LICENSE PLATE DETECTION USING DEEP LEARNING TECHNIQUES

Automatic License Plate Recognition (ALPR) is a critical component of intelligent transportation systems, enablingefficient vehicle identification for applications such as traffic monitoring, access control, and law enforcement. Thispaper presents a method for license plate detection and recognition that integrates a Region- based ConvolutionalNeural Network (RCNN) with Optical Character Recognition (OCR). The RCNN is employed to accurately detectand localize license plates under diverse conditions, including variations in lighting, occlusion, and viewing angles.Following detection, OCR is applied to the extracted license plate regions to identify and decode the alphanumericcharacters. The proposed approach is evaluated on multiple benchmark datasets, demonstrating high accuracy androbustness in both detection and recognition tasks. Experimental results indicate that the system performs effectivelyin real-world scenarios, offering a reliable solution for automated license plate recognition.