中南大学学报（自然科学版）2016，Vol.47Issue(5)：1599-1605,7.DOI:10.11817/j.issn.1672-7207.2016.05.020
基于改进BOF算法的图像识别和分类
Image recognition and classification based on improved BOF algorithm
摘要
Abstract
Improvedbag offeatures (BOF) algorithmwas applied to image recognition and classification. In view of the low efficiency and low classification accuracy of the traditional BOF algorithm, a new recognition and classification algorithm combined SURF(speededuprobustfeature) with spatial pyramid matching principlewas proposed. SURF algorithm can improve the efficiency, and spatial pyramid matching principle can improve the classification accuracy. Firstly, the image featurewas extracted by SURF algorithm and the codebookwas generated using the features which wereable to respond the changing scales. Secondly, the spatial pyramid matching principlewas applied to the image histogram’s codebook which can improve the accuracy of the classification. Finally, the image histogram’s codebookwas used to be the input of LIBSVM classifier. The experimentswere carried out basedon Graz, Caltech-256andPascal VOC 2012. The results show thatthe proposedmethod is better than the traditional method in the efficiency and classification accuracy. In addition,the proposedmethod is compared with some related research work in classification accuracy,and the proposedmethodhas obvious advantages.关键词
bag offeatures算法/图像识别分类/SURF/空间金字塔匹配Key words
bag of featuresalgorithm/image recognitionandclassification/SURF/spatialpyramidmatching分类
信息技术与安全科学引用本文复制引用
李康顺,王福滨,张丽霞,李伟..基于改进BOF算法的图像识别和分类[J].中南大学学报（自然科学版）,2016,47(5):1599-1605,7.基金项目
国家自然科学资金资助项目(70971043)；广东省自然科学基金资助项目(2015A030313408)；江西理工大学科研基金资助项目(NSFJ2015-K13)(Project(70971043)supported by theNational Natural Science Foundation of China （70971043）
Project(2015A030313408)supported bytheNatural Science Foundation of Guangdong Province of China （2015A030313408）
Project(NSFJ2015-K13)supported by theScience Foundation of Jiangxi University of ScienceandTechnology) （NSFJ2015-K13）
