Basic Feature Point Detection Algorithm

This is a basic feature point detection algorithm that includes implementations of both the Harris detector and Harris-Laplace detector code, designed for ease of operation. The algorithm serves as a method for detecting key points in images by performing pixel-level analysis to identify significant corner points. The Harris detector is a commonly used corner detection algorithm that determines corner positions by computing the corner response function for each pixel in the image. The Harris-Laplace detector represents an improved version based on the Harris detector, incorporating scale-space concepts to detect corners at different scales. The implementation includes key functions such as corner response calculation, non-maximum suppression, and scale-space filtering. By utilizing this code, users can conveniently perform operations and experiments with feature point detection algorithms through configurable parameters and modular function design.