MATLAB Implementation of License Plate Localization Method
A license plate localization technique involving image grayscale conversion, binarization, mathematical morphology operations, and filtering processes with code implementation details
Explore MATLAB source code curated for "二值化" with clean implementations, documentation, and examples.
A license plate localization technique involving image grayscale conversion, binarization, mathematical morphology operations, and filtering processes with code implementation details
Image preprocessing procedures including edge denoising, binarization, and erosion operations, designed as foundational steps for license plate localization
Removing background through image subtraction and converting the result to binary format
Implementation details of edge detection algorithms following image binarization, developed using MATLAB, including specific implementations of Roberts, Sobel, Prewitt, and LoG (Laplacian of Gaussian) algorithms with code explanations and functionality descriptions
Full source code for license plate recognition using MATLAB, featuring plate localization, image binarization, noise filtering, character segmentation, and BP neural network-based character recognition with detailed implementation algorithms
MATLAB code for fingerprint recognition implementing enhancement, binarization, and thinning functions with detailed algorithm explanations
MATLAB-based image processing application featuring image reading, grayscale transformation, binarization, edge detection, and Hough transform with a simple GUI interface for real-time result visualization
Binarizing images with adaptive threshold method involves dividing the image into sub-images, calculating local mean values for each sub-image, and using these means as thresholds for binarization
This approach utilizes top-hat and bottom-hat transformations, threshold selection, and binarization to enhance license plate images, ultimately achieving effective segmentation through image preprocessing techniques.
Image recognition, text extraction, edge detection, binarization, pattern recognition design, and neural networks with MATLAB implementation examples