IDEAS home Printed from https://ideas.repec.org/a/igg/jse000/v10y2019i2p49-61.html
   My bibliography  Save this article

2D Shape Recognition and Retrieval Using Shape Contour Based on the 8-Neighborhood Patterns Matching Technique

Author

Listed:
  • Muzameel Ahmed

    (Jain University, Bengaluru, India)

  • Manjunath Aradhya

    (JSS Science and Technology University, Mysore, India)

Abstract

A technique for 2D shape recognition and retrieval is proposed. The proposed technique is based on the 8-neighborhood pattern which represents each point or pixel on the contour of the shape. These patterns are used as a framework in matching the shape of the object. The recognition and retrieval process are conducted by traversing through the contour of the shape and analyzes each point on the contour by considering the 8-neighborhood pattern. The 8-neighborhood patterns are assigned unique labels which are computed on their every occurrence during contour traversal. The cost of the best match between the shapes is evaluated by comparing the hit value obtained by the contour traversal of the shapes to be matched. The recognition and retrieval are carried out using the leave-one-out strategy and standard bull eye score, respectively. The proposed method is experimented on the MPEG-7 data set and the chicken piece data set. The results both for recognition and retrieval outperform most of the previously proposed methods.

Suggested Citation

  • Muzameel Ahmed & Manjunath Aradhya, 2019. "2D Shape Recognition and Retrieval Using Shape Contour Based on the 8-Neighborhood Patterns Matching Technique," International Journal of Synthetic Emotions (IJSE), IGI Global, vol. 10(2), pages 49-61, July.
  • Handle: RePEc:igg:jse000:v:10:y:2019:i:2:p:49-61
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSE.2019070104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jse000:v:10:y:2019:i:2:p:49-61. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.