Based on Image Salient Features Network Image Retrieval Method

K. Yan, Ke Feng, Y. Wang, Bo-nian Pan
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引用次数: 0

Abstract

Traditional image retrieval depends on the images embedded in text messages, text description of the limitations of image content, resulting in low quality of image retrieval. The local information extracted image itself, the use of local features LSH image matching algorithm, memory requirements has led to a linear growth. To overcome these shortcomings, then propose the method of image retrieval which based on the network salient features, by screening out the salient features of the frequent appearance of points, with each image feature point matching vectors to generate histogram matching, the use of its similarity to generate the calculation of PageRank, Adjacency matrix for each image to generate a PageRank score. Experimental results show that the algorithm improves the network image retrieval efficiency and accuracy.
基于图像显著特征的网络图像检索方法
传统的图像检索依赖于图像嵌入文本信息,文本描述图像内容的局限性,导致图像检索质量较低。将图像本身的局部信息提取出来,采用LSH图像局部特征匹配算法,导致内存需求呈线性增长。为了克服这些缺点,提出了基于网络显著特征的图像检索方法,通过筛选出显著特征频繁出现的点,与每个图像特征点的匹配向量生成直方图匹配,利用其相似度生成计算PageRank,邻接矩阵对每个图像生成PageRank分数。实验结果表明,该算法提高了网络图像检索的效率和准确性。
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