Gradient-based edge detection of songket motifs

Nursuriati Jamil, Tengku Mohd Tengku Sembok

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    This paper discussed the effectiveness of several popular gradient-based edge detection techniques when applied on binary images of songket motifs. Five edge detector algorithms that is Roberts, Sobel, Prewitt, Laplacian of Gaussian and Canny are applied to twenty-five Malaysian traditional songket motifs. These scanned motif images are initially preprocessed to remove noise using several morphological operations. Other than noise removal, binarization of color images are also done to produce binary images. To determine the performance of the edge detectors, the results are evaluated by five human subjects based on several pre-conceived criteria.

    Original languageEnglish
    Pages (from-to)456-467
    Number of pages12
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2911
    Publication statusPublished - 2003

    Fingerprint

    Binary images
    Binary Image
    Edge Detection
    Edge detection
    Noise
    Detector
    Gradient
    Detectors
    Morphological Operations
    Binarization
    Noise Removal
    Color Image
    Color
    Human

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science
    • Engineering(all)

    Cite this

    Gradient-based edge detection of songket motifs. / Jamil, Nursuriati; Sembok, Tengku Mohd Tengku.

    In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2911, 2003, p. 456-467.

    Research output: Contribution to journalArticle

    @article{45ea046ef70841d7850600572d4c58f0,
    title = "Gradient-based edge detection of songket motifs",
    abstract = "This paper discussed the effectiveness of several popular gradient-based edge detection techniques when applied on binary images of songket motifs. Five edge detector algorithms that is Roberts, Sobel, Prewitt, Laplacian of Gaussian and Canny are applied to twenty-five Malaysian traditional songket motifs. These scanned motif images are initially preprocessed to remove noise using several morphological operations. Other than noise removal, binarization of color images are also done to produce binary images. To determine the performance of the edge detectors, the results are evaluated by five human subjects based on several pre-conceived criteria.",
    author = "Nursuriati Jamil and Sembok, {Tengku Mohd Tengku}",
    year = "2003",
    language = "English",
    volume = "2911",
    pages = "456--467",
    journal = "Lecture Notes in Computer Science",
    issn = "0302-9743",
    publisher = "Springer Verlag",

    }

    TY - JOUR

    T1 - Gradient-based edge detection of songket motifs

    AU - Jamil, Nursuriati

    AU - Sembok, Tengku Mohd Tengku

    PY - 2003

    Y1 - 2003

    N2 - This paper discussed the effectiveness of several popular gradient-based edge detection techniques when applied on binary images of songket motifs. Five edge detector algorithms that is Roberts, Sobel, Prewitt, Laplacian of Gaussian and Canny are applied to twenty-five Malaysian traditional songket motifs. These scanned motif images are initially preprocessed to remove noise using several morphological operations. Other than noise removal, binarization of color images are also done to produce binary images. To determine the performance of the edge detectors, the results are evaluated by five human subjects based on several pre-conceived criteria.

    AB - This paper discussed the effectiveness of several popular gradient-based edge detection techniques when applied on binary images of songket motifs. Five edge detector algorithms that is Roberts, Sobel, Prewitt, Laplacian of Gaussian and Canny are applied to twenty-five Malaysian traditional songket motifs. These scanned motif images are initially preprocessed to remove noise using several morphological operations. Other than noise removal, binarization of color images are also done to produce binary images. To determine the performance of the edge detectors, the results are evaluated by five human subjects based on several pre-conceived criteria.

    UR - http://www.scopus.com/inward/record.url?scp=0348216514&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=0348216514&partnerID=8YFLogxK

    M3 - Article

    AN - SCOPUS:0348216514

    VL - 2911

    SP - 456

    EP - 467

    JO - Lecture Notes in Computer Science

    JF - Lecture Notes in Computer Science

    SN - 0302-9743

    ER -