Ear biometrics, the use of the unique physical characteristics of the ear for identification purposes, has gained increasing attention in recent years due to its high level of accuracy and stability. However, extracting the biometric features of the ear from images can be challenging due to variations in ear shape and size across different populations. This study proposes a new approach for ear biometric identification using Gabor filters and Canny edge detection. Gabor filters are a type of wavelet that can be used to extract texture and orientation information from images, while Canny edge detection is a widely used edge detection algorithm that can accurately identify object boundaries. Our experiments on a small dataset of ear images show that our proposed method gives great results of accuracy and robustness. The results of our study demonstrate the potential of Gabor filters and Canny edge detection for improving the performance of ear biometric systems.
|Title of host publication
|2023 International Seminar on Intelligent Technology and Its Applications
|Subtitle of host publication
|Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2023
|24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023 - Hybrid, Surabaya, Indonesia
Duration: 26 Jul 2023 → 27 Jul 2023
|2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
|24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
|26/07/23 → 27/07/23
- Canny Edge
- Gabor filter