An Effective Web Content-Based Image Retrieval Algorithm by Using SIFT Feature

2009 ◽  
Author(s):  
Zhuozheng Wang ◽  
Kebin Jia ◽  
Pengyu Liu
Keyword(s):  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Retrieval Algorithm ◽  
Web Content ◽  
Sift Feature

scholarly journals Multidimensional Markov Stationary Feature for Image Retrival Systems

2016 ◽  
Vol 44 ◽  
pp. 113-122
Author(s):  
Md. Saiful Islam ◽  
Md. Emdadul Haque ◽  
Md. Ekramul Hamid
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Experimental Result ◽  
Content Based Image Retrieval ◽  
Retrieval Algorithm ◽  
Histogram Method

Markov Stationary Features (MSF) not only considers the distribution of colors like histogram method does, also characterizes the spatial co-occurrence of histogram patterns. However, handling large scale database of images, simple MSF method is not sufficient to discriminate the images. In this paper, we have proposed a robust content based image retrieval algorithm that enhances the discriminating capability of the original MSF. The proposed Multidimensional MSF (MMSF) algorithm extends the MSF by generating multiple co-occurrence matrices with different quantization levels of an image. Publicly available WANG1000 and Corel10800 databases are used to evaluate the performance of the proposed algorithm. The experimental result justifies the effectiveness of the proposed method.

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