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An Iris Texture feature based Radial Basis Neural network Classifier with enhanced performance

机译:基于虹膜纹理特征的径向基础神经网络分类器,具有增强性能

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Iris detection and classification has been a problem of real significance in the fields of image processing and medical electronics. In this paper, an efficient texture based statistical feature extraction and classification based on a novel Distinction Parameter has been proposed. The proposed technique makes use of standard iris image databases and efficient radial basis neural network architecture for classification. Various simulation results have also been presented in this paper
机译:虹膜检测和分类是图像处理和医疗电子领域的真正意义的问题。本文提出了基于新颖区分参数的基于有效的基于纹理的统计特征提取和分类。所提出的技术利用标准虹膜图像数据库和高效的径向基础神经网络架构进行分类。本文还提出了各种仿真结果

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