Line Laser Camera Calibration Using MATLAB

Line laser camera calibration is a crucial step in machine vision systems, primarily used to establish precise geometric relationships between the camera and laser plane. Implementing this process with MATLAB leverages its powerful matrix operations and Image Processing Toolbox to enhance calibration efficiency and accuracy.

The calibration procedure typically involves several key stages: First, preparation of calibration target datasets using checkerboard or dot array patterns. Then projecting laser lines onto the target while capturing multiple images at different orientations. The MATLAB program identifies laser stripes and calibration pattern feature points in the images, establishing mathematical relationships between the camera coordinate system and laser plane through coordinate transformation calculations.

The calibration function implementation consists of three main modules: image preprocessing, feature extraction, and parameter calculation. Image preprocessing employs filtering and thresholding techniques to enhance laser stripes; feature extraction utilizes edge detection algorithms like Canny operator combined with sub-pixel positioning methods to accurately locate laser centerlines; parameter calculation applies least-squares fitting to determine laser plane equations. The dataset should include calibration images captured at various angles and distances to ensure robust calibration results.

Upon completion, the calibration obtains laser plane equation parameters in the camera coordinate system, which are essential for subsequent applications like 3D reconstruction. MATLAB's implementation offers adjustable parameters and intuitive visualization, making it suitable for algorithm validation and educational demonstrations. Key functions involved include imread() for image loading, edge() for stripe detection, and polyfit() for plane fitting operations.