KEYWORD AND IMAGE CONTENT FEATURES FOR IMAGE INDEXING AND RETRIEVAL WITHIN COMPRESSED DOMAIN
ABSTRACT: The central problem
of most Content Based Image Retrieval approaches is poor quality in terms of
sensitivity (recall) and specificity (precision). To overcome this problem, the
semantic gap between high-level concepts and low-level features has been
acknowledged. In this paper we introduce
an approach to reduce the
impact of the
semantic gap by
integrating high-level (semantic)
and low-level features
to improve the quality
of Image Retrieval
queries. Our experiments
have been carried
out by applying
two hierarchical procedures. The first approach is called
keyword-content, and the second content-keyword. Our proposed approaches show better results
compared to a single method (keyword or content based) in term of recall and
precision. The average precision has increased by up to 50%.
Author: Irianto, Y. Suhendro
Journal Code: jptinformatikagg090003
