Towards an efficient Iris Recognition System on Embedded Devices
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Abstract (arXiv)
Iris Recognition (IR) is one of the market's most reliable and accurate biometric systems. Today, it is challenging to build NIR-capturing devices under the premise of hardware price reduction. Commercial NIR sensors are protected from modification. The process of building a new device is not trivial because it is required to start from scratch with the process of capturing images with quality, calibrating operational distances, and building lightweight software such as eyes/iris detectors and segmentation sub-systems. In light of such challenges, this work aims to develop and implement iris recognition software in an embedding system and calibrate NIR in a contactless binocular setup. We evaluate and contrast speed versus performance obtained with two embedded computers and infrared cameras. Further, a lightweight segmenter sub-system called "Unet_xxs" is proposed, which can be used for iris semantic segmentation under restricted memory resources.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 11 of its 51 references that are in the map. First posted on arXiv 24 Oct 2022.
Builds on
11 of 51 references.
References · 11
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2014DenseNet: Implementing Efficient ConvNet Descriptor Pyramidscited by 66
- 2016Discriminative Correlation Filter with Channel and Spatial Reliabilitycited by 45
- 2018Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognitioncited by 24
- 2019CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentationcited by 13
- 2019DeepIris: Iris Recognition Using A Deep Learning Approachcited by 8
- 2020SIP-SegNet: A Deep Convolutional Encoder-Decoder Network for Joint Semantic Segmentation and Extraction of Sclera, Iris and Pupil based on Periocular Region Suppressioncited by 8
- 2020On Benchmarking Iris Recognition within a Head-mounted Display for AR/VR Applicationcited by 8
- 2020Open Source Iris Recognition Hardware and Software with Presentation Attack Detectioncited by 7
- 2021Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effectscited by 6
- 2021Selfie Periocular Verification using an Efficient Super-Resolution Approachcited by 3
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.