Effective background subtraction algorithm for food inspection using a low-cost near infrared camera

Paulius Tumas, A. Serackis
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引用次数: 4

Abstract

Computer vision-based image analysis is one of the most widely used food quality tool in food industry. It allows to perform the non-contact and low-cost measurements of inspected object's surface and color. The aim of investigation presented in this paper is to propose an effective algorithm for background subtraction on multi-spectral images. Paper presents the application of multi-spectral image analysis approach using near infrared low cost camera and four different key wavelengths for controlled LED illumination. The performance of the background subtraction algorithm was measured by comparing the variation of estimated area of the food samples in the foreground. An experimental tests showed, that the best performance of background subtraction is received using infrared LED illumination with key wavelength of 940nm using all methods selected for comparison.
低成本近红外相机食品检测的有效背景减法算法
基于计算机视觉的图像分析是食品工业中应用最广泛的食品质量分析工具之一。它允许执行非接触式和低成本的测量被检查对象的表面和颜色。本文的研究目的是提出一种有效的多光谱图像背景减除算法。本文介绍了近红外低成本相机和四个不同关键波长的多光谱图像分析方法在受控LED照明中的应用。通过比较前景中食物样本估计面积的变化来衡量背景减法算法的性能。实验测试表明,在所有选择的对比方法中,关键波长为940nm的红外LED照明获得的背景减法效果最好。
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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