License Plate Recognition with Image Processing Techniques
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This article presents code implementations for license plate recognition systems. The code demonstrates critical image processing steps including grayscale conversion and binarization, which transform color images into binary black-and-white representations using thresholding algorithms like Otsu's method. The implementation further showcases feature extraction techniques that identify distinct characteristics such as alphanumeric characters and structural patterns from the processed images. Finally, the template matching process compares these extracted features against predefined character templates using correlation-based matching algorithms to precisely determine license plate locations and content. Collectively, these algorithmic steps form a comprehensive pipeline for accurate vehicle identification, demonstrating significant application value in traffic management systems and related fields through robust image processing and pattern recognition methodologies.
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