Digit Recognition of Iranian License Plate Based on SOFM and Naive Bayesian Classifier

摘要

This paper presents license plate (LP) detection and recognition of Iranian LP digits. The proposed method can be divided into four major steps which are preprocessing, digit segmentation, feature extraction and finally classification using naive Bayesian (NB) classifier. In the preprocessing step, the obtained vehicle images are converted to the binary format based on a proposed threshold value. In the digit segmentation step, the LP digits are extracted from the image based on connected component labeling and some extracted characteristics of LP digits. In the feature extraction step, the self-organizing feature maps (SOFM) is used. In the classification step, the digits are recognized by a NB classifier which its performance is compared with a K-NN classifier. Various images in different conditions were used to test the proposed algorithm and experimental results demonstrated its robustness.