稳健的大理石纹肉分割计算机视觉系统

Q4 Computer Science
G. F. C. Campos, J. L. Seixas, A. P. A. Barbon, A. S. Felinto, A. Bridi, Sylvio Barbon Junior
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引用次数: 3

摘要

在这项研究中,我们开发了一个鲁棒的自动计算机视觉系统,用于大理石纹肉分割。我们的方法可以在有外部环境光和人造光的不受控制的环境中使用不同质量的设备获得的图像来分割各种大理石肉样本中的肌肉脂肪;因此,专业人员可以在没有样品处理或设备方面的专业知识的情况下应用该方法,也不会中断正常程序,从而获得可靠的解决方案。提出了一种基于数据聚类和动态阈值分割的大理石纹分割方法。实验使用了两个数据集,包括41张背最长肌的82张图像,这些图像由不同的采样设备获得。实验结果表明,无论采用何种采集设备,计算机视觉系统都具有98%以上的准确率和低误报率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust computer vision system for marbling meat segmentation
In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment muscle fat in various marbled meat samples using images acquired with different quality devices in an uncontrolled environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of sample treatments or equipment, as well as without disruption to normal procedures, thereby obtaining a robust solution. The proposed approach for marbling segmentation is based on data clustering and dynamic thresholding. Experiments were performed using two datasets that comprised 82 images of 41 longissimus dorsi muscles acquired by different sampling devices. The experimental results showed that the computer vision system performed well with over 98% accuracy and a low number of false positives, regardless of the acquisition device employed.
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来源期刊
Electronic Letters on Computer Vision and Image Analysis
Electronic Letters on Computer Vision and Image Analysis Computer Science-Computer Vision and Pattern Recognition
CiteScore
2.50
自引率
0.00%
发文量
19
审稿时长
12 weeks
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