A multi-step method of partitioning the pixels of an image such that the partitions at one step are wholly nested inside the partitions of the next step is described, ie, we describe an agglomerative, hierarchical segmentation technique that uses texture information to perform the segmentation. The image is requantized using K-means clustering. Then, clusters are expanded using region growing and morphological processing. This provides the most detailed level of segmentation. The next coarser segmentation levels are obtained by steadily relaxing the inter-cluster distance between the clusters that is allowed by the morphological processing. Results are demonstrated on real-world images and swathes of Brodatz textures.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Nested partitions using texture segmentation


    Contributors:


    Publication date :

    2002-01-01


    Size :

    383859 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Nested Partitions Using Texture Segmentation

    Lakshmanan, V. / DeBrunner, V. E. / Rabin, R. et al. | British Library Conference Proceedings | 2002


    Energy Partitions and Image Segmentation

    Arbelaez, P. A. / Cohen, L. D. | British Library Online Contents | 2004


    Partial Partitions, Partial Connections and Connective Segmentation

    Ronse, C. | British Library Online Contents | 2008


    Dynamic texture segmentation

    Doretto, / Cremers, / Favaro, et al. | IEEE | 2003


    Dynamic Texture Segmentation

    Doretto, G. / Cremers, D. / Favaro, P. et al. | British Library Conference Proceedings | 2003