Recognition of the İmages with Random Forest Classifier Based on the LPP and LBP Methods
Sevcan Aytaç Korkmaz · Sakarya University Journal of Science · 2017
Image cells have taken with Light Microscope help. The local binary pattern (LBP) features have obtained for original images. High-dimensional of these LBP features is reduced to lower-dimensional with Locality Preserving Projections (LPP). These low dimensional data are classified by the Random Forest (RF), Naive Bayes (NB), and Artificial Neural Networks (ANN) classifiers. The classification results are compared with previous studies. The performance achieved with the ANN classifier is higher than the RF and NB classifiers. Moreover, feature vector size used in ANN classifier is a lower than feature vector size used in RF and NB classifiers. The success rates achieved with the ANN, RF, and NB classifiers is respectively 96.29%, 74.44%,and 70.00% according to LPP Method.