![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
A Novel Approach to Palmprint Classification using Orthogonal Moments
Subscribe/Renew Journal
Biometrics plays an important role in personal identification and it is becoming increasingly popular today. Palmprint matching is considered in this paper for effective identification of persons. Palmprint matching is performed based on Zernike moments feature descriptors and the classification using Modified Adaboost classifiers. Since, Zernike moments have the property of geometrical invariance, they are superior in image representative capability. From the experimental results, it has been observed that Zernike moments achieve superior performance than the other well-known moments.
Keywords
Biometrics, Palmprint, Feature Extraction, Zernike Moments, Adaboost.
User
Subscription
Login to verify subscription
Font Size
Information
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 185
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 3