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SegNet Approach for Vehicle License Plate Localization

Automatic License Plate Recognition (ALPR) system has wide applications in Intelligent Transportation System (ITS). Many researchers contributed advanced systems for the detection of License Plate (LP). License Plate Localization (LPL) is an important module in the ALPR system. In this paper, LPL is carried out by SegNet method of segmentation. Semantic pixel wise segmentation is accomplished using deep Convolution Neural Network (CNN) architecture. The input image is preprocessed using Gaussian filtering and Adaptive contrast enhancement method. The LP region is identified and segmented using Semantic Segmentation Network (SSN). Deep encoder-decoder network is used for the segmentation. The segmented LP regions are classified by CNN. The proposed method provides 96.3% LP detection accuracy. It achieved 95.6% Recall Value (RV), 96.2% Precision Value (PV) and 94.7% F-Measure Value (FMV).