Classification of License Plate Recognition
August 02, 2023
License Plate Recognition (LPR) can be classified into two main categories: 1. Optical Character Recognition (OCR) based LPR: This method uses OCR technology to recognize and extract the characters on license plates. It involves capturing an image of the license plate, preprocessing the image to enhance the quality, segmenting the characters from the plate, and finally recognizing the characters using OCR algorithms. This approach requires a clear and high-quality image of the license plate for accurate recognition. 2. Deep Learning based LPR: This method utilizes deep learning techniques, particularly convolutional neural networks (CNNs), to directly recognize license plates without explicitly segmenting the characters. The CNN models are trained on a large dataset of license plate images to learn the patterns and features of license plates. This approach is more robust to variations in license plate images, such as different fonts, sizes, and lighting conditions. Both OCR-based and deep learning-based LPR systems can be further classified based on the specific techniques used, such as template matching, feature extraction, character segmentation, and character recognition algorithms. Additionally, LPR systems can also be classified based on their deployment scenarios, such as fixed camera systems for parking enforcement or toll collection, mobile camera systems for law enforcement or traffic monitoring, or embedded camera systems in vehicles for automatic vehicle identification.