TY - GEN
T1 - Robust iris segmentation through parameterization of the chan-vese algorithm
AU - Mabuza-Hocquet, Gugulethu
AU - Nelwamondo, Fulufhelo
AU - Marwala, Tshilidzi
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - The performance of an iris recognition system relies on automated processes from the segmentation stage to the matching stage. Each stage has traditional algorithms used successfully over the years. The drawback is that these algorithms assume that the pupil-iris boundaries are perfect circles sharing the same center, hence only use circle fitting methods for segmentation. The side effect posed by the traditional rubber sheet model used for normalization is; one cannot work backwards to place the discriminative features on the original image. This paper proposes a different approach to each stage using algorithms different from the traditional ones to address the above issues. Bresenham’s circle algorithm to locate and compute pupil-iris boundaries. Chan-Vese algorithm with pre-defined initial contour and curve evolution parameters for accurate segmentation. Preprocessing techniques to enhance and detect iris features for extraction. Labeling features of strongest pixel connectivity and using Harris algorithm for feature extraction and matching.
AB - The performance of an iris recognition system relies on automated processes from the segmentation stage to the matching stage. Each stage has traditional algorithms used successfully over the years. The drawback is that these algorithms assume that the pupil-iris boundaries are perfect circles sharing the same center, hence only use circle fitting methods for segmentation. The side effect posed by the traditional rubber sheet model used for normalization is; one cannot work backwards to place the discriminative features on the original image. This paper proposes a different approach to each stage using algorithms different from the traditional ones to address the above issues. Bresenham’s circle algorithm to locate and compute pupil-iris boundaries. Chan-Vese algorithm with pre-defined initial contour and curve evolution parameters for accurate segmentation. Preprocessing techniques to enhance and detect iris features for extraction. Labeling features of strongest pixel connectivity and using Harris algorithm for feature extraction and matching.
KW - Chan-Vese algorithm
KW - Feature matching
KW - Harris corner detector
KW - Iris segmentation
KW - Sobel edge detector
UR - http://www.scopus.com/inward/record.url?scp=84955503476&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24584-3_17
DO - 10.1007/978-3-319-24584-3_17
M3 - Conference contribution
AN - SCOPUS:84955503476
SN - 9783319245829
T3 - Lecture Notes in Electrical Engineering
SP - 183
EP - 194
BT - Advanced Computer and Communication Engineering Technology - Proceedings of ICOCOE 2015
A2 - Sulaiman, Hamzah Asyrani
A2 - Othman, Mohd Azlishah
A2 - Othman, Mohd Fairuz Iskandar
A2 - Rahim, Yahaya Abd
A2 - Pee, Naim Che
PB - Springer Verlag
T2 - 2nd International Conference on Communication and Computer Engineering, ICOCOE 2015
Y2 - 9 June 2015 through 11 June 2015
ER -