Corner Detection using Moravec Interest Operator

I have developed a custom algorithm that utilizes the Moravec Interest Operator to extract corner points from images. The implementation involves calculating intensity variations across different directions (typically 0°, 45°, 90°, and 135°) within a local window around each pixel. The algorithm computes the minimum variance value among these directions to identify corner points where intensity changes significantly in multiple orientations. This approach effectively distinguishes corners from edges and flat regions by analyzing directional intensity patterns. Through this algorithm, I can accurately detect corner points in images, which can be further applied to computer vision tasks such as object tracking, image registration, and 3D reconstruction. One of the key advantages of this implementation is its computational efficiency and detection accuracy, making it a valuable component in image processing pipelines. The algorithm's window-based approach allows for robust corner detection while maintaining reasonable computational complexity.