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[A method of iris image quality evaluation]
Hamit Murat1, Dawei Mao, Qinye Tong
1College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhaou 310027, China.
Summary
This study introduces an iris image quality evaluation method to identify high-quality iris images for computer recognition. The method effectively distinguishes usable images from those degraded by common issues like distortion and occlusion.
Area of Science:
- Computer Vision
- Biometrics
- Image Processing
Context:
- Iris recognition systems rely heavily on the quality of iris images.
- Poor image quality can lead to significant performance degradation in automated systems.
- Common image artifacts include pupil distortion, blurred boundaries, non-concentric circles, and occlusions from eyelids or eyelashes.
Purpose:
- To develop and evaluate a method for assessing iris image quality.
- To differentiate between acceptable and unacceptable iris images for recognition algorithms.
- To address common sources of image degradation in iris datasets.
Summary:
- A novel iris image quality evaluation method was proposed.
- The method identifies and quantifies image degradations such as distortion, blur, concentricity issues, and occlusions.
- Experimental results demonstrated the effectiveness of the proposed method in distinguishing good quality iris images from poor quality ones.
Impact:
- Improved accuracy and reliability of iris computer recognition systems.
- Reduced failure rates in iris matching due to poor image quality.
- Provides a crucial pre-processing step for robust iris biometrics.
