Full Utilization of a Single Image by Characterizing Multiple Regions of Interest for Line Tracing

Jinsung Ahn, Y. Yamakawa
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Abstract

This paper presents a new method of image processing for the line tracing task, which is one of the simple and fundamental tasks that has been applied to an unmanned system, utilizing multiple regions of interest to draw information from the entire image which was discarded in traditional image processing method for more accurate and flexible line trace. This new method divides the acquired image by machine vision into 3 regions: feedback region, prediction region, and inspection region. And different process was applied to each region to acquire parameters depending on the characteristics of each region that can enhance line tracing performance. In this paper, parameters of the new method are applied to the proportional control method and implemented to the robot arm and the camera and evaluated with the basic proportional control by comparing adaptability to a sharp curve. Consequently, the new method provided more adaptability in line tracing compared to the traditional single region of interest method.
充分利用单幅图像特征的多个感兴趣的区域线跟踪
本文提出了一种新的图像处理方法,利用多个感兴趣区域从整个图像中提取信息,以获得更精确和灵活的线条跟踪,这是无人系统中应用的简单而基本的任务之一。该方法将机器视觉获取的图像划分为3个区域:反馈区、预测区和检测区。根据每个区域的特点,对每个区域采用不同的处理方法获取参数,以提高直线跟踪性能。本文将新方法的参数应用到比例控制方法中,并将其应用到机器人手臂和相机上,并通过比较对锐曲线的适应性来与基本比例控制进行评价。因此,与传统的单一感兴趣区域方法相比,该方法在直线跟踪方面具有更强的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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