Explore MATLAB source code curated for "摄像头" with clean implementations, documentation, and examples.
A MATLAB video interface program designed for camera integration, featuring real-time image capture and processing capabilities through specialized functions like videoinput and getsnapshot.
A MATLAB-based application designed to capture audio input from microphones and video input from cameras, with comprehensive code implementation details for audio-visual data acquisition.
To perform inverse perspective mapping on images, camera height, field of view, and the desired output image's horizontal width (in meters) must be specified. With accurate parameters, high-quality inverse perspective transformed images can be generated. Key implementation involves calculating homography matrices using OpenCV's warpPerspective function with properly configured projection parameters.
Real-time image processing using camera input for traffic sign detection and recognition, incorporating edge detection, color recognition algorithms, and machine learning/deep learning model integration
Acquire and display video from a camera, requiring MATLAB 7.0 or higher with recommended installation of universal camera drivers for optimal compatibility.
Perspective transformation addresses camera perspective effects by converting between world coordinate systems and image coordinate systems, with practical MATLAB code implementation examples
A MATLAB-based face recognition program using camera input with satisfactory performance, providing reference for researchers in the field. Features algorithmic implementation details including face detection, feature extraction, and classification components.
Implementation of local image selection, camera activation, photo capture, image saving, histogram generation, image inversion, horizontal mirroring, and vertical mirroring with detailed code architecture.
Implementation of real-time image reading from camera with frame capture functionality using Python and OpenCV library
Comprehensive image enhancement techniques including local image loading, camera capture, image saving, histogram equalization, Sobel sharpening, smoothing filters, and median filtering with code implementation details