Flexible approach for Region of Interest creation for shape-based matching in vision system

Wee Teck Lim, M. Sulaiman, H. N. M. Shah
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引用次数: 9

Abstract

This research is regarding the application of a vision algorithm to monitor the operations of a system in order to control the decision making concerning jobs and work pieces recognition that are to be made during system operation in real time. This paper stress on the vision algorithm used which mainly focus on the shape matching properties of the product. The algorithm consists of two phases, the training phase and the recognition phase. The main focus of this paper is on the development of an adaptive training phase of the vision system, which is the creation of a flexible Region of Interest capability that is able to adapt to various type of applications and purposes depending on the users' requirements. The system was tested on a number of different images with various characteristics and properties to determine the reliability and accuracy of the system in respect to different conditions and combination of different training traits. This system can be applied in industrial sectors especially for process and quality control.
视觉系统中基于形状匹配的兴趣区域创建的灵活方法
本研究是关于应用视觉算法来监控系统的运行,以实时控制系统运行过程中有关作业和工件识别的决策。本文重点介绍了所使用的视觉算法,主要关注产品的形状匹配特性。该算法分为两个阶段:训练阶段和识别阶段。本文的主要重点是开发视觉系统的自适应训练阶段,即创建一个灵活的兴趣区域能力,能够根据用户的需求适应各种类型的应用和目的。该系统在具有不同特征和属性的多个不同图像上进行了测试,以确定系统在不同条件和不同训练特征组合下的可靠性和准确性。该系统可用于工业部门,特别是过程和质量控制。
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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