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Texture removal for adaptive level set based iris segmentation
2010
2010 IEEE International Conference on Image Processing
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Level set based active contour method has been proposed for iris segmentation in recent years, but it can not converge to iris contours in real applications because of its sensitivity to local gradient ...
Finally, the accurate segmentation is obtained by the robust adaptive level set method. ...
Finally, level set is adopted for iris segmentation. And a new convergency criterion and an adaptive parameter are proposed for improving the performance the traditional level set method. ...
doi:10.1109/icip.2010.5652941
dblp:conf/icip/ZhangST10
fatcat:dwt2o5zstjhqxajvmvuqq5tgwa
Survey on Iris Image Analysis
2017
Indian Journal of Science and Technology
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This paper primarily focuses on the survey of Iris camera for Iris acquisition, Methods adopted for iris segmentation, feature extraction, matching and public Iris database. ...
Iris segmentation and feature extraction are important steps in Iris recognition. ...
An iris segmentation algorithm is presented in 6 which is based on the local statistics of the texture region in the iris and is suited for segmenting poor quality iris images. ...
doi:10.17485/ijst/2017/v10i19/97455
fatcat:2xp2ayitkfbftcmuopulrychmm
An Algorithm of Eyelashes Detection for Iris Recognition
2016
International Journal of Security and Its Applications
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In order to reduce the eyelash influencing on iris recognition rate, an eyelashes detection algorithm is proposed based on adaptive threshold. ...
Based on the iris localization, gray morphological operation is used to accurately localize eyelids. ...
If the noise is not removed, it will be mistaken for the iris texture feature, which affects the performance of iris recognition system. ...
doi:10.14257/ijsia.2016.10.7.17
fatcat:ewc6axlx7va75opid23pzxtn74
Iris Deidentification with High Visual Realism for Privacy Protection on Websites and Social Networks
2021
IEEE Access
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features of the iris textures are removed and substituted. ...
Extraction of the eye region and iris segmentation C. Computation of
synthetic texture
D. Color domain
adaptation
E. ...
doi:10.1109/access.2021.3114588
fatcat:2tdcxas53bf7pkk2irhxvh2ebm
Adaptive Fuzzy Switching Noise Reduction Filter for Iris Pattern Recognition
2015
Jurnal Teknologi
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Noise reduction is a necessary procedure for the iris recognition systems. This paper proposes an adaptive fuzzy switching noise reduction (AFSNR) filter to reduce noise for iris pattern recognition. ...
This paper proposes an adaptive fuzzy switching noise reduction (AFSNR) filter to reduce noise for iris pattern recognition. ...
Acknowledgement The authors would like to thank the Ministry of Higher Education (MOHE) and Universiti Technologi Malaysia for supporting this research under MIS scholarship. ...
doi:10.11113/jt.v73.3381
fatcat:2dqyxne6snbsffuvmbagmaavsq
Iris recognition by using blood vessel segmentation
2016
IOSR Journal of Computer Engineering
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In this paper a novel framework for recognizing and identifying iris is been proposed. Iroimages are pre-processed to remove noise using median filtering on different image planes separately. ...
Experiment is carried out with the different Iris of different classes and tested. Iris recognition by using blood vessel segmentation ...
Gabor-based texture feature 2.Texture Analysis Using the Gray-Level Co-Occurrence Matrix (GLCM) A statistical method of examining texture that considers the spatial relationship of pixels is the gray-level ...
doi:10.9790/0661-1805034653
fatcat:ugckj3pxpbbxjgfiauclnote7i
A Comparison of Fused Segmentation Algorithms for Iris Verification
[chapter]
2014
Lecture Notes in Computer Science
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Recent studies show fusion at level of segmentation to be useful for more robust iris recognition rates compared with simple segmentation. ...
composed by two parts: Iris segmentation, in which the pupillary and limbic polar curves are detected and Iris normalization: a normalized representation of the iris texture is created using angular and ...
Weighted Adaptive Hough and Ellipsopolar Transform (S2) Weighted Adaptive Hough and Ellipsopolar Transforms (WHT) [8] , the iris segmentation algorithm implemented in the USIT toolbox, based on a weighted ...
doi:10.1007/978-3-319-12568-8_14
fatcat:qxpsi4gavzaknjigvwe5krlun4
An Accurate Iris Segmentation Framework Under Relaxed Imaging Constraints Using Total Variation Model
2015
2015 IEEE International Conference on Computer Vision (ICCV)
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The proposed framework is built on a novel total-variation based formulation which uses l 1 norm regularization to robustly suppress noisy texture pixels for the accurate iris localization. ...
