Journal of South China University of Technology (Natural Science Edition) ›› 2015, Vol. 43 ›› Issue (5): 114-119.doi: 10.3969/j.issn.1000-565X.2015.05.018

• Computer Science & Technology • Previous Articles     Next Articles

Image Classification Based on JointBoost I2C Distance Metric

Li Zi-long Liu Wei-ming   

  1. School of Civil Engineering and Transportation，South China University of Technology，Guangzhou 510640，Guangdong，China
  • Received:2014-05-06 Revised:2014-11-21 Online:2015-05-25 Published:2015-05-07
  • Contact: 李子龙(1979-)，男，在职博士生，徐州工程学院讲师，主要从事智能交通、图像处理与模式识别研究． E-mail:ong-taizi1979@gmail.com
  • About author:李子龙(1979-)，男，在职博士生，徐州工程学院讲师，主要从事智能交通、图像处理与模式识别研究．
  • Supported by:
    Supported by the National Natural Science Foundation of China(50978106，60273064)and the Natural Science Foundation of Jiangsu Higher Education Institutions of China(14KJB520038，13KJD510007)

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Abstract: Image classification on the basis of image-to-class (I2C) distance metric is a novel method． However，its classification performance needs to be further improved． In this paper，a new image classification method on the basis of JointBoost I2C distance metric is proposed． In this method，a prototype feature set with representative sam-ples is generated,which makes the calculation of distance from the test image to the set more effective． Then，on the basis of JointBoost algorithm，multiple I2C distance metrics are combined to generate a strong classifier for in-tegrating spatial information． Experimental results show that the proposed method is of higher performance for image classification．

Key words: image classification, JointBoost, image to class distance, prototype feature set