Image Retrieval Method Based on Three-Structure Descriptor

doi:10.7652/xjtuxb201706014

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Image Retrieval Method Based on Three-Structure Descriptor

更新时间：2025-07-09

- Image Retrieval Method Based on Three-Structure Descriptor
- Vol. 51, Issue 6, Pages: 86-91(2017)
- 作者机构：
  
  大连理工大学计算机科学与技术学院,辽宁,大连,116024
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201706014
  CLC： TP391
- Online First：10 June 2017，
  
  Published：2017
- 稿件说明：
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Image Retrieval Method Based on Three-Structure Descriptor[J]. 2017, 51(6): 86-91.
DOI：

Image Retrieval Method Based on Three-Structure Descriptor[J]. 2017, 51(6): 86-91. DOI： 10.7652/xjtuxb201706014.

摘要

针对基元结构描述子在颜色空间的基础上再提取其他特征

导致偏重对颜色信息的描述而降低了图像检索性能的问题

提出一种应用在HSV颜色空间上的三结构描述子(TSD)的特征提取方法。该方法在HSV颜色空间中分别提取颜色和纹理信息

考虑到了颜色和纹理特征的同等重要性

同时避免了颜色信息的过多干扰; 在纹理特征提取中

TSD利用像素间的信息变化来表示局部空间结构信息

解决了传统的局部模式方法忽略对局部结构的空间关系描述的问题

获得了更多的空间结构信息。实验结果表明

该方法在3个图像库Corel-1000、Corel-5000和Corel-10000上的检索准确率分别达到78.08%、38.12%和52.12%

与以往基元结构方法相比

检索准确率得到了提高。

Abstract

A novel feature extraction method called three-structure descriptor(TSD)used in HSV color space is proposed to address the problem that the image description methods based on texton pay undue attention to the color description so reduce the performance of image retrieval due to directly extracting other features in color space. The proposed method extracts color and texture information in HSV color space and the same importance of both the color and texture is taken into account while the excessive interference of color information is avoided. TSD uses the information change among pixels to represent the local spatial structure information in texture feature extraction

which solves the problem that the traditional local pattern methods disregard the spatial correlation in local structure and captures more information regarding to spatial structure information. Experimental results show that the retrieval precisions of the proposed method reach 78.08%

38.12% and 52.12% on the Corel-1000

Corel-5000 and Corel-10000 databases respectively

and its retrieval precisions are higher than those of existing methods based on texton.

关键词

Keywords

references

ELALAMI M E. A new matching strategy for content based image retrieval system [J]. Applied Soft Computing, 2014, 14(1): 407-418.

SWAIN M J, BALLARD D H. Color indexing [J]. International Journal of Computer Vision, 1991, 7(1): 11-32.

STRICKER M A, ORENGO M. Similarity of color images [C]∥Proceedings of the SPIE, Storage and Retrieval for Image and Video Database III. Bellingham, WA, USA: SPIE, 1995: 381-392.

HARALICK R M, SHANMUGAM K, DINSTEIN I H. Textural features for image classification [J]. IEEE Transactions on Systems, Man and Cybernetics, 1973, 3(6): 610-621.

DE SIQUEIRA F R, SCHWARTZ W R, PEDRINI H. Multi-scale gray level co-occurrence matrices for texture description [J]. Neurocomputing, 2013, 120(10): 336-345.

OJALA T, PIETIKAINEN M, MAENPAA T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987.

JAIN A K, VAILAYA A. Image retrieval using color and shape [J]. Pattern Recognition, 1996, 29(8): 1233-1244.

KAUPPINEN H, SEPPANEN T, PIETIKAINEN M. An experimental comparison of autoregressive and Fourier-based descriptors in 2D shape classification [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17(2): 201-207.

VIPPARTHI S K, NAGAR S K. Multi-joint histogram based modelling for image indexing and retrieval [J]. Computers and Electrical Engineering, 2014, 40(8): 163-173.

LIU G H, LI Z Y, ZHANG L, et al. Image retrieval based on micro-structure descriptor [J]. Pattern Recognition, 2011, 44(9): 2123-2133.

LIU G H, ZHANG L, HOU Y K, et al. Image retrieval based on multi-texton histogram [J]. Pattern Recognition, 2010, 43(7): 2380-2389.

LIU G H, YANG J Y. Content-based image retrieval using color difference histogram [J]. Pattern Recognition, 2013, 46(1): 188-198.

JULESZ B. Textons, the elements of texture perception, and their interactions [J]. Nature, 1981, 290(5802): 91-97.

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