Efficient Iris and Eyelids Detection from Facial Sketch Images

Authors

  • Tan Boonchuan Universiti Sains Malaysia
  • Samsul Setumin Universiti Sains Malaysia Universiti Teknologi MARA
  • Abduljalil Radman Universiti Sains Malaysia
  • Shahrel Azmin Suandi Universiti Sains Malaysia http://orcid.org/0000-0001-9980-7426

Abstract

In this paper, we propose a simple yet effective technique for an automatic iris and eyelids detection method for facial sketch images. Our system uses Circular Hough Transformation (CHT) algorithm for iris localization process and a low level grayscale analysis for eyelids contour segmentation procedure. We limit the input face for the system to facial sketch photos with frontal pose, illumination invariant, neutral expression and without occlusions. CUHK and IIIT-D sketch databases are used to acquire the experimental results. As to validate the proposed algorithm, experiments on ground truth for iris and eyelids segmentation, which are prepared at our lab, is conducted. The iris segmentation from the proposed method gives the best accuracy of 92.93 and 86.71 based on F-measure evaluation for IIIT-D and CUHK, respectively. For eyelids segmentation, on the other hand, the proposed algorithm achieves an average of 4 standard deviation which indicates the closeness of proposed method to ground truth.

Keywords

iris, eyelids, circular hough transform, sketch images

Author Biography

Shahrel Azmin Suandi, Universiti Sains Malaysia

I am currently an Associate Professor at School of EE. My research interest are face biometric, motion detection and recognition, intelligent video surveillance security.

Published

07-11-2018

Downloads

Download data is not yet available.