This paper proposes a novel and more accurate iris segmentation framework to automatically segment iris region from the face images acquired with relaxed imaging under visible or near-infrared illumination ...
This approach first adopts a Random Walker [13] to coarsely segment the iris reg ion to locate the iris circle, then applies a set of gray level statistics based operations to refine the boundary. ...
doi:10.1109/iccv.2015.436
dblp:conf/iccv/ZhaoK15
fatcat:3jh4a5acgzbonhq45s4xzx2nze
Iris Recognition Using Fuzzy Level Set and GEFE
2014
International Journal of Machine Learning and Computing
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The proposed iris localization scheme based on FCMLS avoids the over-segmentation and performs well against blurred iris/sclera boundary. ...
The MLBP algorithm combines the sign and magnitude features for the improvement of iris texture classification performance. ...
ACKNOWLEDGMENTS The authors would like to thank the ARL and the NSF for their support of this research. ...
doi:10.7763/ijmlc.2014.v4.416
fatcat:lnmd6mmrunhvlo2y7ogvllb47i
An Improved Bovine Iris Segmentation Method
2019
MATEC Web of Conferences
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The experimental results show that the algorithm can effectively segment iris region, it has good performance of speed and accuracy for iris segmentation, and can eliminate the effects of uneven illumination ...
Then, the annular iris region is normalized. Finally, the normalized iris image is enhanced with adaptive image enhancement method. ...
According to characteristics of bovine iris image , dynamic contour tracking method based on the nonreinitialized variation level set was used to detect inner edge of bovine iris. ...
doi:10.1051/matecconf/201926703002
fatcat:7piieqfiurg2ropsjlctdt4r2e
Accurate Detection of Non-Iris Occlusions
2014
2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems
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This paper presents a fast multispectral iris occlusions detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding. ...
The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections, eyelashes, and eyelids using the recursive prediction analysis. ...
The gray level texture is removed using the wavelet shrinkage approach and defects are subsequently detected by simple thresholding. ...
doi:10.1109/sitis.2014.48
dblp:conf/sitis/HaindlK14
fatcat:kglehyeaczhcldllgjmatzdr5y
Non-ideal iris segmentation using graph cuts
2008
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
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The image is modeled as a Markov random field, and a graph cut based energy minimization algorithm [2] is used to separate textured and untextured regions for eyelash segmentation, as well as to segment ...
A preprocessing step removes specular reflections in the iris, and image gradients in a pixel neighborhood are used to compute texture. ...
For example, eyelash segmentation helps in iris segmentation by removing the eyelashes which may cause errors in iris segmentation. ...
doi:10.1109/cvprw.2008.4563108
dblp:conf/cvpr/PundlikWB08
fatcat:qmjuobpcnncbvnmpyujnwyfwd4
Iris-ocular-periocular: toward more accurate biometrics for off-angle images
2021
Journal of Electronic Imaging (JEI)
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We present convolutional neural network (CNN)-based deep learning frameworks to improve the recognition performance of iris, ocular, and periocular biometric modalities for off-angle images. ...
Finally, deep learning-based results are compared with a traditional iris recognition algorithm using the gallery approach. ...
Since the initial layers of CNNs extract similar low-level Gabor-based features from the datasets, we adapted the first approach to copy the initial weights from the base networks. ...
doi:10.1117/1.jei.30.3.033035
fatcat:kf2ecktdknatvn7iuw3xwnxaga
Quality-based iris segmentation-level fusion
2016
EURASIP Journal on Information Security
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A novel intelligent reference method for iris segmentation-level fusion is presented, which uses a learning-based approach predicting ground truth segmentation performance from quality indicators and model-based ...
In order to avoid a propagation of system errors along the processing chain, this paper investigates iris fusion at segmentation-level prior to feature extraction and presents a framework for this task ...
Acknowledgements This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 312583 and from ...
doi:10.1186/s13635-016-0048-x
fatcat:b65jf5bzbjekvlb4sw7vieremi
Iris Recognition Using Modified Fuzzy Hypersphere Neural Network with different Distance Measures
2011
International Journal of Advanced Computer Science and Applications
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In this paper we describe Iris recognition using Modified Fuzzy Hypersphere Neural Network (MFHSNN) with its learning algorithm, which is an extension of Fuzzy Hypersphere Neural Network (FHSNN) proposed ...
IRIS SEGMENTATION AND FEATURE EXTRACTION Iris Segmentation plays very important role for detecting the iris patterns, Segmentation is to locate valid part of the iris for iris biometric [3] . ...
In segmentation, it is desired to discriminate the iris texture from the rest of the image. ...
doi:10.14569/ijacsa.2011.020619
fatcat:claqmo2ptbarxjhqxvjdh5jdg4
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