摘要:叶片图像的识别是计算机视觉的一个重要应用，其关键问题是如何对其进行有效的描述.提出了一种圆周特征描述方法.该方法用圆心在轮廓线上的圆与轮廓线和叶片形状区域分别相交所得到的圆心角、区域点的空间分布和灰度统计，分别表征叶片的轮廓、形状区域和灰度信息这3类特征，称其为叶片图像的圆周特征描述.通过改变圆的半径来产生由粗到细的圆周特征描述，给出了一种局部的多尺度安排，根据圆心到轮廓线其他各点的距离信息，确定半径的取值范围和各个尺度的半径取值.该方法描述全面，通过分析圆周与叶片图像相交的几何特性，自然地抽取了叶片的轮廓线、区域和灰度信息，且描述子满足对相似性变换的不变性.在公开的测试集上，对该方法进行叶片的分类和检索实验，取得了比现有流行方法更高的精确度，验证了该方法的有效性.



Abstract: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.



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