Name
Abstract | ||
|---|---|---|
The use of camera as a biometric sensor is desirable due to its ubiquity and low cost, especially for mobile devices. Palm print is an effective modality in such cases due to its discrimination power, ease of presentation and the scale and size of texture for capture by commodity cameras. However, the unconstrained nature of pose and lighting introduces several challenges in the recognition process. Even minor changes in pose of the palm can induce significant changes in the visibility of the lines. We turn this property to our advantage by capturing a short video, where the natural palm motion induces minor pose variations, providing additional texture information. We propose a method to register multiple frames of the video without requiring correspondence, while being efficient. Experimental results on a set of different 100 palms show that the use of multiple frames reduces the error rate from 12.75% to 4.7%. We also propose a method for detection of poor quality samples due to specularities and motion blur, which further reduces the EER to 1.8%. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.334 | ICPR |
Keywords | Field | DocType |
discrimination power,palm print,natural palm motion,multiple frame,additional texture information,commodity camera,palmprint recognition,short video,minor change,biometric sensor,motion blur,image recognition,error rate,feature extraction,lighting,image resolution,accuracy,pixel,mobile device,robustness | Computer vision,Visibility,Pattern recognition,Palm print,Computer science,Word error rate,Motion blur,Feature extraction,Robustness (computer science),Pixel,Artificial intelligence,Biometrics | Conference |
Citations | PageRank | References |
1 | 0.35 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chhaya Methani | 1 | 1 | 0.69 |
| Anoop M. Namboodiri | 2 | 255 | 26.36 |