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On-Line Detection of Hami Big Jujubes' Size and Shape Based on Machine Vision

机译:基于机器视觉的哈密大枣大小和形状在线检测

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In this paper, we present a on-line machine vision system for Hami big jujubes¡¯ size and shape detection, which solved the problems such as fast processing the large amount of image information, improving system performance for real time dynamic image capture and processing capability, increasing precision of detection etc. Based on the application of Visual Basic 6.0 designed the user¡¯s interface. SOLIOS images gathering card linked with the CCD camera to collect image data, Which consisted united application ofMIL9.0 and VB on Auto-Detecting of the Hami bigjujubes¡¯ size and shape. With image processing control of Active Mil 9.0, comparison of the algorithm and verified, we can find the feature extraction to distinguish the rapid defects about the size and shape. During the image processing, many methods were used to identify the quality defects as soon as possible, such as application of wavelet denoising, threshold segmentation, mathematical morphology processing methods etc. A Hierarchical Clustering Analysis method was used to realize the recognition and to determine the classification £¬ which the recognition rate can research 83%.
机译:本文提出了一种用于哈密大枣大小和形状检测的在线机器视觉系统,解决了快速处理大量图像信息,提高实时动态图像捕捉和处理系统性能的问题。基于Visual Basic 6.0的应用程序设计了用户界面。 SOLIOS图像采集卡与CCD相机联动采集图像数据,由MIL9.0和VB联合应用在哈密大枣大小,形状的自动检测中。通过Active Mil 9.0的图像处理控制,算法的比较和验证,我们可以找到特征提取来区分大小和形状方面的快速缺陷。在图像处理过程中,采用小波去噪,阈值分割,数学形态学处理方法等多种方法尽早识别质量缺陷。采用层次聚类分析法实现识别并确定图像质量。识别率可以研究83%。

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