Efficiency comparative analysis between two search algorithms using DT CWT for content-based image retrieval

Author(s):  
Stella Vetova ◽  
Ivan Ivanov
Author(s):  
Dmitry Kinoshenko ◽  
Vladimir Mashtalir ◽  
Vladislav Shlyakhov ◽  
Elena Yegorova

In this paper, a metric on partitions of arbitrary measurable sets and its special properties for metrical content-based image retrieval based on the ‘spatial’ semantic of images is proposed. This approach considers images represented in the form of nested partitions produced by any segmentations, which are used to express a degree of information refinement or roughening. In doing so, this not only corresponds to rational content control but also ensures creation of specific search algorithms (e.g., invariant to image background) and synthesizes hierarchical models of image search by reducing the number of query and database elements match operations.


Author(s):  
Rajeev Gupta ◽  
Virender Singh

Purpose: With the popularity and remarkable usage of digital images in various domains, the existing image retrieval techniques need to be enhanced. The content-based image retrieval is playing a vital role to retrieve the requested data from the database available in cyberspace. CBIR from cyberspace is a popular and interesting research area nowadays for a better outcome. The searching and downloading of the requested images accurately based on meta-data from the cyberspace by using CBIR techniques is a challenging task. The purpose of this study is to explore the various image retrieval techniques for retrieving the data available in cyberspace.  Methodology: Whenever a user wishes to retrieve an image from the web, using present search engines, a bunch of images is retrieved based on a user query. But, most of the resultant images are unrelated to the user query. Here, the user puts their text-based query in the web-based search engine and compute the related images and retrieval time. Main Findings:  This study compares the accuracy and retrieval-time of the requested image. After the detailed analysis, the main finding is none of the used web-search engines viz. Flickr, Pixabay, Shutterstock, Bing, Everypixel, retrieved the accurate related images based on the entered query.   Implications: This study is discussing and performs a comparative analysis of various content-based image retrieval techniques from cyberspace. Novelty of Study: Research community has been making efforts towards efficient retrieval of useful images from the web but this problem has not been solved and it still prevails as an open research challenge. This study makes some efforts to resolve this research challenge and perform a comparative analysis of the outcome of various web-search engines.


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