北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2011, Vol. 34 ›› Issue (s1): 100-103.doi: 10.13190/jbupt.2011s1.100.chenht

• 研究报告 • 上一篇    下一篇

综合纹理统计模型与全局主颜色的图像检索方法

陈慧婷,覃团发,唐振华,常侃   

  1. 广西大学 计算机与电子信息学院, 南宁 530004
  • 出版日期:2011-10-28 发布日期:2011-10-28
  • 作者简介:陈慧婷(1987-),女,硕士生,E-mail:doris_tintin@yahoo.com.cn 覃团发(1966-),男,教授,博士生导师
  • 基金资助:

    广西科学基金项目(桂科自0991058);广西高校人才小高地建设创新团队资助计划项目(桂教人[2007]71号)

A Method of Image Retrievals Based on Texture Probability Statistics  and Global Dominant Color

    

  1.  
  • Online:2011-10-28 Published:2011-10-28
  • Supported by:
     

摘要:

为了克服纹理概率统计方法中颜色信息丢失的缺点,提高图像检索性能,将纹理概率统计模型和全局主颜色方法有机地结合起来,在对纹理和颜色特征线性加权的基础上对组合后的纹理和颜色特征进行二次检索.实验结果表明,在2 600幅彩色图像库中,与单一特征和线性结合2种特征的方法相比新方法的性能有较大提高,查全率提高30%,平均归一化修正检索等级提高22%.

关键词: 概率统计模型, 全局主颜色, 纹理特征, 图像检索

Abstract:

Extracting texture features of images with probability statistics models is a significant method of contentbased image retrieval. In order to overcome the shortcomings of lack of color information and improve probability statistics retrieval performance, an approach that combines the global dominant color and probability statistics is proposed. The combinative features including texture and color are utilized for second retrieval after linear weighting. Experiments based on the 2600 images database shows superior performance of our proposed method compared with the single feature image retrieval and the probability statistics retrieval, recall rates and average normalized modified retrieval rank have been raised by 30% and 22% respectively.

Key words: probability statistics, dominant color, texture, image retrieval

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