In the domain of 3D scene reconstruction

motion estimate and machine vision

we need to detect the corners in a image

as well as obtain more information around corners

namely we could classify the corner further. We proposed a corner classification method based on directed area. First

we applied corner detection principle of wavelet transformation

based on the eigenvectors of covariance matrices

to detect the corner on the edge of images. Secondly

we defined six types of corners based on the edge information of both sides. Finally

corners can be classified by computing three directed areas arranged in order on the edge of the corners. The experiment indicated that the method of classifying corners has higher accuracy.