کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388004 | 660915 | 2009 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
High performance iris recognition based on 1-D circular feature extraction and PSO–PNN classifier
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: High performance iris recognition based on 1-D circular feature extraction and PSO–PNN classifier High performance iris recognition based on 1-D circular feature extraction and PSO–PNN classifier](/preview/png/388004.png)
چکیده انگلیسی
In this paper, a novel iris feature extraction technique with intelligent classifier is proposed for high performance iris recognition. We use one dimensional circular profile to represent iris features. The reduced and significant features afterward are extracted by Sobel operator and 1-D wavelet transform. So as to improve the accuracy, this paper combines probabilistic neural network (PNN) and particle swarm optimization (PSO) for an optimized PNN classifier model. A comparative experiment of existing methods for iris recognition is evaluated on CASIA iris image databases. The experimental results reveal the proposed algorithm provides superior performance in iris recognition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 7, September 2009, Pages 10351–10356
Journal: Expert Systems with Applications - Volume 36, Issue 7, September 2009, Pages 10351–10356
نویسندگان
Ching-Han Chen, Chia-Te Chu,