基于混合深度字典学习和弹性阈值的图像去噪方法

Guanlin Liu
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引用次数: 2

摘要

机器视觉在现代工业中的应用,使智能制造成为可能。目前电路板相关故障检测,如断线、缺焊点等问题频繁发生,人工识别速度慢,误检率高。针对这一问题,本研究提出了一种结合深度字典学习和弹性阈值的图像降噪处理方法,可以服务于计算机图像处理,从而大大提高印刷电路板的检测速度,最终服务于现代电子产品的加工生产。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Denoising Method Based on Hybrid Deep Dictionary Learning and Elastic Threshold
The application of machine vision in the modern industry makes intelligent manufacturing possible. At present, circuit board related fault detection, such as broken wires, missing solder joints, and other problems frequently occur, the manual recognition speed is slow and the false detection rate is high. In response to this problem, this research proposes an image noise reduction processing method that combines deep dictionary learning and elastic thresholds, which can serve computer image processing, thereby greatly improving the detection speed of printed circuit boards, and ultimately serving the processing and production of modern electronic products.
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