Open AccessCOMPARISON STUDY BETWEEN IMAGE RETRIEVAL METHODS
Author(s) -
Zahraa H. Al-Obaide,
Ayad A. Al-Ani
Publication year - 2022
Publication title -
iraqi journal of information and communication technology/iraqi journal of information and communication technology
Language(s) - English
Resource type - Journals
eISSN - 2789-7362
pISSN - 2222-758X
DOI - 10.31987/ijict.5.1.182
Subject(s) - image retrieval , automatic image annotation , computer science , visual word , content based image retrieval , image texture , information retrieval , artificial intelligence , feature (linguistics) , metadata , feature detection (computer vision) , sort , field (mathematics) , image (mathematics) , representation (politics) , pattern recognition (psychology) , computer vision , image processing , mathematics , world wide web , linguistics , philosophy , pure mathematics , politics , political science , law
Searching for a relevant image in an archive is a problematic research issue for the computer vision research community. The majority of search engines retrieve images using traditional text-based approaches that rely on captions and metadata. Extensive research has been reported in the last two decades for content-based image retrieval (CBIR), analysis, and image classification. Content-Based Image Retrieval is a process that provides a framework for image search, and low-level visual features are commonly used to retrieve the images from the image database. The essential requirement in any image retrieval process is to sort the images with a close similarity in terms of visual appearance. The shape, color, and texture are examples of low-level image features. In image classification-based models and CBIR, high-level image visuals are expressed in the form of feature vectors made up of numerical values. The researcher's findings a significant gap between human visual comprehension and image feature representation. In this paper, we plan to present a comparison study and a comprehensive overview of the recent developments in the field of CBIR and image representation.