A Case Study on Multi-instance Finger Knuckle Print Score and Decision Level Fusions

نویسندگان

  • Harbi AlMahafzah
  • Mohammad Imran
چکیده

Abstract—This paper proposed the use of multi-instance as a means to improve the performance of Finger Knuckle Print (FKP) verification. A log-This paper proposed the use of multi-instance as a means to improve the performance of Finger Knuckle Print (FKP) verification. A logGabor filter has been used to extract the image local orientation information, and represent the FKP features. Experiments are performed using the DZhang FKP database, which consists of 7,920 images. The influence on biometric performance using Decision and Score Level Fusions has been demonstrated in this paper. Results indicate that the Multi-instance verification approach at Score Level (Max Rule) and Decision Level (OR Rule) outperforms higher performance than using any single instance. Whereas at Score Level (Min Rule) and Decision Level (AND Rule) does not have performance improvement.

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تاریخ انتشار 2012