一种改进的颜色跟踪系统在果实采摘中的研究

Research of an Improved Color Tracking System in Fruit Picking

针对人工成本的不断提高的新情况,农业果实采摘领域越来越迫切需求机械化和自动化。要实现这一需求,首先要解决的是自然光环境下颜色学习和跟踪的技术难题。在设计微控制器和图像感光元件的硬件系统平台上,通过把采集的图片的RGB颜色空间转换为HSV颜色空间,采用颜色学习的方式确定待识别样本阈值。在分析了颜色跟踪条件表达式比较法的基础上,提出了数组查表法的颜色跟踪算法,节省了时间,加快了颜色跟踪的速率,提高了系统的运行效率。

In response to the new situation of increasing labor costs,there are more and more urgent needs for mechanization and automation in the field of agricultural fruit picking.To achieve this demand,the first thing to be solved is the technical problem of color learning and tracking under natural light environment.On the hardware system platform for designing the microcontroller and the image sensor,the RGB color space of the collected pictures is converted into the HSV color space,and the threshold of the sample to be recognized is determined by color learning.Based on the analysis of the color tracking conditional expression comparison method,the color tracking algorithm of the array look-up table method is proposed,which saves time,speeds up the color tracking rate,and improves the operating efficiency of the system.