Approaches, Challenges and Future Direction of Image Retrieval

TL;DR

This paper reviews the evolution, challenges, and future directions of image retrieval, emphasizing the shift from keyword-based to semantic features and addressing the semantic gap issue.

Contribution

It provides a comprehensive overview of the development, challenges, and potential future research directions in image retrieval techniques.

Findings

Shift from keyword to semantic features in image retrieval

Semantic gap remains a major challenge

Discussion of user query mechanisms and gap bridging methods

Abstract

This paper attempts to discuss the evolution of the retrieval approaches focusing on development, challenges and future direction of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users' mind. Hence, introducing an interpretation inconsistency between image descriptors and high level semantics that known as the semantic gap. This paper also discusses the semantic gap issues, user query mechanisms as well as common ways used to bridge the gap in image retrieval.