MATLAB Implementation of License Plate Localization Algorithm Using Row Scanning Technique

In my research, I developed a license plate localization algorithm using MATLAB that implements a row scanning technique. The algorithm achieves remarkable accuracy in plate detection through systematic image processing. The implementation begins with comprehensive image preprocessing using MATLAB's image processing toolbox, including grayscale conversion (rgb2gray function) and binarization (imbinarize with adaptive thresholding). Edge detection is performed using sophisticated operators like Canny or Sobel (edge function) to enhance plate boundaries. The core algorithm utilizes horizontal row scanning methodology, where the system analyzes pixel intensity variations across image rows to identify potential plate regions. This approach effectively minimizes localization errors by filtering out non-plate objects based on aspect ratio and texture characteristics. The row scanning implementation involves creating projection profiles and analyzing peak distributions to detect candidate regions. Further optimizations include morphological operations (imopen, imclose) to refine detected regions and heuristic validation using plate dimension constraints. The algorithm incorporates efficient searching mechanisms to reduce computational complexity while maintaining high precision. Research results demonstrate that this row scanning-based localization algorithm shows significant potential for practical applications, achieving robust performance under varying lighting conditions and vehicle orientations. The MATLAB implementation provides a modular structure allowing easy integration with subsequent character recognition stages.