A turning function based approach for foot outline classification

Asanka S. Rodrigo, Ravindra S. Goonetilleke

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Scopus citations

    Abstract

    This study introduces a turning function based technique to classify foot outlines. Foot scans from ten males and ten females were obtained using a laser scanner. The similarities among the different foot shapes were assessed based on the Euclidean distance between turning functions. Thereafter, average linkage clustering was used to classify the differing foot outlines. Two distinct shape groups emerged for both medial and lateral sides. The presence or absence of a medial bulge results in two clusters on the medial side. Similarly, a narrow lateral side with more concavity and a wider lateral side in the midfoot region are the two clusters for the lateral side. More males (60%) showed a bulge on the medial side. The group that belongs to the narrower lateral side were predominantly females (70%). These differences in the structure of the clusters were reflected in the lack of a correlation between the medial and lateral side clusters.

    Original languageBritish English
    Title of host publicationIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management
    Pages861-864
    Number of pages4
    DOIs
    StatePublished - 2009
    EventIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009 - Hong Kong, China
    Duration: 8 Dec 200911 Dec 2009

    Publication series

    NameIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management

    Conference

    ConferenceIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009
    Country/TerritoryChina
    CityHong Kong
    Period8/12/0911/12/09

    Keywords

    • Cluster
    • Foot outline
    • Foot shapes
    • Footwear
    • Turning function

    Fingerprint

    Dive into the research topics of 'A turning function based approach for foot outline classification'. Together they form a unique fingerprint.

    Cite this