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April 7, 2026IET Information SecurityOpen Access

Fusion of Siamese Network‐Based Sclera and Iris Detection: A Multimodal Biometrics Approach Using a Sclera Detection Tracing Algorithm

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Authors

JAJide Kehinde AdeniyiTATunde Taiwo AdeniyiSASunday Adeola Ajagbe

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Overview

Demonstrates improved sclera and iris detection using a new fusion biometrics approach, suggesting enhanced security applications.

Key Points

  • The research aims to enhance the accuracy of sclera and iris detection for biometric systems.
  • Utilized a sclera detection tracing (SDT) approach with circular Hough transform for segmentation.
  • Employed discrete wavelet transform (DWT) to fuse local binary features of iris and sclera.
  • Implemented a Siamese network for classification and comparison of unimodal and bimodal systems.
  • Achieved a performance score of 98.5% for the fusion of sclera and iris biometrics.
  • Sclera detection algorithm outperformed segmentation by convolutional neural network (CNN).

Cite This Study

Adeniyi et al. (2026) studied this question.

synapsesocial.com/papers/69d49f6bb33cc4c35a227cd2https://doi.org/10.1049/ise2/5569382
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