IDEAS home Printed from https://ideas.repec.org/a/igg/jaec00/v10y2019i2p8-18.html
   My bibliography  Save this article

Comparative Study on Feature Extractions for Ear Recognition: Comparative Study on Feature Extractions for Ear Recognition

Author

Listed:
  • Dayanand Bharat Gore

    (MGM Dr. G.Y. Pathrikar CS & IT Aurangabad, Aurangabad, India)

Abstract

Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioural traits. The problem of finding good biometric features and recognition methods has been researched extensively in recent years. This research considers the use of ears as a biometric for human recognition. In this article, basic feature extraction techniques are implemented such as Harris Feature, FAST Feature extraction and SURF Feature Extraction. All the images are taken from standard database and each image has different angles because of any criminal investigation, accident, or ATM machine camera taken different types of images. So, using different images feature extraction the research goes through these techniques to give the best result to the user.

Suggested Citation

  • Dayanand Bharat Gore, 2019. "Comparative Study on Feature Extractions for Ear Recognition: Comparative Study on Feature Extractions for Ear Recognition," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 10(2), pages 8-18, April.
    • Handle: RePEc:igg:jaec00:v:10:y:2019:i:2:p:8-18
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2019040102
    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:jaec00:v:10:y:2019:i:2:p:8-18. 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.