Content-based image retrieval: A review of recent trends. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Hameed, Ibtihaal M.; Abdulhussain, Sadiq H.; Mahmmod, Basheera M.
• Editors: Pham, D T
• Is Part Of: Cogent engineering. Volume 8:Issue 1(2021)
• Publication Date: 2021-01-01
• Subjects: content-based image retrieval -- image feature -- feature extraction -- similarity measure -- machine learning; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2021.1927469
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: With the availability of internet technology and the low-cost of digital image sensor, enormous amount of image databases have been created in different kind of applications. These image databases increase the demand to develop efficient image retrieval search methods that meet user requirements. Great attention and efforts have been devoted to improve content-based image retrieval method with a particular focus on reducing the semantic gap between low-level features and human visual perceptions. Due to the increasing research in this field, this paper surveys, analyses and compares the current state-of-the-art methodologies over the last six years in the CBIR field. This paper also provides an overview of CBIR framework, recent low-level feature extraction methods, machine learning algorithms, similarity measures, and a performance evaluation to inspire further research efforts.