The Method of Flotation Froth Image Segmentation Based on Threshold Level Set


A novel flotation froth image segmentation based on threshold level set method is put forward in view of the problem of over-segmentation and under-segmentation which occurs when the existing method segmented the flotation froth images. Firstly, the proposed method adopts histogram equalization to improve the contrast of the image, and then chooses the upper threshold and lower threshold from grey value of histogram of the image equalization, and complete image segmentation using the level set method. In this paper, the model which integrates edge with region level set model is utilized, and the speed energy term is introduced to segment the target. Experimental results show that the proposed method has better segmentation results and higher segmentation efficiency on the images with under-segmentation and incorrect segmentation, and it is meaningful for ore dressing industrial.

Share and Cite:

Zhao, J. , Wang, H. , Zhang, L. and Wang, C. (2015) The Method of Flotation Froth Image Segmentation Based on Threshold Level Set. Advances in Molecular Imaging, 5, 38-48. doi: 10.4236/ami.2015.52004.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Vincent, L. and Soille, P. (1991) Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13, 583-598.
[2] Zhao, G.Q., Gu, Y.Y., et al. (2007) A Classification of Flotation Froth Based on Geometry. Mechatronics and Automation, Harbin, 2716-2720.
[3] Liu, J.P., Gui, W.H., Chen, Q., et al. (2013) An Unsupervised Method for Flotation Froth Image Segmentation Evaluation Base on Image Gray-Level Distribution. IEEE Control Conference (CCC), Xi’an, 4018-4022.
[4] Massinaei, M. (2014) Development of a New Algorithm for Segmentation of Flotation Froth Images. Minerals and Metallurgical Processing, 31, 66-72.
[5] Wirthgen, T., Lempe, G. and Zipser, S. (2012) Ulrich Grünhaupt Level-Set Based Infrared Image Segmentation for Automatic Veterinary Health Monitoring. Computer Vision and Graphics, 685-693.
[6] Wirthgen, T., Zipser, S., Franze, U., et al. (2011) Automatic Segmentation of Veterinary Infrared Images with the Active Shape Approach. Lecture Notes in Computer Science. Proceedings of 17th Scandinavian Conference on Image Analysis, 435-446.
[7] Lim, P.H., Bagci, U., Aras, O., et al. (2012) A Novel Spinal Vertebrae Segmentation Framework Combining Geometric Flow and Shape Prior with Level Set Method. IEEE International Symposium on Biomedical Imaging, Barcelona, 1703-1706.
[8] Li, C.M., Xu, C.Y., Gui, C.F., et al. (2005) Level Set Evolution without Re-Initialization: A New Variational Formulation. IEEE Conference on Computer Vision and Pattern Recognition, San Diego, 430-436.
[9] Paragios, N. and Deriche, R. (2002) Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation. International Journal of Computer Vision, 46, 223-247.
[10] Caselles, V., Kimmel, R. and Sapiro, G. (1997) Geodesic Active Contours. International Journal of Computer Vision, 22, 61-79.
[11] Vese, L. and Chan, T. (2002) A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model. International Journal of Computer Vision, 50, 271-293.
[12] Sagiv, C., Sochen, N.A. and Zeevi, Y.Y. (2006) Integrated Active Contours for Texture Segmentation. IEEE Transactions on Image Processing, 15, 1633-1646.
[13] Qiao, J.M. (2011) The Improvement of Image Segmentation Based on GAC Model and C-V Model. Harbin Institute of Technology, Harbin.
[14] Khalifa, F., El-Baz, A., Ouseph, R., et al. (2010) Shape-Appearance Guided Level-Set Deformable Model for Image Segmentation. IEEE International Conference on Pattern Recognition, Istanbul, 4581-4584.
[15] Chung, D.H. and Sapiro, G. (2000) On the Level Lines and Geometry of Vector-Valued Image. IEEE, Signal Processing Letters, 7, 241-243.
[16] Sapiro, G. (2001) Geometric Partial Differential Equations and Image Analysis. Cambridge University Press, Cambridge.
[17] Wang, B. (2010) The Improvement of Image Segmentation Based on Level Set Method. Xidian University, Xi’an.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.