CDIS: Circle Density Based Iris Segmentation

  • Anand Gupta
  • Anita Kumari
  • Boris Kundu
  • Isha Agarwal
Part of the Communications in Computer and Information Science book series (CCIS, volume 40)


Biometrics is an automated approach of measuring and analysing physical and behavioural characteristics for identity verification. The stability of the Iris texture makes it a robust biometric tool for security and authentication purposes. Reliable Segmentation of Iris is a necessary precondition as an error at this stage will propagate into later stages and requires proper segmentation of non-ideal images having noises like eyelashes, etc. Iris Segmentation work has been done earlier but we feel it lacks in detecting iris in low contrast images, removal of specular reflections, eyelids and eyelashes. Hence, it motivates us to enhance the said parameters. Thus, we advocate a new approach CDIS for Iris segmentation along with new algorithms for removal of eyelashes, eyelids and specular reflections and pupil segmentation. The results obtained have been presented using GAR vs. FAR graphs at the end and have been compared with prior works related to segmentation of iris.


Non Ideal Iris segmentation Circular Hough filter Sobel filter CASIA Eyelash Removal Specular Reflections Pupil Segmentation Canny Edge Eyelid Detection Eyelid Removal Non-ideal iris images 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anand Gupta
    • 1
  • Anita Kumari
    • 1
  • Boris Kundu
    • 1
  • Isha Agarwal
    • 1
  1. 1.Department of Information Technology, Netaji Subhas Institute of TechnologyDelhi UniversityNew DelhiIndia

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