Explore MATLAB source code curated for "图像预处理" with clean implementations, documentation, and examples.
This is my original MATLAB source code for image preprocessing, featuring illumination compensation, rotation, and scale normalization. The implementation includes optimized algorithms for practical applications, with detailed explanations of key functions and processing techniques.
Complete face recognition system implementation featuring image preprocessing, K-L transform based feature extraction, and classifier design for fully automated facial identification
Code for image preprocessing using adaptive filters to remove noise, with implementation details for various filtering algorithms
Commercial Image Processing for Illumination Reduction - Image Preprocessing Suitable for Face Recognition Applications
Comprehensive implementation of image preprocessing methods (grayscale enhancement, wavelet high-pass filtering, LBP, iterative threshold segmentation, seed growing method, etc.) combined with RGB and texture (co-occurrence matrix) feature extraction algorithms
MATLAB program for automatic license plate localization: implementing image preprocessing, vertical edge detection, morphological operations, and license plate extraction with algorithm explanations and key function descriptions.
Load an image, perform preprocessing, detect edges, binarize the resulting image, apply Hough transform to obtain circular boundaries, and overlay this image with the original to enhance edges.
(1) Image Preprocessing: Perform image conversion, image enhancement, and edge detection on automotive images. (2) License Plate Localization: Segment the license plate image from preprocessed automotive images, i.e., locate the license plate position within a vehicle image. (3) Character Segmentation: Execute geometric correction, noise removal, binarization, and character segmentation on the license plate image to isolate individual character images composing the license plate number. (4) Character Recognition: Preprocess segmented characters (binarization, normalization), analyze and extract features, and recognize the segmented character images to output the license plate number in text format.
Shape features containing high-level semantic information hold significant application value in content-based image retrieval and image recognition. Various descriptors can characterize shape features, with Fourier descriptors being widely applied as they simplify 2D contour information into 1D problems. However, natural image shapes are typically noisy and irregular. This study proposes an image preprocessing method to obtain purified shape images and experimentally evaluates Fourier descriptor algorithms for shape feature extraction.
Vehicle detection approach using background subtraction, image preprocessing, and mathematical morphology operations