摘要： 在图像分类与识别算法研究中，目标几何特征的提取通常需要计算目标图像的最小外接矩形以获取长、宽等属性。针对该特点，提出一种利用顶点链码与离散格林理论相结合的方式提取目标图像的最小外接矩形的算法。该算法只需根据顶点链中垂直或水平方向上的点坐标即可求出目标的面积、形心和主轴。基于顶点链码和离散格林的主轴法和旋转法可快速求出目标的最小外接矩形。实验结果表明，旋转法的运算速度是现有算法的2倍左右，主轴法的速度又比旋转法快速2倍左右。

关键词: 顶点链码, 离散格林理论, 最小外接矩形

Abstract: Geometric feature extraction from image is a crucial step in image classification and recognition algorithms. It requires to calculate the Minimum Enclosing Rectangle(MER) of the image to get some attributes, such as length and width. This paper proposes an algorithm based on the combination of the vertex chain code and the discrete Green theorem to extract MER from image. According to this algorithm, it can calculate the area, centroid, and principal axis of the image easily, only with its point coordinates from the veritical or hrizontal direction of the vertex chain code. Experimental results show that the rotation method’s speed is two times of the current algorithms, while the principal axis method is three times of the rotation method.

Key words: vertex chain code, discrete Green theorem, Minimum Enclosing Rectangle(MER)

中图分类号: 

• TP312