Papers Iris Segmentation
“Iris Segmentation” 태그가 달린 논문 38편 · 필터 해제
Privacy-Preserving Iris Recognition: Performance Challenges and Outlook
Iris-based biometric identification is increasingly recognized for its significant accuracy and long-term stability compared to other biometric modalities such as fingerprints or facial features. However, all biometric m…
Iris SegmentationPost-Mortem Human Iris Segmentation Analysis with Deep Learning
Iris recognition is widely used in several fields such as mobile phones, financial transactions, identification cards, airport security, international border control, voter registration for living persons. However, the p…
Deep LearningImage SegmentationIris RecognitionIris Segmentation+2Normalized Validity Scores for DNNs in Regression based Eye Feature Extraction
We propose an improvement to the landmark validity loss. Landmark detection is widely used in head pose estimation, eyelid shape extraction, as well as pupil and iris segmentation. There are numerous additional applicati…
Head Pose EstimationIris SegmentationPose EstimationregressionIris-SAM: Iris Segmentation Using a Foundation Model
Iris segmentation is a critical component of an iris biometric system and it involves extracting the annular iris region from an ocular image. In this work, we develop a pixel-level iris segmentation model from a foundat…
Iris SegmentationmodelSegmentationArtificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation
Biometrics is the science of identifying an individual based on their intrinsic anatomical or behavioural characteristics, such as fingerprints, face, iris, gait, and voice. Iris recognition is one of the most successful…
Data AugmentationIris RecognitionIris SegmentationPupil Dilation+2Novel Deep Learning Framework For Bovine Iris Segmentation
Iris segmentation is the initial step to identify biometric of animals to establish a traceability system of livestock. In this study, we propose a novel deep learning framework for pixel-wise segmentation with minimum u…
DecoderDeep LearningIris SegmentationSegmentationExperimental analysis regarding the influence of iris segmentation on the recognition rate
In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will examine whether the segmentation accuracy,…
Iris SegmentationSegmentationSegmentation-free Direct Iris Localization Networks
This paper proposes an efficient iris localization method without using iris segmentation and circle fitting. Conventional iris localization methods first extract iris regions by using semantic segmentation methods such …
CPUDecoderIris RecognitionIris Segmentation+2A fast and accurate iris segmentation method using an LoG filter and its zero-crossings
This paper presents a hybrid approach to achieve iris localization based on a Laplacian of Gaussian (LoG) filter, region growing, and zero-crossings of the LoG filter. In the proposed method, an LoG filter with region gr…
Iris SegmentationSaliency-Guided Textured Contact Lens-Aware Iris Recognition
Iris recognition requires an adequate level of the iris texture being visible to perform a reliable matching. In case when a textured contact lens covers the iris, a false non-match is reported or a presentation attack i…
Iris RecognitionIris SegmentationKartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentation
Iris segmentation and localization in unconstrained environments is challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. To address this problem, we present a U-Net w…
BinarizationDomain AdaptationIris RecognitionIris Segmentation+1Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition
Iris recognition of living individuals is a mature biometric modality that has been adopted globally from governmental ID programs, border crossing, voter registration and de-duplication, to unlocking mobile phones. On t…
Deep LearningIris RecognitionIris SegmentationSegmentationDirect attacks using fake images in iris verification
In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied. A database of fake iris images has been created from real iris of the BioSec baseline database. Iris images are p…
Iris RecognitionIris SegmentationToward Accurate and Reliable Iris Segmentation Using Uncertainty Learning
Iris segmentation is a deterministic part of the iris recognition system. Unreliable segmentation of iris regions especially the limbic area is still the bottleneck problem, which impedes more accurate recognition. To ma…
Iris RecognitionIris SegmentationSegmentationMicro Stripes Analyses for Iris Presentation Attack Detection
Iris recognition systems are vulnerable to the presentation attacks, such as textured contact lenses or printed images. In this paper, we propose a lightweight framework to detect iris presentation attacks by extracting …
Iris RecognitionIris SegmentationAn approach to human iris recognition using quantitative analysis of image features and machine learning
The Iris pattern is a unique biological feature for each individual, making it a valuable and powerful tool for human identification. In this paper, an efficient framework for iris recognition is proposed in four steps. …
BIG-bench Machine LearningIris RecognitionIris SegmentationOpen Source Iris Recognition Hardware and Software with Presentation Attack Detection
This paper proposes the first known to us open source hardware and software iris recognition system with presentation attack detection (PAD), which can be easily assembled for about 75 USD using Raspberry Pi board and a …
Iris RecognitionIris SegmentationReconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT
Precise characterization and analysis of iris shape from Anterior Segment OCT (AS-OCT) are of great importance in facilitating diagnosis of angle-closure-related diseases. Existing methods focus solely on analyzing struc…
Iris SegmentationSurface ReconstructionIris segmentation techniques to recognize the behavior of a vigilant driver
In this paper, we clarify how to recognize different levels of vigilance for vehicle drivers. In order to avoid the classical problems of crisp logic, we preferred to employ a fuzzy logic-based system that depends on two…
Iris SegmentationPositionBoltzmann Exploration Expectation–Maximisation
We present a general method for fitting finite mixture models (FMM). Learning in a mixture model consists of finding the most likely cluster assignment for each data-point, as well as finding the parameters of the clus…
Iris Segmentation