基于-分割算法的磨损颗粒图像分割

IF 1.5 Q3 ENGINEERING, MECHANICAL
Hong Liu, Haijun Wei, Lidui Wei, Jing-ming Li, Zhiyuan Yang
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引用次数: 5

摘要

本研究旨在利用JSEG算法对磨损颗粒图像进行分割。磨损颗粒提供了机械部件之间发生磨损过程的详细信息。图像的自动分割是智能分类系统的关键。本研究考察了该算法能否用于粒子图像分割。已经测试了不同的尺度。与传统的阈值分割和边缘检测器相比较,JSEG算法取得了较好的效果。它提供了相对较高的精度,可用于彩色图像代替灰度图像,计算复杂度低。结果表明,JSEG方法适合于图像磨损颗粒的分割,可在磨损颗粒识别系统中实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Segmentation of Wear Particles Images Using -Segmentation Algorithm
This study aims to use a JSEG algorithm to segment the wear particle’s image. Wear particles provide detailed information about the wear processes taking place between mechanical components. Autosegmentation of their images is key to intelligent classification system. This study examined whether this algorithm can be used in particles’ image segmentation. Different scales have been tested. Compared with traditional thresholding along with edge detector, the JSEG algorithm showed promising result. It offers a relatively higher accuracy and can be used on color image instead of gray image with little computing complexity. A conclusion can be drawn that the JSEG method is suited for imaged wear particle segmentation and can be put into practical use in wear particle’s identification system.
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来源期刊
Advances in Tribology
Advances in Tribology ENGINEERING, MECHANICAL-
CiteScore
5.00
自引率
0.00%
发文量
1
审稿时长
13 weeks
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