Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM
In order to overcome the weakness of wavelet transform in two dimensional spatial analysis，an improved algorithm based on fast discrete Curvelet transform for iris recognition was proposed.Curvelet transform which can effectively capture the image edge information was introduced to decompose iris im...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2016-03-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016058/ |
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| _version_ | 1841529130114351104 |
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| author | Zhenhong HE |
| author_facet | Zhenhong HE |
| author_sort | Zhenhong HE |
| collection | DOAJ |
| description | In order to overcome the weakness of wavelet transform in two dimensional spatial analysis，an improved algorithm based on fast discrete Curvelet transform for iris recognition was proposed.Curvelet transform which can effectively capture the image edge information was introduced to decompose iris image.Mean and variance of low frequency sub-band coefficients and the energy of high frequency sub-band were extracted.Then the feature vectors were weighted according to the difference of classification ability of sub-band feature.Fuzzy least square support vector machine with optimal binary tree was developed to implement classification and recognition.The simulation results show that the proposed algorithm has higher recognition performance than the present method. |
| format | Article |
| id | doaj-art-e19bd52b799b4832ab7f695e084e5ed4 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2016-03-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-e19bd52b799b4832ab7f695e084e5ed42025-01-15T03:24:55ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012016-03-0132929859800456Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVMZhenhong HEIn order to overcome the weakness of wavelet transform in two dimensional spatial analysis，an improved algorithm based on fast discrete Curvelet transform for iris recognition was proposed.Curvelet transform which can effectively capture the image edge information was introduced to decompose iris image.Mean and variance of low frequency sub-band coefficients and the energy of high frequency sub-band were extracted.Then the feature vectors were weighted according to the difference of classification ability of sub-band feature.Fuzzy least square support vector machine with optimal binary tree was developed to implement classification and recognition.The simulation results show that the proposed algorithm has higher recognition performance than the present method.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016058/iris recognitionfeature weightingfast discrete Curvelet transformfuzzy least square support vector machineoptimal binary tree |
| spellingShingle | Zhenhong HE Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM Dianxin kexue iris recognition feature weighting fast discrete Curvelet transform fuzzy least square support vector machine optimal binary tree |
| title | Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM |
| title_full | Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM |
| title_fullStr | Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM |
| title_full_unstemmed | Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM |
| title_short | Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM |
| title_sort | iris recognition algorithm based on feature weighting fast discrete curvelet transform and fuzzy ls svm |
| topic | iris recognition feature weighting fast discrete Curvelet transform fuzzy least square support vector machine optimal binary tree |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016058/ |
| work_keys_str_mv | AT zhenhonghe irisrecognitionalgorithmbasedonfeatureweightingfastdiscretecurvelettransformandfuzzylssvm |