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Improving a leaves automatic recognition process using PCA

Improving a leaves automatic recognition process using PCA
 
Solé-Casals, Jordi ; Travieso, Carlos M. ; Alonso, Jesús B. ; Ferrer, Miguel A.
2009

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Abstract

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, ...»»»»
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.^^^^

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Conference object

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(c) Springer, 2009
 
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Citation:

Solé Casals, J., Travieso, C.M., Alonso, J.B. & Ferrer, M.A. 2009, "Improving a Leaves Automatic Recognition Process Using PCA", 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (Iwpacbb 2008); ADVANCES IN SOFT COMPUTING; 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 08), eds. J. Corchado, J. DePaz, M. Rocha & F.F. Riverola, SPRINGER-VERLAG BERLIN, BERLIN; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, OCT 22-24, 2008, pp. 243.