Color-Based Localization Process for Colored Vehicle License Plates

The localization process for colored vehicle license plates is primarily based on color characteristics. For yellow plates with white characters, accurate localization can be achieved through systematic image processing. The implementation typically begins with extracting color information from the input image using techniques like color space conversion (e.g., RGB to HSV) and specific color thresholding to isolate the yellow regions. Following color extraction, morphological operations such as dilation and erosion help refine the regions of interest. Machine learning algorithms, particularly classifiers like SVM or CNN, can then be employed to distinguish true license plate regions from background noise. Pattern recognition techniques further enhance the accuracy by validating character arrangement and plate dimensions. This multi-step approach, combining color segmentation with intelligent classification, significantly improves both the precision and efficiency of license plate recognition systems.