SUSAN corner detection is a classical algorithm, but has not the property of scale change. Using multi-scale characteristics of wavelet Transform, positioning in small-scale is accurate and anti-noise in large-scale is strong. The multi-resolution idea is introduced into the SUSAN algorithm in this paper. Then, a novel SUSAN multi-scale corner detection algorithm based on wavelet transform is presented, which might detect the corners in different scales and overcome the drawback that the single-scale SUSAN detector usually leads to detecting false corners due to noise. For comprehensive utilization of various scales corner information, corner screening programs from coarseness to fine is presented. Compared with SUSAN algorithm, the presented algorithm is more efficient in detecting the corners with accurate location and is robust to noise.