MATLAB Corner Detection Code Implementation

This code implements a corner detection program designed to extract pixel coordinates of corners from images, primarily used in camera calibration processes. Written in MATLAB, this implementation provides a flexible and user-friendly solution for computer vision applications. Corner detection serves as a fundamental task in computer vision, enabling precise localization and identification of corner features within digital images. During camera calibration, accurate corner pixel coordinates are essential for determining both intrinsic and extrinsic camera parameters. The program employs sophisticated image processing algorithms to analyze pixel intensity values and feature point distributions. Through MATLAB's built-in image processing toolbox functions, the implementation may utilize techniques such as Harris corner detection or Shi-Tomasi corner detection approaches. These algorithms work by calculating the corner response function based on image gradient analysis, identifying points where intensity changes significantly in multiple directions. Key functions likely include image preprocessing steps (noise reduction, contrast enhancement), corner response calculation, non-maximum suppression for precise corner localization, and coordinate extraction routines. The code automatically processes input images, detects corner features with sub-pixel accuracy when configured, and returns organized pixel coordinate data suitable for calibration workflows. This functionality significantly streamlines camera calibration procedures by providing reliable corner coordinate data necessary for computing camera parameters and enabling accurate image-based measurements and spatial relationships.