Special Issue "Image Based Information Retrieval from the Web"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: 30 August 2018

Special Issue Editors

Guest Editor
Prof. Dr. Phivos Mylonas

Department of Informatics, Ionian University, P.C. 49100, Corfu, Greece
Website | E-Mail
Interests: knowledge management and acquisition; context representation and analysis; content-based information retrieval; knowledge-assisted multimedia analysis; multimedia personalization; user adaptation; user modeling and profiling
Guest Editor
Prof. Dr. Evaggelos Spyrou

Department of Computer Engineering, Technological Educational Institute of Central Greece, P.C. 35100, Lamia, Greece
Website | E-Mail
Interests: computer vision; pattern recognition; semantic multimedia analysis; indexing and retrieval; multimedia content representation; biomedical image analysis

Special Issue Information

Dear Colleagues,

In recent years, following the tremendous growth of the Web, extremely large amounts of digital multimedia content are being produced every day and are shared online, mainly through several newly-emerged channels, such as social networks. Moreover, several digital content archives and datasets have become publicly available. Therefore, the field of image-based information retrieval has received a great deal of attention and on a wide range of topics dealing with every aspect of content handling. When designing and implementing an image-based retrieval system, and considering the continuous growth of digital content, one has to deal with several issues such as efficiency, accuracy, scaling, user-friendliness, and impact.

The intent of this Special Issue is to collect the experiences of leading scientists, but also to serve as an assessment tool for people who are new to the world of image-based information retrieval.

This Special Issue is intended to covering the following topics, but is not limited to them:

  • Feature extraction from visual content
  • Multimodal information fusion
  • 2D/3D detection, categorization and recognition
  • Scene recognition
  • Image and video retrieval, annotation, indexing
  • Datasets construction and analysis
  • Social media analysis, interaction and retrieval
  • Multimedia representation
  • Efficient large-scale image/video search
  • Deep learning techniques for detection and classification
  • Interfaces for querying, retrieval, exploration and visualization of multimedia databases
  • Applications and systems for image/video-based information retrieval
  • User-centric social multimedia computing
  • Personalized multimedia search
  • Semantic-based multimedia big data retrieval

Prof. Dr. Phivos Mylonas
Prof. Dr. Evaggelos Spyrou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Information retrieval
  • Multimedia content
  • Detection
  • Recognition
  • Classification
  • Fusion

Published Papers (1 paper)

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Open AccessArticle Efficient Implementation of Gaussian and Laplacian Kernels for Feature Extraction from IP Fisheye Cameras
J. Imaging 2018, 4(6), 73; https://doi.org/10.3390/jimaging4060073
Received: 1 May 2018 / Revised: 15 May 2018 / Accepted: 17 May 2018 / Published: 24 May 2018
PDF Full-text (11031 KB) | HTML Full-text | XML Full-text
The Gaussian kernel, its partial derivatives and the Laplacian kernel, applied at different image scales, play a very important role in image processing and in feature extraction from images. Although they have been extensively studied in the case of images acquired by projective
[...] Read more.
The Gaussian kernel, its partial derivatives and the Laplacian kernel, applied at different image scales, play a very important role in image processing and in feature extraction from images. Although they have been extensively studied in the case of images acquired by projective cameras, this is not the case for cameras with fisheye lenses. This type of cameras is becoming very popular, since it exhibits a Field of View of 180 degrees. The model of fisheye image formation differs substantially from the simple projective transformation, causing straight lines to be imaged as curves. Thus the traditional kernels used for processing images acquired by projective cameras, are not optimal for fisheye images. This work uses the calibration of the acquiring fisheye camera to define a geodesic metric for distance between pixels in fisheye images and subsequently redefines the Gaussian kernel, its partial derivatives, as well as the Laplacian kernel. Finally, algorithms for applying in the spatial domain these kernels, as well as the Harris corner detector, are proposed, using efficient computational implementations. Comparative results are shown, in terms of correctness of image processing, efficiency of application for multi scale processing, as well as salient point extraction. Thus we conclude that the proposed algorithms allow the efficient application of standard processing and analysis techniques of fisheye images, in the spatial domain, once the calibration of the specific camera is available. Full article
(This article belongs to the Special Issue Image Based Information Retrieval from the Web)

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Topic: The Development of A Methodology for Extracting Characterizations/Categorizations of The Urban Environment Using Sources Like Google Maps And Street View
Authors: Anastasios Delopoulos and Christos Diou
Affiliation: School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece

Title: Recent Trends And Case Studies in Image Indexing and Retrieval
Authors: Sule Yildirim Yayilgan, Claudia Companioni Brito, Zygred Calibjo, Lissete Paiz, Nadile Nudes and LAM Yat Hong
Affiliation: Norwegian University of Science and Technology, Norway

Title: An Ensemble SSL Algorithm for Efficient Chest X-rays Image Classification
Authors: Ioannis Livieris1, Andreas Kanavos1, Vassilis Tampakas1, Panagiotis Pintelas2
1 Computer & Informatics Engineering Department, Technological Educational Institute of Western Greece, Antirrion, Greece
2 Department of Mathematics, University of Patras, Greece

Title: Efficient Implementation of Gaussian and Laplacian Kernels for Feature Extraction of Image Sequences from IP Fisheye Cameras
Author: Kostas Delibasis 
Affiliation: Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece

Topic: Photogrammetric Reconstruction Using Photos Mined from Large Internet Collections
Authors: Stamatis Chatzistamatis, Christos-Nikolaos Anagnostopoulos, George E. Tsekouras, Dimitrios Makris
Affiliation: Department of Cultural Technology and Communication, University of the Aegean, Greece
                  Department of Computer Science, Kingston University London, UK

Title: Digital comics image indexing based on deep learning
Authors: Nhu Van Nguyen, Christophe Rigaud, Jean-Christophe Burie
Affiliation: University of La Rochelle, France

Author: Mahmudur Rahman
Affiliation: Department of Computer Science, Morgan State University, USA

Author: Spyros Sioutas
Affiliation: Department of Informatics, School of Information Sciences and Informatics, Ionian University, Greece

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