Explore MATLAB source code curated for "背景" with clean implementations, documentation, and examples.
An adaptive iterative reweighted penalized least squares algorithm suitable for background removal in Raman spectroscopy or chromatographic data analysis, with robust noise filtering capabilities and customizable parameter optimization.
Otsu's Maximum Inter-class Variance MATLAB Code - Principle Explanation: Otsu's method, proposed by Japanese scholar Nobuyuki Otsu in 1979, is an adaptive threshold determination technique also known as the Otsu method. It segments images into background and foreground based on grayscale characteristics. A larger inter-class variance indicates greater distinction between the two components; misclassifying foreground as background or vice versa reduces this distinction.
Adaptive threshold algorithm effectively separates foreground from background including handling non-uniform illumination conditions.
This program provides MATLAB source code for separating pedestrians from background using pre-extracted HOG features. The implementation includes both blocked and non-blocked feature extraction approaches, where blocking involves dividing images into smaller segments for more detailed feature representation. Classification is performed using minimum Euclidean distance method for enhanced pedestrian detection accuracy.
MATLAB implementation of frame difference algorithm for background analysis with sample images and detailed code workflow
MATLAB Implementation of HOG Feature Extraction and SVM Classification Methods for Person/Vehicle and Background Recognition
This project implements a high-speed color-background license plate detection system, featuring advanced image processing techniques and optimized region-of-interest (ROI) extraction algorithms for efficient vehicle identification.
Using maximum entropy threshold for grayscale image segmentation to separate foreground and background
This implementation of moving target detection in sea clutter environment is outstanding, self-developed and highly practical, featuring advanced signal processing algorithms for maritime target recognition.
Implementation of foreground-background segmentation through histogram-based adaptive thresholding method with code integration