Pre-processing of Froth Image of Coal Flotation Based on Weighted Fuzzy C-Mean Clustering by One-Dimensional Histogram

Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogram can classify accurately pixels of coal flotation froth images into three kinds such as bubble vertex, the bubble surface and the background to increase the contrast of bubble edge and background, accurately positioning the bubbl...

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Published in:2012 International Conference on Computing, Measurement, Control and Sensor Network pp. 396 - 400
Main Authors: Tian Mu-Ling, Yang Jie-Ming
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2012
Subjects:
Clustering algorithms
Coal
coal flotation
de-noising
Filtering
Histograms
Image reconstruction
Image segmentation
morphological reconstruction
Noise reduction
opening and closing filtering
Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogra
ISBN:1467320331, 9781467320337
Online Access:Get full text
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Abstract Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogram can classify accurately pixels of coal flotation froth images into three kinds such as bubble vertex, the bubble surface and the background to increase the contrast of bubble edge and background, accurately positioning the bubble region for its fast convergence speed, real-time characteristics. After de-noised based on morphological filtering method of reconstruction opening and closing, clustered image can not only remove noises but retain more image detail and reflect accurately the true image information. So over-segmentation and under-segmentation will be avoided so as to be segmented more accurate when image clustered by these algorithms is processed using watershed segmentation based tags.
AbstractList Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogram can classify accurately pixels of coal flotation froth images into three kinds such as bubble vertex, the bubble surface and the background to increase the contrast of bubble edge and background, accurately positioning the bubble region for its fast convergence speed, real-time characteristics. After de-noised based on morphological filtering method of reconstruction opening and closing, clustered image can not only remove noises but retain more image detail and reflect accurately the true image information. So over-segmentation and under-segmentation will be avoided so as to be segmented more accurate when image clustered by these algorithms is processed using watershed segmentation based tags.
Author Tian Mu-Ling
Yang Jie-Ming
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  surname: Yang Jie-Ming
  fullname: Yang Jie-Ming
  email: Yangjieming@tyut.edu.cn
  organization: Inst. of Mechatron. Eng., Taiyuan Univ. of Technol., Taiyuan, China
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Snippet Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogram can classify accurately pixels of coal flotation froth images into three kinds such as...
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StartPage 396
SubjectTerms Clustering algorithms
Coal
coal flotation
de-noising
Filtering
Histograms
Image reconstruction
Image segmentation
morphological reconstruction
Noise reduction
opening and closing filtering
Weighted Fuzzy C-Mean clustering algorithm by one-dimensional histogra
Title Pre-processing of Froth Image of Coal Flotation Based on Weighted Fuzzy C-Mean Clustering by One-Dimensional Histogram
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