Exploring the Use of Leaf Shape Frequencies for Plant Classification

Plant identification and classification play an important role in ecology, but the manual process is cumbersome even for experimented taxonomists. Technological advances allows the development of strategies to make these tasks easily and faster. In this context, this paper describes a methodology fo...

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Bibliographic Details
Main Authors: Quintao Siravenha, Ana Carolina, Carvalho, Schubert R.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Brazil
Classification
Decision trees
Ecology
Feature extraction
Feature selection
Fourier transform
Frequency domains
Image color analysis
Manuals
Neural networks
Plants classification
Power plants
Shape
Shape features
Training
Vegetation
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Summary:Plant identification and classification play an important role in ecology, but the manual process is cumbersome even for experimented taxonomists. Technological advances allows the development of strategies to make these tasks easily and faster. In this context, this paper describes a methodology for plant identification and classification based on leaf shapes, that explores the discriminative power of the contour-centroid distance in the Fourier frequency domain in which some invariance (e.g. Rotation and scale) are guaranteed. In addition, it is also investigated the influence of feature selection techniques regarding classification accuracy. Our results show that by combining a set of features vectors - in the principal components space - and a feed forward neural network, an accuracy of 97.45% was achieved.
ISSN:1530-1834
2377-5416
1530-1834
DOI:10.1109/SIBGRAPI.2015.36