Image feature detection is a fundamental issue in computer vision. SIFT[1] and SURF[2] are very effective in scale-space feature detection, but their stabilities are not good enough because unstable features such as edges are often detected even if they use edge suppression as a post-treatment. Inspired by Harris function[3], we extend Harris to scale-space and propose a novel method Harris-lik...