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浏览/检索结果: 共8条，第1-8条 帮助 限定条件 发表日期：2011    内容类型：会议论文     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China Wu Z.-G.; Wang M.-J.; Han G.-L. 收藏  |  浏览/下载：34/0  |  提交时间：2013/03/25 Being an efficient method of information fusion  image fusion has been used in many fields such as machine vision  medical diagnosis  military applications and remote sensing.In this paper  Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing  including segmentation  target recognition et al.  and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First  the two original images are decomposed by wavelet transform. Then  based on the PCNN  a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength  so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So  the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment  the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range  which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore  by this algorithm  the threshold adjusting constant is estimated by appointed iteration number. Furthermore  In order to sufficient reflect order of the firing time  the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved  each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules  the experiments upon Multi-focus image are done. Moreover  comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.   Feature Extraction from Noisy Image Using Intersecting Cortical Model 会议论文 World-Association-of-Science-Engineering Global Congress on Science Engineering (GCSE 2010), Yantai, PEOPLES R CHINA, NOV 27-28, 2010 作者:  Wang, XF;  Li, BN;  Huang, YL;  Wang, XR 收藏  |  浏览/下载：3/0  |  提交时间：2017/01/18 Intersecting Cortical Model (ICM)  Pulse Coupled Neural Network (PCNN)  Mean Square Error (MSE)  Feature extraction  Pattern Recognition   The application of the combinatorial optimization problems based on preventive feedback pulse coupled neural network 会议论文 2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011, Wuhan, China, May 28, 2011 - May 29, 2011 作者:  Feng, Xiaowen;  Zhan, Kun;  Ma, Yide 收藏  |  浏览/下载：2/0  |  提交时间：2017/01/18 Neural networks  Algorithms  Combinatorial optimization  Intelligent systems  Optimization  auto-wave  Combination optimization  Combinatorial optimization problems  preventive feedback  Pulse Coupled Neural Network  Searching speed  Solution space  Space complexity  Triangle inequality   A PCNN-based method for vehicle license localization 会议论文 作者:  Wei, Zhuo 收藏  |  浏览/下载：8/0  |  提交时间：2019/12/10 Automatic vehicles  Connected component analysis  License plate location  Morphological operations  Plate extractions  projection  Pulse coupled neural network  Vertical projection   PCNN automatic parameters determination in image segmentation based on the analysis of neuron firing time 会议论文 作者:  Deng, Xiangyu;  Ma, Yide 收藏  |  浏览/下载：0/0  |  提交时间：2020/11/15 Image analysis  Intelligent systems  Neural networks  Neurons  Coupling effect  Neuron Firing Characteristics  Neuron firing time  Parameters determination  Parameters setting  Pcnn models  Pulse coupled neural network models  Setting parameters   Combination of SVM and score normalization for person identification based on audio-visual feature fusion 会议论文 Hangzhou, China, March 9, 2011 - March 11, 2011 作者:  Cao, Jie;  Wu, Di;  Liu, Zong Li;  Pan, Peng 收藏  |  浏览/下载：0/0  |  提交时间：2020/11/15 Biometrics  Computer applications  Feature extraction  Neural networks  Signal to noise ratio  Speech recognition  Support vector machines  Accuracy rate  Audio-visual features  Computational costs  Face features  Feature level fusion  Fused system  Fusing face  Identity recognition  Noisy environment  ORL database  Person identification  Pulse coupled neural network  Recognition performance  Recognition rates  Score normalization  Speaker recognition  Speech features  SVM theory   Edge detection for aluminum alloy MIG welding pool based on pulse coupled neural network 会议论文 Shanghai, China, July 26, 2011 - July 28, 2011 作者:  Wu, Mingliang;  Zhang, Gang;  Huang, Jiankang;  Shi, Yu;  Shao, Ling 收藏  |  浏览/下载：0/0  |  提交时间：2020/11/15 Edge detection  Gas metal arc welding  Inert gas welding  Lakes  Neural networks  Object recognition  Canny detector  MIG welding  Pulse coupled neural network  Single frames  Welding pool   Combination of SVM and Score Normalization for Person Identification based on audio-visual feature fusion 会议论文 作者:  Cao, Jie;  Wu, Di;  Liu, Zong Li;  Pan, Peng 收藏  |  浏览/下载：1/0  |  提交时间：2019/11/15 Support Vector Machine  Score Normalization  Pulse Coupled Neural Network