To access the full text documents, please follow this link: http://hdl.handle.net/10854/2094

Improving a leaves automatic recognition process using PCA
Solé-Casals, Jordi; Travieso, Carlos M.; Alonso, Jesús B.; Ferrer, Miguel A.
Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; International Workshop on Practical Applications of Computational Biology and Bioinformatics (Iwpacbb 2008)
In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.
-Percepció de les formes
(c) Springer, 2009
Tots els drets reservats
Conference Object
Springer
         

Full text files in this document

Files Size Format View
artconlli_a2009 ... jordi_improving_leaves.pdf 202.1 KB application/pdf View/Open

Show full item record

Related documents

Other documents of the same author

 

Coordination

 

Supporters