基于遗传算法的种子图象目标点模式匹配

在完成种子图象目标点坐标提取和由单摄像机、平面镜组成的摄像系统标定之后 ,关键问题是如何寻找图象中种子质心的对应点 .为了准确寻找到图象中种子质心的对应点 ,根据图象中种子区域的分布特点及遗传算法具有简单、通用、鲁棒性和适于并行处理等特性 ,提出了一种基于遗传算法的种子图象目标点模式匹配算法 ,即首先通过模糊聚类将单帧图象上的像点与虚像点划分为两类点群 ,然后通过在两类点群之间建立遗传机制来进行种子图象点模式匹配 .实验证明 ,采用该算法进行种子目标点群之间的匹配 ,具有快速准确的特点 ,并为种子空间点的恢复提供了准确的对应点寻找信息 .

A Point-pattern Matching Method of the Seed Images Based on the Genetic Algorithm

After the image coordinates of seed objects are computing and camera system composed of the single camera and a mirror are calibrated, searching corresponding points of seed centroids in the single-frame image is a key technique. In this paper, considering the distributing traits of the seeds in the single-frame image and the characteristics of genetic algorithm such as simple, current, robust and so on, a point-pattern matching method of the seed objects in the image based on the genetic algorithm is proposed. Firstly, by the fuzzy clustering method, the image points of seeds are distinguished to two groups, and then the genetic mechanism is established between the two point groups in the image, and the corresponding points are searched in the single-frame image. The experiments show this method can search corresponding points between two point groups of objects very fast and correctly, it is good for calculating the seed position in the space.