电信科学 ›› 2016, Vol. 32 ›› Issue (12): 80-85.doi: 10.11959/j.issn.1000-0801.2016308

• 研究与开发 • 上一篇    下一篇

结合VLAD特征和稀疏表示的图像检索

颜文,金炜,符冉迪   

  1. 宁波大学信息科学与工程学院，浙江 宁波 315211
  • 出版日期:2016-12-20 发布日期:2017-04-26
  • 基金资助:
    国家自然科学基金资助项目;浙江省自然科学基金资助项目;宁波市自然科学基金资助项目

Image retrieval based on the feature of VLAD and sparse representation

Wen YAN,Wei JIN,Randi FU   

  1. Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, China
  • Online:2016-12-20 Published:2017-04-26
  • Supported by:
    The National Natural Science Foundation of China;The Natural Science Foundation of Zhejiang Province of China;The Natural Science Foundation of Ningbo of China

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摘要：

为了实现快速准确的图像检索目标，提出一种结合VLAD（局部聚合描述符）特征和稀疏表示的图像检索方法。首先，根据图像具有结构细节丰富、局部视觉特征差异明显的特点，提取图像的局部旋转不变SURF特征，并采用局部聚合描述符方法，构造具有旋转不变性的图像VLAD特征，然后将VLAD特征与稀疏表示相结合，设计基于稀疏表示的相似性检索度量准则，实现图像的查询检索。实验结果表明，提出方法在查准率（precision）及平均归一化修正检索排序等指标上，均优于其他几种典型方法，并具有较高的计算效率。

关键词: 图像检索, 稀疏表示, 局部聚合描述符

Abstract:

In order to achieve the goal of fast and accurate image retrieval,an image retrieval method combining VLAD （vector of locally aggregated descriptor）feature and sparse representation was proposed. Firstly, according to the characteristics of rich structure details and obvious differences for local visual features in image, the local rotation invariant SURF feature of the image was extracted,and the local VLAD feature of the image with rotation invariance was constructed by the local aggregation descriptor method. Then, the VLAD feature was combined with the sparse representation（SR）to design the similarity retrieval metric based on SR,thus the retrieval of the image could be realized. The experimental results show that,proposed method outperforms the compared methods in terms of precision,average normalize modified retrieval rank（ANMRR）and other indicators,and it also has higher computational efficiency.

Key words: image retrieval, sparse representation, vector of locally aggregated descriptor

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