Determinations of bubble size distribution of foam-fibre mixture using circular hough transform

Timo Lappalainen, Jani Lehmonen

    Research output: Contribution to journalArticleScientificpeer-review

    44 Citations (Scopus)


    The aim of our work is to broaden the current knowledge of foam-fibre systems. This article focuses on the determination of the bubble size distribution (BSD) of foam containing cellulose fibres. It is well known that BSD has a powerful effect on a wide range of foam properties. The Circular Hough Transform was used in this study as the pattern recognition algorithm, in conjunction with a non-biased rule for sampling partially visible bubbles in an image. This algorithm is suitable for wet foams with almost spherical bubbles. We used a cuvette, with an internal diameter of 1.6 mm, for foam collection. We showed that images of the foam must be acquired within 30 s of collection of the foam sample and that bubbles with a radius larger than 25 µm can be recognised with this technique. The number of images needed to estimate the BSD of wet foam was four i.e. the diameters of 400-800 bubbles per trial point were measured. The Sauter mean radius r[3,2] was used for characterising the BSD of foam. We tested our method using several sets of images. Quantitative determination of the BSD of foam-fibre mixture is possible using the measurement and image analysis method developed in this study. This method can also be used to study foams created using different combinations of surfactants, fibres and additives.
    Original languageEnglish
    Pages (from-to)930-939
    Number of pages9
    JournalNordic Pulp and Paper Research Journal
    Issue number5
    Publication statusPublished - 2012
    MoE publication typeA1 Journal article-refereed


    • bubble size distribution
    • aqueous foam
    • foam-fibre mixture
    • circular hough transform
    • sodium dodecyl sulphate


    Dive into the research topics of 'Determinations of bubble size distribution of foam-fibre mixture using circular hough transform'. Together they form a unique fingerprint.

    Cite this