一种快速提取植物叶片最小外接矩形算法

Algorithm for Minimum Bounding Rectangle of Fast Extracting Leaves

图像几何特征如矩形度等是图像分类与识别的重要依据之一,提取目标图像最小外接矩形具有重要的应用价值。本文提出和研究一种快速提取植物叶片最小外接矩形的算法。首先从水平和垂直两方向扫描植物叶片图像确定初始外接矩形,以初始外接矩形中心点作旋转中心点,确定主轴位置。然后不断旋转和平移主轴确定边界,通过比较边界所围区域面积的大小寻优到面积最小的外接矩形。使用Flavia数据库实验结果表明,算法运算量小,能快速有效地提取植物叶片最小外接矩形。

Geometric feature such as rectangle degree, which is a crucial foundation for image classification and recognition. Extracting minimum bounding rectangle is of important value. A new algorithm of minimum bounding rectangle of fast extracting plant leaves was studied in this paper. First, image was scanned from horizontal direction and vertical direction to extract the initial bounding rectangle. Horizontal axis and vertical axis were defined through the center of initial bounding rectangle. Then, with the main axis rotated and moved, four boundaries and a new bounding rectangle were obtained. Compared with the area, the minimum bounding rectangle was extracted. The effectiveness of this algorithm is verified by using Flavia plant leaves database. The results show that minimum bounding rectangle can be quickly found.