Content Based Image Retrieval Using Quad Tree Block Truncation Coding with Color Co-Occurrence Feature for the Big Data Platform

2017 ◽  
Vol 14 (8) ◽  
pp. 3874-3886 ◽  
Author(s):  
Jackulin Thangarasu ◽  
P Geetha
Keyword(s):  
Big Data ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Block Truncation Coding ◽  
Quad Tree ◽  
Data Platform

scholarly journals Towards Large Scale Image Retrieval System Using Parallel Frameworks

2020 ◽  
Author(s):  
Saliha Mezzoudj
Keyword(s):  
Big Data ◽  
Image Retrieval ◽  
Large Scale ◽  
Retrieval System ◽  
Image Databases ◽  
Content Based Image Retrieval ◽  
Content Search ◽  
Parallel Frameworks ◽  
Image Retrieval System ◽  
Large Scale Image Retrieval

Recently, the increasing use of mobile devices, such as cameras and smartphones, has resulted in a dramatic increase in the amount of images collected every day. Therefore, retrieving and managing these large volumes of images has become a major challenge in the field of computer vision. One of the solutions for efficiently managing image databases is an Image Content Search (CBIR) system. For this, we introduce in this chapter some fundamental theories of content-based image retrieval for large scale databases using Parallel frameworks. Section 2 and Section 3 presents the basic methods of content-based image retrieval. Then, as the emphasis of this chapter, we introduce in Section 1.2 A content-based image retrieval system for large-scale images databases. After that, we briefly address Big Data, Big Data processing platforms for large scale image retrieval. In Sections 5, 6, 7, and 8. Finally, we draw a conclusion in Section 9.

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