Trademark image retrieval based on particle swarm optimization in multi-feature fusion

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (21): 186-190.

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Trademark image retrieval based on particle swarm optimization in multi-feature fusion

ZHANG Wenwen1, WANG Bin1，2, SHU Huazhong3

1.School of Biomedical Engineering, Southeast University, Nanjing 210096, China
2.Provincial Key Lab of E-Commerce, Nanjing University of Finance and Economics, Nanjing 210046, China
3.School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

Online:2012-07-21 Published:2014-05-19

基于粒子群优化的多特征融合的商标图像检索

张雯雯1，王斌1，2，舒华忠3

1.东南大学生物医学工程学院，南京 210096
2.南京财经大学电子商务省级重点实验室，南京 210046
3.东南大学计算机科学与工程学院，南京 210096

Abstract

Abstract: This paper develops a method of trademark image retrieval based on particle swarm optimization in multi-feature fusion. It can optimize the weights of multi-feature fusion automatically, improve self-adaptive of?the image?retrieval system, and solve the allocation problem of feature weights in the trademark image retrieval. After retrieving in the trademark?image database constituted of 1000?images, the results show that the proposed method has a better retrieval performance than?the single-feature-based retrieval?methods and some multi-feature-fusion retrieval?methods.

Key words: Particle Swarm Optimization（PSO） algorithm, multi-feature fusion, feature weight assignment, trademark image retrieval

摘要： 提出一种基于粒子群优化的多特征融合的商标图像检索方法，该方法可自动优化多特征融合的权重，提高图像检索系统的自适应性，解决了多特征商标图像检索中的权重分配问题。在1 000幅图像构成的商标图像库进行检索实验，实验结果表明，与基于单一特征的检索方法和一些多特征融合的检索方法相比，提出方法的检索性能最优。

关键词: 粒子群优化算法, 多特征融合, 特征权重分配, 商标图像检索

ZHANG Wenwen1, WANG Bin1，2, SHU Huazhong3. Trademark image retrieval based on particle swarm optimization in multi-feature fusion[J]. Computer Engineering and Applications, 2012, 48(21): 186-190.

张雯雯1，王斌1，2，舒华忠3. 基于粒子群优化的多特征融合的商标图像检索[J]. 计算机工程与应用, 2012, 48(21): 186-190.

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Trademark image retrieval based on particle swarm optimization in multi-feature fusion

基于粒子群优化的多特征融合的商标图像检索

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