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An Image Similarity Acceleration Detection Algorithm Based on Sparse Coding

机译：基于稀疏编码的图像相似度加速检测算法

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摘要

Aiming at the problem that the image similarity detection efficiency is low based on local feature, an algorithm called ScSIFT for image similarity acceleration detection based on sparse coding is proposed. The algorithm improves the image similarity matching speed by sparse coding and indexing the extracted local features. Firstly, the SIFT feature of the image is extracted as a training sample to complete the overcomplete dictionary, and a set of overcomplete bases is obtained. The SIFT feature vector of the image is sparse-coded with the overcomplete dictionary, and the sparse feature vector is used to build an index. The image similarity detection result is obtained by comparing the sparse coefficients. The experimental results show that the proposed algorithm can significantly improve the detection speed compared with the traditional algorithm based on local feature detection under the premise of guaranteeing the accuracy of algorithm detection.
机译：针对基于局部特征的图像相似度检测效率低的问题，提出了一种基于稀疏编码的图像相似度加速检测算法ScSIFT。该算法通过稀疏编码和索引提取的局部特征来提高图像相似度匹配速度。首先，提取图像的SIFT特征作为训练样本，以完成超完备字典，并获得一组超完备库。图像的SIFT特征向量用过完备字典进行稀疏编码，稀疏特征向量用于建立索引。通过比较稀疏系数来获得图像相似度检测结果。实验结果表明，与传统的基于局部特征检测的算法相比，在保证算法检测精度的前提下，该算法能够显着提高检测速度。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第6期|1917421.1-1917421.9|共9页
  • 作者

    Luan Xidao; Xie Yuxiang; Zhang Lili; Zhang Xin; Li Chen; He Jingmeng;

  • 作者单位

    Changsha Univ, Dept Math & Comp Sci, Changsha 410003, Hunan, Peoples R China;

    Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Hunan, Peoples R China;

    Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Hunan, Peoples R China;

    Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Hunan, Peoples R China;

    Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Hunan, Peoples R China;

    Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Hunan, Peoples R China;

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