scholarly journals The Segmentation of Wear Particles Images UsingJ-Segmentation Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Liu ◽  
Haijun Wei ◽  
Lidui Wei ◽  
Jingming Li ◽  
Zhiyuan Yang

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.

2013 ◽  
Vol 770 ◽  
pp. 427-432 ◽  
Author(s):  
Jing Qiu Wang ◽  
Xiao Lei Wang

This paper provides a general overview on the developments and progress in the segmentation of ferrography images. The problems experienced with applying traditional image processing methods in the segmentation of wear particles, revealed that it is still a big challenge for intelligent ferrography. This has highlighted the need for combining the segmentation and clustering methods for performing ferrography image analysis. In this paper, some of the developments reported in the literature relating to progress made with wear particle image segmentation are reported and examined as a basis for establishing improved methods of ferrography image analysis.


2010 ◽  
Vol 36 (6) ◽  
pp. 807-816 ◽  
Author(s):  
Xiao-Dong YUE ◽  
Duo-Qian MIAO ◽  
Cai-Ming ZHONG

2009 ◽  
Vol 29 (8) ◽  
pp. 2074-2076
Author(s):  
Hua LI ◽  
Ming-xin ZHANG ◽  
Jing-long ZHENG

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