自动采摘目标图像快速识别算法研究——基于K-means聚类算法

Research on Fast Recognition Algorithm of Automatic Picking Target Image Based on K-means Clustering Algorithm

介绍了K-means聚类算法的工作原理,研究了基于图像处理和K-means聚类算法的目标物体快速识别,设计了一套自动采摘目标图像快速识别算法,可以准确实现对苹果的快速精确识别,未来还可以扩展对其他水果的识别。实验结果表明:当采摘机器人的机械臂移动速度较高,能够准确对目标物体进行快速识别,证明了目标图像快速识别算法性能优良,具有较高的有效性和可行性。

It firstly introduces the working principle of K-means clustering algorithm,studies the target object fast recognition based on image processing and K-means clustering algorithm,and realizes a set of automatic picking target image fast recognition algorithm.The system can accurately realize the fast and accurate recognition of apple,and can also expand the recognition of other fruits in the future.The experimental results show that when the manipulator of the picking robot moves at a high speed,it can accurately and quickly recognize the target object,which proves that the fast recognition algorithm of automatic picking target image has excellent performance,high effectiveness and feasibility.