全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

标牌图像的旋转不变性矢量提取及其PCA子空间识别*

, PP. 824-830

Keywords: 凹凸字符识别,主分量分析(PCA),特征不变量

Full-Text   Cite this paper   Add to My Lib

Abstract:

提出一种标牌字符图像样本矢量生成方法,有效解决字符图像存在旋转变化时对识别结果的影响.该方法首先提取图像的质心、主轴等特征不变量,然后对图像进行极坐标变换,并按照一定的规则进行排序,最后得到具有旋转不变性的样本矢量.在此基础上对分割得到的单个字符采用PCA子空间方法直接在灰度图像上进行识别.实验表明,该方法可大幅度降低离群样本的数量,与通常采用的矢量形成方法相比,具有更高的识别率.

References

[1]  Li Guoping, Lu Changhou, Li Jianmei. The Method of Image Acquisition on Metal Label Pressed Protuberant Characters Based on Moiré Contour // Proc of the 6th World Congress on Control and Automation. Dalian, China, 2006, Ⅱ: 10175-10178
[2]  Wang Xuechuan, Paliwal K K. Feature Extraction and Dimensionality Reduction Algorithms and Their Applications in Vowel Recognition. Pattern Recognition, 2003, 36(10): 2429-2439
[3]  Cao Jianhai. A Study on Recognition and Checking for the Pressed Protuberant Character on a Metal Label. Ph.D Dissertation. Jinan, China: Shandong University. School of Mechanical Engineering, 2004: 80-82 (in Chinese) (曹建海.金属标牌压印凹凸字符的检测与识别研究.博士学位论文.济南:山东大学.机械工程学院, 2004: 80-82)
[4]  Wang Junfeng, Shi Tielin, Liu Shiyuan. PCA-Based Signal Whitening Decorrelation. China Mechanical Engineering, 2005, 16(21): 954-1956 (in Chinese) (王峻峰,史铁林,刘世元.基于主分量分析的信号白化解相关处理.中国机械工程, 2005, 16(21): 1954-1956)
[5]  Jiang Weifeng, Liu Jilin. Recognition of a Limited Chinese Character Set Based on PCA Learning Subspace Algorithm. Journal of Image and Graphics, 2001, 6(2): 186-190 (in Chinese) (蒋伟峰,刘济林.基于PCA学习子空间算法的有限汉字识别.中国图象图形学报, 2001, 6(2): 186- 190)
[6]  Seghouane A K, Cichocki A. Bayesian Estimation of the Number of Principal Components. Signal Processing, 2007, 87(3): 562-568
[7]  Korenius T, Kaurikkale J, Juhola M. On Principal Component Analysis, Cosine and Euclidean Measures in Information Retrieval. Information Science, 2007, 177(22): 4893-4925
[8]  Salinelli E, Sgarra C. Shift, Slope and Curvature for a Class of Yields Correlation Matrices. Linear Algebra and Its Applications, 2007, 426(2/3): 650-666
[9]  Hu Xuelei, Xu Lei. A Comparative Investigation on Subspace Dimension Determination. Neural Networks, 2004, 17(8/9): 1051-1059
[10]  Cordes D, Nandy R R. Estimation of the Intrinsic Dimensionality of fMRI Data. NeuroImage, 2006, 29(1): 145-154
[11]  Hu M K. Visual Pattern Recognition by Moment Invariant. IEEE Trans on Information Theory, 1962, 8(2): 179-187
[12]  Dudani S A, Breeding K J, McGhee R. Aircraft Identification by Moment Invariants. IEEE Trans on Computers, 1977, 26(1): 39-45
[13]  Abu-Mostafa Y S, Psaltis D. Recognitive Aspects of Moment Invariants. IEEE Trans on Pattern Analysis and Machine Intelligence, 1984, 6(6): 698-706
[14]  Resis T H. The Revised Fundamental Theorem of Moment Invariants. IEEE Trans on Pattern Analysis and Machine Intelligence, 1991, 13(8): 830-834
[15]  Dai M, Baylou P, Najim M. An Efficient Algorithm for Computation of Shape Moments from Run-Length Codes or Chain Codes. Pattern Recognition, 1992, 25(10): 1119-1128
[16]  Rui Ting, Wang Jinruo, Shen Chunlin, et al. Invariance-Based Target Recognition Using Linear Discriminate Analysis. Computer Engineering, 2005, 31(15): 4-6,18 (in Chinese) (芮 挺,王金若,沈春林,等.基于线形分析的特征不变性目标识别.计算机工程, 2005, 31(15): 4-6,18)
[17]  Rui Ting, Shen Chunlin, Qi Tian, et al. Invariance-Based Target Recognition Using Independent Component Analysis. Journal of Chinese Computer Systems, 2005, 26(3): 505-508 (in Chinese) (芮 挺,沈春林,Qi Tian,等.基于ICA的特征不变性目标识别.小型微型计算机系统, 2005, 26(3): 505-508)
[18]  Wang Qicong. Image Recognition Based on the Wavelet Analysis of Moment Features and the Neural Network. Master Dissertation. Hangzhou, China: Zhejiang University of Technology. College of Information Engineering, 2005: 11-17 (in Chinese) (王其聪.基于小波分析的矩特征和神经网络的图像识别.硕士学位论文.杭州: 浙江工业大学.信息工程学院, 2005: 11-17)
[19]  Oja E, Kuusela M. The ALSM Algorithm: An Improved Subspace Method of Classification. Pattern Recognition, 1983, 16(4): 421-427

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133