Open AccessReview of the application of machine learning to the automatic semantic annotation of images
Author(s) -
Olaode Abass,
Naghdy Golshah
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.6153
Subject(s) - computer science , annotation , semantic annotation , artificial intelligence , automatic image annotation , natural language processing , information retrieval , machine learning , image retrieval , image (mathematics)
The massive amount of digital content generated daily in the modern world has created the need for an image retrieval system built on image analysis via image processing and machine learning, therefore this study explains the role of machine learning in bridging the semantic gap in content‐based image retrieval, proposes an automatic image annotation framework, in which training images are obtained from social media, and semantic indexing is achieved using a combination of supervised and unsupervised machine learning. Furthermore, the study also highlights the need for continuous vocabulary improvement for optimum system performance and recommends hardware implementation of machine learning algorithms to ensure high overall speed of image retrieval systems.