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.^^^^
Tipus:
Conferència
Drets:
(c) Springer, 2009
Tots els drets reservats
Citació Bibliogràfica:
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.