Application of Semantic Image Analysis to Intelligent Image Retrieval

Abstract

The field of computer vision is seeing unprecedented growth, and one of its most fascinating subfields is image interpretation
and analysis. The effective analysis and retrieval of semantic images is made possible by modern computer vision techniques
and technology. Images, estimating formulas, and sample densities are the main topics of image analysis. When we do semantic
level image analysis, we can automatically extract descriptions of images based on how humans see them. This helps to close
the semantic gap between basic visual characteristics and the abstract ideas that capture their meaning. The content of images,
particularly significant objects inside them and the relationships between them, is the primary source for retrieving crucial semantic
picture information. We begin with an analysis of the image’s content in light of semantic concepts, then build a database
and knowledge base for images based on their semantic content and retrieval, and finally present and modify the database and
knowledge base for the purpose of knowledge delivery. Image retrieval performance and accuracy are both enhanced according
to the experimental results.