Plant Species Identification Using Multi-scale Fractal Dimension Applied to Images of Adaxial Surface Epidermis

Authors:
André R. Backes;Jarbas J. M. Sá Junior;Rosana M. Kolb;Odemir M. Bruno
Affiliations:
Instituto de Ciências Matemáticas e de Computação (ICMC), Universidade de São Paulo (USP), ;Instituto de Ciências Matemáticas e de Computação (ICMC), Universidade de São Paulo (USP), ;Instituto de Física de São Carlos (IFSC), Universidade de São Paulo (USP), ;Departamento de Ciências Biológicas, Universidade Estadual Paulista Júlio de Mesquita Filho,
Venue:
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Year:
2009

Citing 0
Cited 5

Characterizing 3D shapes using fractal dimension

CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Texture analysis using graphs generated by deterministic partially self-avoiding walks

Pattern Recognition
Review: Plant species identification using digital morphometrics: A review

Expert Systems with Applications: An International Journal
Salient features selection for multiclass texture classification

MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Gabor wavelets combined with volumetric fractal dimension applied to texture analysis

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 脳300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species.