Skip to main navigation Skip to search Skip to main content

Multi-scale image segmentation using MSER

    • Woosuk University
    • University of California at Irvine

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    Recently several research works propose image segmentation algorithms using MSER. However they aim at segmenting out specific regions corresponding to user-defined objects. This paper proposes a novel algorithm based on MSER which segments natural images without user intervention and captures multi-scale structure. The algorithm collects MSERs and then partitions whole image plane by redrawing them in specific order. To denoise and smooth the region boundaries, hierarchical morphological operations are developed. To illustrate effectiveness of the algorithm's multi-scale structure, effects of various types of LOD control are shown for image stylization.

    Original languageEnglish
    Title of host publicationComputer Analysis of Images and Patterns - 15th International Conference, CAIP 2013, Proceedings
    Pages201-208
    Number of pages8
    EditionPART 2
    DOIs
    StatePublished - 2013
    Event15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013 - York, United Kingdom
    Duration: 2013.08.272013.08.29

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume8048 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013
    Country/TerritoryUnited Kingdom
    CityYork
    Period13.08.2713.08.29

    Keywords

    • image segmentation
    • image stylization
    • Multi-scale structure

    Quacquarelli Symonds(QS) Subject Topics

    • Computer Science & Information Systems

    Fingerprint

    Dive into the research topics of 'Multi-scale image segmentation using MSER'. Together they form a unique fingerprint.

    Cite this