Relevant Techniques for License Plate Detection and Recognition

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License Plate Detection and Recognition Techniques: A gradient enhancement method is proposed to strengthen image edges through simple gradient transformations that highlight edge information, combined with dilation operations from mathematical morphology for rapid license plate localization. In the character segmentation phase, the minimum area rotation method determines the optimal license plate rotation angle, followed by vertical projection analysis to segment individual characters. Implementation involves gradient calculation algorithms like Sobel/Prewitt operators and morphological structuring elements for dilation.

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Relevant Techniques for License Plate Detection and Recognition: This paper proposes a gradient enhancement method to reinforce image edges. The technique primarily employs basic gradient transformations (e.g., using Sobel or Prewitt operators in OpenCV) to accentuate edge features, integrated with dilation operations from mathematical morphology (implemented through structuring elements) for efficient license plate localization. For character segmentation, we introduce the minimum area rotation method - calculated via rotating calipers algorithm or OpenCV's minAreaRect() function - to determine the optimal license plate orientation. Subsequently, vertical projection analysis (computing pixel density along horizontal axis) segments characters within the license plate. These methodologies enable more precise detection and recognition of license plates through systematic image processing pipelines.

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