Advertisement

Grain Size Measurement of Crystalline Products Using Maximum Difference Method

  • Leena Lepistö
  • Iivari Kunttu
  • Matti Lähdeniemi
  • Tero Tähti
  • Juha Nurmi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

Texture analysis methods are widely used in various monitoring and measurement tasks in machine vision solutions. In this paper we present a novel method for the determination of grain size distributions in the manufacturing processes of crystalline products. Our method, maximum difference histogram (MDH), is based on statistical gray level differences in the texture images. Using this method, it is possible to estimate the grain size distributions in the images. It is also possible to monitor the average grain sizes in the image series acquired during the crystallization process. This is carried out by determining the center of gravity (CoG) of the distribution represented by MDH. Experimental results obtained from images acquired from a carbohydrate crystallization process reveal that the proposed method is useful in in-line grain size measurement tasks.

Keywords

Gray Level Grain Size Distribution Texture Analysis Crystalline Product Crystal Size Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Haralick, R.M., Shanmugam, K., Dinstein, L.: Textural Features for Image Classification. IEEE Transactions on Systems, Man, and Cybernetics 3, 610–621 (1973)CrossRefGoogle Scholar
  2. 2.
    Laitinen, N., Antikainen, O., Yliruusi, J.: Does a powder surface contain all necessary information for particle size distribution analysis? European Journal of Pharmaceutical Sciences 17, 217–227 (2002)CrossRefGoogle Scholar
  3. 3.
    Laitinen, N., Rantanen, J., Antikainen, O., Yliruusi, J.: New perspectives for visual characterization of pharmaceutical solids. Journal of Pharmaceutical Sciences 93, 165–176 (2004)CrossRefGoogle Scholar
  4. 4.
    Lepistö, L., Kunttu, I., Autio, J., Visa, A.: Classification Method for Colored Natural Textures Using Gabor Filtering. In: Proceedings of 12th International Conference on Image Analysis and Processing, pp. 397–401 (2003)Google Scholar
  5. 5.
    Lepistö, L., Kunttu, I., Autio, J., Visa, A.: Rock image retrieval and classification based on granularity. In: Proceedings of 5th International Workshop on Image Analysis for Multimedia Interactive Services (2004)Google Scholar
  6. 6.
    Pietikäinen, M., Ojala, T., Silven, O.: Approaches to texture-based classification, segmentation and surface inspection. In: Chen, C.H., Pau, L.F., Wang, P.S.P. (eds.) Handbook of Pattern Recognition and Computer Vision, 2nd edn., pp. 711–736. World Scientific, Singapore (1998)Google Scholar
  7. 7.
    Qu, H., Louhi-Kultanen, M., Kallas, J.: In-line image analysis on the effects of additives in batch cooling crystallization. Journal of Crystal Growth 289, 286–294 (2006)CrossRefGoogle Scholar
  8. 8.
    Rao, A.R., Lohse, G.L.: Towards a texture naming system: identifying relevant dimensions of texture. In: Proceedings of IEEE Conference on Visualization, San Jose, California, pp. 270–227 (1993)Google Scholar
  9. 9.
    Tüceryan, M., Jain, A.K.: Texture Analysis. In: Chen, C.H., Pau, L.F., Wang, P.S.P. (eds.) Handbook of Pattern Recognition and Computer Vision, pp. 235–276. World Scientific, Singapore (1993)Google Scholar
  10. 10.
    Weszka, J.S., Dyer, C.R., Rosenfeld, A.: A Comparative Study of Texture Measures for Terrain Classification. IEEE Transactions on Systems, Man, and Cybernetics 6, 269–285 (1976)zbMATHGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Leena Lepistö
    • 1
  • Iivari Kunttu
    • 1
  • Matti Lähdeniemi
    • 1
  • Tero Tähti
    • 2
  • Juha Nurmi
    • 2
  1. 1.Satakunta University of Applied Sciences, Faculty of Technology and Maritime Management, Tekniikantie 2, FI-28600 PoriFinland
  2. 2.Danisco Texturants & Sweeteners, Innovation & Technology, Sokeritehtaantie 20, FI-02460 KantvikFinland

Personalised recommendations