A Novel Iris Recognition Based on PSO-RBFNN

摘要：

In this paper, a self-adaptive method of iris boundary detection is presented and the method can segment the iris area accurately regardless of the shapes of iris boundaries.On the same time, a new feature extraction technique based on combination using special Gabor filters and wavelet maxima components is proposed.Finally, The radial basis function neural network (RBFNN) with a particle swarm optimization (PSO) a novel iris iris recognition technique with intelligent classifier is proposed for high performance iris recognition, this paper combines radial basis function neural network (RBFNN) and particle swarm optimization (PSO) for an optimized PNN classifier model.The experimental results reveal the proposed algorithm provides superior performance in iris recognition.

关键词： iris recognition Probabilistic neural network Particle swarm optimization RBF neural networks

作者: Liu Jin Fu Xiao Wang Haopeng

作者单位: Department of Fundamental Courses Air Force Aviation University Changchun,China Elementary Flight Training Base Air Force Aviation University Changchun,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Education Technology and Computer(2011第三届教育技术与计算机国际会议 ICETC2011)

会议地点: 成都

会议语种:英文

页码: 148-151

在线出版日期: 2011-07-15（万方平台首次上网日期，不代表论文的发表时间）