Author Description

In image retrieval system, machine understandability is a great quest. In a system giving an image as a query and retrieving semantically relevant image is a potential and promising research area. The main objective of this work is to reduce the semantic gap between low-level feature vector and high-level semantic information with respect to images. As humans we can make a machine understand an image if we provide both Syntactic and Semantic information regarding those images. Here the low-level feature of an image is said to be Syntactic feature information and the high-level description about the image is the Semantic information. Thus in this work an integration of Syntactic feature with Semantic information about the images has been used for Image retrieval System which can be implemented as a Multi-Modal Semantic Image Retrieval System.