MATLAB Implementation of Moravec Corner Detection Algorithm

In this tutorial, I will demonstrate how to implement the Moravec corner detection algorithm using MATLAB. The Moravec corner detection algorithm is a fundamental computer vision technique used to identify corner points in digital images. This algorithm plays a crucial role in detecting significant feature points that are essential for various computer vision and image processing applications. The implementation involves calculating intensity variations in multiple directions (typically 0°, 45°, 90°, and 135°) using small windows around each pixel. The key steps include: - Loading and preprocessing the input image (converting to grayscale if necessary) - Defining a sliding window size and corner response threshold - Computing intensity differences for each direction using window shifting - Calculating the minimum variance value for each pixel position - Applying non-maximum suppression to identify prominent corners MATLAB's matrix operations make this implementation efficient through vectorized computations. Key functions used include imread() for image input, padarray() for boundary handling, and conv2() for efficient window operations. The algorithm outputs coordinate positions of detected corners that can be visualized using plot() or scatter() functions. Let's begin the implementation process to effectively detect corner features in your images!