Leaf image recognition is a significant application of computer vision. Its key issue is how to effectively describe the leaf images. A method, called circular features description, is proposed. In this method, a circular centered at the contour is put on the image plane and the central angle, the spatial distribution of the region points, and the gray statistics characteristics are derived from its intersection to the leaf contour and region for describing the contour, region and gray features of the leaf image. By varying the size of the circle, a coarse to fine descriptor is yielded and a local multiscale arrangement is developed in which the range of the radius of the circles and the values of various scales taking for each contour point are determined by the distance of the remaining contour points to it. The proposed method naturally integrates the contour, region, and grayscale information of the leaf image and is also invariant to the similarity transform of the leaf image. It is conducted on the public test datasets and the experimental results show its higher accuracies over the state-of-the-art methods.