Iris Recognition Using Scattering Transform and Textural Features
Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all biometric features, iris is known to possess a rich set of features. Different features have been used to perform iris recognition in the past. In this paper, two powerful sets of features are introduced to be used for iris recognition: scattering transform-based features and textural features. PCA is also applied on the extracted features to reduce the dimensionality of the feature vector while preserving most of the information of its initial value. Minimum distance classifier is used to perform template matching for each new test sample. The proposed scheme is tested on a well-known iris database, and showed promising results with the best accuracy rate of 99.2%.
Code (0)
등록된 구현이 없습니다.
Tasks
Iris RecognitionTemplate MatchingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations
Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris features and a wide spectrum of anomalies. Because of the rich texture of…
Image AugmentationRobust Iris Presentation Attack Detection Fusing 2D and 3D Information
Diversity and unpredictability of artifacts potentially presented to an iris sensor calls for presentation attack detection methods that are agnostic to specificity of presentation attack instruments. This paper proposes…
Iris RecognitionSpecificityScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges
Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy. However, precise detection remains a considerable chall…
EEGSeizure DetectionPalmprint Recognition Using Deep Scattering Convolutional Network
Palmprint recognition has drawn a lot of attention during the recent years. Many algorithms have been proposed for palmprint recognition in the past, majority of them being based on features extracted from the transform …
TranslationIris Recognition Based on SIFT Features
Biometric methods based on iris images are believed to allow very high accuracy, and there has been an explosion of interest in iris biometrics in recent years. In this paper, we use the Scale Invariant Feature Transform…
Iris Recognition