%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2015/06.20.13.19
%2 sid.inpe.br/sibgrapi/2015/06.20.13.19.32
%@doi 10.1109/SIBGRAPI.2015.36
%T Exploring the Use of Leaf Shape Frequencies for Plant Classification
%D 2015
%A Siravenha, Ana Carolina Quintao,
%A Carvalho, Schubert Ribeiro,
%@affiliation Federal University of Para
%@affiliation Vale Institute of Technology
%E Papa, Joćo Paulo,
%E Sander, Pedro Vieira,
%E Marroquim, Ricardo Guerra,
%E Farrell, Ryan,
%B Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)
%C Salvador, BA, Brazil
%8 26-29 Aug. 2015
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Plants classification, Shape features, Fourier transform, Feature selection.
%X 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 feedforward neural network, an accuracy of 97.45% was achieved.
%@language en
%3 example_v3.pdf