A FRAMEWORK TO DEVELOP INTELLIGENT SYSTEM FOR CAPTURING PRODUCT FEATURES USING OPEN CV TECHNIQUE

Yazid Saif, Y. Yusof, Maznah lliyas Ahmed, Zohaib khan Pathan, K. Latif, A. A. Kadir
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引用次数: 2

Abstract

This research aims to propose an innovative framework using ISO14649 standard to detect defects in manufactured shaped objects or geometric surfaces of non-linear products of the CNC machine. The significant importance in order to recognize the potential to improve industry product quality inspection and encourage the waste of timing machines and product rejection. Open Computer Vision (Open CV) offers a smart, non-contact measurement and cost-effective technique to fulfil the requirements. The framework depends on the new technique of Open CV, which includes two parts: an intelligent selection of work-piece capturing the image for a particular inspection of the planar interfaces such as the hole, rectangular, pocket one, and the symmetric lighting model comparison approach for measurement of defects in the matched images. The contribution of this study is to build a structure in the computer vision method with a convolution neural network that predicts the classification of the feature for better accuracy and emphasizes the significant characteristics of the image processing technique coupled with experimental data on demanding image datasets and quality inspection measures.
一个基于开放CV技术的智能产品特征捕获系统的开发框架
本研究旨在提出一种采用ISO14649标准的创新框架,用于数控机床加工成型物体或非线性产品几何表面的缺陷检测。重要的是要认识到潜力,以提高工业产品质量的检验和鼓励浪费的定时机器和产品的拒收。开放计算机视觉(Open CV)提供了一种智能,非接触式测量和经济高效的技术来满足要求。该框架基于Open CV新技术,该技术包括两部分:一是智能选择工件捕获图像,用于特定平面界面(如孔、矩形、口袋)的检测;二是对称照明模型比较方法,用于测量匹配图像中的缺陷。本研究的贡献在于利用卷积神经网络在计算机视觉方法中构建一种结构,该结构可以预测特征的分类以获得更好的准确性,并强调图像处理技术的重要特征,并结合要求苛刻的图像数据集和质量检测措施的实验数据。
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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