| 结合LBP和Brushlet的自适应图像检索 |
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| 引用本文： | 杨晓慧,姚雪彦.结合LBP和Brushlet的自适应图像检索[J].计算机工程,2013,39(2):233-236. |
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| 作者姓名： | 杨晓慧 姚雪彦 |
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| 作者单位： | 1. 河南大学数学与信息科学学院应用数学研究所,河南开封475004;西安电子科技大学智能感知与图像理解教育部重点实验室,西安710071
2. 河南大学数学与信息科学学院应用数学研究所,河南开封,475004 |
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| 基金项目： | 国家自然科学基金资助项目(60802061)；智能感知与图像理解教育部重点实验室开放基金资助项目“图像检索中相关反馈技术研究”(IPIU012011004) |
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| 摘 要： | 针对时域和频域纹理特征的优点和互补性，提出一种结合局部二值模式(LBP)和Brushlet域系数统计特征的自适应纹理图像检索方法。利用Brushlet变换得到各个子带的能量作为频域特征，提取图像的LBP直方图作为空域特征，并采用改进的Canberra距离进行度量，使用闭环反馈实现图像的自适应检索。实验结果表明，与LBP方法和Brushlet方法相比，该方法的平均检索率分别提高8.93%和18.66%。
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| 关 键 词： | 图像检索 Brushlet变换 局部二值模式 闭环反馈 空域特征 变换域特征 |
| 收稿时间： | 2011-11-23 |
| 修稿时间： | 2012-01-26 |
Adaptive Image Retrieval Combined with LBP and Brushlet |
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| YANG Xiao-hui
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YAO Xue-yan.Adaptive Image Retrieval Combined with LBP and Brushlet[J].Computer Engineering,2013,39(2):233-236. |
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| Authors: | YANG Xiao-hui YAO Xue-yan |
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| Affiliation: | 1(1.Institute of Applied Mathematics,School of Mathematics and Information Sciences,Henan University,Kaifeng 475004,China;2.Key Laboratory of Intelligent Perception and Image Understanding,Ministry of Education,Xidian University,Xi’an 710071,China) |
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| Abstract: | By considering advantages and complementary of spatial and frequency textures features, an adaptive texture image retrieval method is presented combined with Local Binary Pattern(LBP) feature and Brushlet domain coefficient statistical feature. Frequency feature is described as energy feature of every Brushlet subband. Spatial feature is LBP histogram. Similarity between images is measured by improved Canberra distance. Further, closed-loop feedback is introduced to adjust weights adaptively for image retrieval. Experimental results show that average recall rate of this method based on fused features is 8.93% and 18.66% higher than LBP method and Brushlet domain method respectively. |
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| Keywords: | image retrieval Brushlet transform Local Binary Pattern(LBP) closed-loop feedback spatial domain feature transform domain feature |
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