An Analysis and Implementation of the Harris Corner Detector
Javier Sánchez, Nelson Monzón, Agustín Salgado
⚠ This is a preprint. It may change before it is accepted for publication.


In this work, we present an implementation and thorough study of the Harris corner detector. This feature detector relies on the analysis of the eigenvalues of the auto-correlation matrix. The algorithm comprises seven steps, including several measures for the classification of corners, a generic non-maximum suppression method for selecting interest points, and the possibility to obtain corners position with subpixel accuracy. We study each step in detail and propose several alternatives for improving the precision and speed. The experiments analyze the repeatability rate of the detector using different types of transformations.