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...

基于集成分类算法的自动图像标注

DOI: 10.3724/SP.J.1004.2012.01257, PP. 1257-1262

Keywords: 自动图像标注,机器学习,集成分类器,快速随机森林算法

Full-Text   Cite this paper   Add to My Lib

Abstract:

?基于语义的图像检索技术中,按照图像的语义进行自动标注是一个具有挑战性的工作.本文把图像的自动标注过程转化为图像分类的过程,通过有监督学习对每个图像区域分类并得到相应关键字,实现标注.采用一种快速随机森林(Fastrandomforest,FRF)集成分类算法,它可以对大量的训练数据进行有效的分类和标注.在基于Corel数据集的实验中,相比经典算法,FRF改善了运算速度,并且分类精度保持稳定.在图像标注方面有很好的应用.

References

[1]  Rui Y, Huang T S, Chang S F. Image retrieval: past, present, and future. Journal of Visual Communication and Image Representation, 1997, 10: 1-23
[2]  Duygulu P, Barnard K, Freitas J F G, Forsyth D A. Object recognition as machine translation: learning a lexicon for a fixed image vocabulary. In: Proceedings of the 7th European Conference on Computer Vision. Copenhagen, Denmark: Springer, 2002. 97-112
[3]  Blei D, Jordan M. Modeling annotated data. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Toronto, Canada: ACM, 2003. 127-134
[4]  Lavrenko V, Manmatha R, Jeon J. A model for learning the semantics of pictures. In: Proceedings of the Advances in Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2003. 553-560
[5]  Chow T W S, Rahman M K M. A new image classification technique using tree-structured regional features. Neurocomputing, 2007, 70(4-6): 1040-1050
[6]  Fan J, Shen Y, Yang C, Zhou N. Structured max-margin learning for inter-related classifier training and multilabel image annotation. IEEE Transactions on Image Processing, 2011, 20(3): 837-854
[7]  Pourghassem H, Ghassemian H. Content-based medical image classification using a new hierarchical merging scheme. Computerized Medical Imaging and Graphics, 2008, 32(8): 651-661
[8]  Chang E, Kingshy G, Sychay G, Wu G. CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines. IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(1): 26-38
[9]  Lu Jing, Ma Shao-Ping. Region-based image annotation using heuristic support vector machine in multiple-instance learning. Journal of Computer Research and Development, 2009, 46(5): 864-871(路晶, 马少平. 使用基于多例学习的启发式SVM算法的图像自动标注. 计算机研究与发展, 2009, 46(5): 864-871)
[10]  Efron B. Bootstrap methods: another look at the Jack-knife. The Annals of Statistics, 1979, 7(1): 1-26
[11]  Breiman L. Bagging predictors. Machine Learning, 1996, 24(2): 123-140
[12]  Wang Xiang-Yang, Yang Hong-Ying, Zheng Hong-Liang, Wu Jun-Feng. A color block-histogram image retrieval based on visual weight. Acta Automatica Sinica, 2010, 36(10): 1489-1492(王向阳, 杨红颖, 郑宏亮, 吴俊峰. 基于视觉权值的分块颜色直方图图像检索算法. 自动化学报, 2010, 36(10): 1489-1492)
[13]  Ulges A, Worring M, Breuel T. Learning visual contexts for image annotation from flickr groups. IEEE Transactions on Multimedia, 2010, 13(2): 330-341
[14]  Xu Hong-Tao, Zhou Xiang-Dong, Xiang Yu, Shi Bai-Le. Adaptive model for web image semantic automatic annotation. Journal of Software, 2010, 21(9): 2183-2195(许红涛, 周向东, 向宇, 施伯乐. 一种自适应的Web图像语义自动标注方法. 软件学报, 2010, 21(9): 2183-2195)
[15]  Mori Y, Takahashi H, Oka R. Image-to-word transformation based on dividing and vector quantizing images with words. In: Proceedings of the 1st International Workshop on Multimedia Intelligent Storage and Retrieval Management. Orlando, Florida: MISRM, 1999. 1-9
[16]  Jeon J, Lavrenko V, Manmatha R. Automatic image annotation and retrieval using cross-media relevance models. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Toronto, Canada: ACM, 2003. 119-126
[17]  Feng S L, Manmatha R, Lavrenko V. Multiple Bernoulli relevance models for image and video annotation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). Washington D.C., USA: IEEE, 2004. 1002-1009
[18]  Hou J, Chen Z, Qin X, Zhang D. Automatic image search based on improved feature descriptors and decision tree. Integrated Computer-Aided Engineering, 2011, 18(2): 167-180
[19]  Nezamabadi-pour H, Kabir E. Concept learning by fuzzy k-NN classification and relevance feedback for efficient image retrieval. Expert Systems with Applications, 2008, 36(3): 5948-5954
[20]  Tsai C F. Image mining by spectral features: a case study of scenery image classification. Expert Systems with Applications, 2007, 32(1): 135-142
[21]  Yang C B, Dong M, Hua J. Region-based image annotation using asymmetrical support vector machine-based multiple-instance learning. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). New York, USA: IEEE, 2006. 2057-2063
[22]  Breiman L. Random forests. Machine Learning, 2001, 45(1): 5-32
[23]  Rokach L. Ensemble-based classifiers. Artificial Intelligence Review, 2010, 33(1-2): 1-39
[24]  Xu L, Krzyzak A, Suen C Y. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Transactions on Systems, Man, and Cybernetics, 1992, 22(3): 418-435
[25]  Deng Y, Manjunath B S. Unsupervised segmentation of color-texture regions in images and video. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(8): 800-810

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133