Corresponding Author: Hui-Hui Wang Department of Computing and Software Engineering, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia Email: [email protected] Abstract: This paper attempts to discuss the image query mechanisms and user needs for image retrieval. The explosive growth of image data leads to the need of research ...

More and more digitized art images are accumulated and expanded in our daily life and techniques are needed to be established on how to organize and retrieve them. Though content-based image retrieval (CBIR)made great progress, current low-level visual information based retrieval technology in CBIR does not allow users to search images by high-level semantics for art image retrieval. We propose...

ÐThe paper presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps for image retrieval systems. Step one of the review is image processing for retrieval sorted by color, t...

One of the biggest challenges in content based image retrieval is to solve the problem of “semantic gaps” between low-level features and high-level semantic concepts. In this paper, we aim to investigate various combinations of mid-level features to build an effective image retrieval system based on the bag-offeatures (BoF) model. Specifically, we study two ways of integrating the SIFT and LBP ...

With the detonative development of internet technologies in the web huge amount of images are available on the web. Large amount of research has been carried out on image retrieval since last few years. There is need for efficient and viable procedure to find visual information on demand. Recent research shows that there is semantic gap between low level features of image and semantic concepts ...

Author: Liam M. Mayron Title: Image retrieval using visual attention Institution: Florida Atlantic University Dissertation Advisor: Dr. Oge Marques Degree: Doctor of Philosophy Year: 2008 The retrieval of digital images is hindered by the semantic gap. The semantic gap is the disparity between a user’s high-level interpretation of an image and the information that can be extracted from an image...

A projection onto convex sets (POCS)-based annotation method for semantic image retrieval is presented in this paper. Utilizing database images previously annotated by keywords, the proposed method estimates unknown semantic features of a query image from its known visual features based on a POCS algorithm, which includes two novel approaches. First, the proposed method semantically assigns dat...

To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intraimage and inter-class semant...

In this paper a new method for image retrieval using high level semantic features is proposed. It is based on extraction of low level color, shape and texture characteristics and their conversion into high level semantic features using fuzzy production rules, derived with the help of an image mining technique. DempsterShafer theory of evidence is applied to obtain a list of structures containin...

Traditional methods of content-based image retrieval deal with the retrieval of images according to the similarity between them and the sample image in some low-level feature space such as color, shape and structure. But the relevant images satisfying user information need tend to have different distribution in the low-level feature space. In this case, the query image needs to be represented a...