Rapid Image Corner Detection using 9-Point Method

This MATLAB program implements a fast corner detection method that rapidly identifies corner points in images using a 9-point neighborhood analysis technique. The algorithm requires input images to be binary (two-color) format, containing only black and white pixels, to ensure accurate corner detection. The implementation utilizes a sliding window approach where each pixel's 3x3 neighborhood is examined to determine corner characteristics based on intensity transitions. Key implementation details include: - Binary image validation to confirm proper input format - Efficient matrix operations for 9-point pattern matching - Corner scoring based on gradient changes in the 3x3 window - Threshold-based corner classification system By employing this optimized detection method, the program significantly accelerates corner identification in digital images, thereby enhancing overall image processing efficiency for computer vision applications. The algorithm is particularly effective for structural analysis in technical drawings, document processing, and binary shape characterization.