Automatic Number Plate Detection Using Optimal Black Window Evolutionary Transfer Moth Fly with Alex Net Classification Approach

The Automatic Number Plate Recognition (ANPR) technology can automatically photograph and identify vehicle license plates. It uses advanced computer vision technologies to analyse video surveillance footage. Automatic License Plate Recognition (ALPR) is used to identify cars in car components, stolen vehicles, and traffic management. Many Automatic Number Plate Recognition (ANPR) research have practical obstacles. These challenges include being limited to predefined borders, interior spaces, and vehicle velocities on designated driveways. We introduce the Black Window evolutionary Transfer Moth fly (BWETM) with Alex. This research aims to extract number plate attributes and improve detection. The Preprocessing approach improves the median construct, while Morphological Methods help identify the License Plate. The Enhanced Sliding Contract Window aids segmentation. Finally, the hybrid Black Window and Evolutionary Transfer Moth fly (BW-ETMFO), and Alex net architecture achieve optimum image characteristics and boost classification accuracy. The method’s Sensitivity, Specificity, F-measure, Recall, and Precision are compared to traditional approaches to determine its accuracy. The suggested solution surpasses other conventional methods in identifying license plate numbers with 98.54% accuracy, regardless of image quality degradation.