Summary of A Prior Embedding-driven Architecture For Long Distance Blind Iris Recognition, by Qi Xiong et al.
A Prior Embedding-Driven Architecture for Long Distance Blind Iris Recognition
by Qi Xiong, Xinman Zhang, Jun Shen
First submitted to arxiv on: 1 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is proposed to address the issue of decreased iris recognition rates caused by unknown degradation during long-distance iris recognition. The authors introduce a prior embedding-driven architecture for blind iris recognition, consisting of two components: Iris-PPRGAN, a blind iris image restoration network using Generative Adversarial Network (GAN) and DNN; and Insight-Iris, a robust iris classifier modified from InsightFace’s bottleneck module. The proposed method involves restoring low-quality blind iris images with Iris-PPRGAN and then recognizing the restored image via Insight-Iris. Experimental results on the CASIA-Iris-distance dataset show significant improvements over state-of-the-art methods, achieving a recognition rate of 90% for long-distance blind iris images, an increase of approximately ten percentage points. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to recognize someone’s eyes from far away, but they’re blurry or distorted. This can make it hard to identify people using iris recognition technology. Researchers have developed a new way to improve this process by restoring blurry eye images and then recognizing them more accurately. They created a special system that combines two parts: one to fix the blurry image and another to recognize the restored image. Tests on a large dataset showed that their method is much better than existing methods, achieving a recognition rate of 90% for blurry eye images taken from far away. |
Keywords
» Artificial intelligence » Embedding » Gan » Generative adversarial network
