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Journal of Electronic Imaging Special Section Calls for Papers

To submit manuscripts for consideration in a Special Section, please prepare the manuscript according to the journal guidelines and use the Online Submission System.Leaving siteA cover letter indicating that the submission is intended for this special section should be included with the paper. Papers will be peer‐reviewed in accordance with the journal's established policies and procedures. Authors who pay the voluntary page charges will receive the benefit of open access.

View the list of special sections that have already been published on the SPIE Digital Library. 


Ultrawide Context- and Content-Aware Imaging

Quality Control by Artificial Vision: Nonconventional Imaging Systems

Advances on Distributed Smart Cameras

Intelligent Surveillance for Transport Systems

Color in Texture and Material Recognition

September-October 2015

Ultrawide Context- and Content-Aware Imaging

Guest Editors:

François Brémond
INRIA Sophia Antipolis
2004 Rte des Lucioles - BP 93
Sophia Antipolis 06902, France
E-mail: Francois.Bremond@inria.fr

Ljiljana Platiša
Ghent University
Department of Telecommunications and Information Processing
Research Group for Image Processing and Interpretation (IPI/iMinds)
Sint-Pietersnieuwstraat 41
Ghent 9000, Belgium
E-mail: Ljiljana.Platisa@telin.ugent.be

Sebastiano Battiato
University of Catania
Dipartimento di Matematica e Informatica
Viale Andrea Doria 6
Catania 95125, Italy
E-mail: Battiato@dmi.unict.it

Call for Papers: Breakthrough technologies are needed to make emerging imaging applications-such as 3-D/4-D imaging in healthcare, high-definition TV, broadcasting, and multicamera systems in surveillance-handle increasingly demanding requirements concerning reliability and speed of automated image analysis (e.g., person identification in a surveillance system). In addition, advancements are needed to improve the success rate and comfort for humans using images for a particular task, such as performing a laparoscopic surgery. Future imaging systems will have to be much more intelligent about what data to acquire (e.g., automatic region of interest detection) and how to optimally image it based on the image content. Moreover, the systems need to become more context aware, for example, accounting for the presence of other cameras in the systems, and contribute to the joint optimization of the imaging system given the environment in which they are used.

This special section will focus on new developments that may speed up the transition towards intelligent imaging, ranging from intelligent sensors to control systems in various domains, including healthcare, broadcasting, and surveillance.

We invite submissions of original unpublished research contributions on, but not limited to, the following topics:

  • Smart cameras and detectors
  • Joint optimization of multicamera systems
  • Simplified representations of multiple video streams
  • Multicamera content identification and tracking
  • Multisource and multimodality image acquisition, processing, and data fusion
  • Object detection, classification, and tracking
  • Image and video understanding
  • Real-time image and video processing algorithms
  • Subjective and objective image and video quality assessment.

Closed for submissions.


November-December 2015

Quality Control by Artificial Vision: Nonconventional Imaging Systems

Guest Editors:

Fabrice Mériaudeau
Université de Bourgogne - LE2I - UMR CNRS 6306
12 rue de la Fonderie
71200 Le Creusot, France
E-mail: fabrice.meriaudeau@u-bourgogne.fr

Aamir Saeed Malik
Universti Teknologi Petronas
Centre for Intelligent Signal and Imaging Research
Department of Electrical and Electronic Engineering
Tronoh, Malaysia
E-mail: aamir_saeed@petronas.com.my

Call for Papers: Artificial vision relates to the application of computers, sensors, methods, and networks to view and interpret the world through the "eyes" of a machine. Research and development in artificial vision has made tremendous strides over the last decade moving from "gray level" passive systems to nonconventional (polarization information, multispectral systems, plenoptic systems, 3-D systems, infrared systems, RGB-D systems) active systems, enabling perception of more information about the scene. Meanwhile, processing has greatly benefited from the advances in the semiconductor industry, and greedy resources applications can now be harnessed through powerful computers, dedicated CMOS chips, networks, or graphic cards. Many advances in manufacturing/CAD have required tremendous corresponding advances in metrology, inspection, and data interpretation for process characterization and control that rely on the fundamental methods and technologies of artificial vision.

This special section welcomes papers on, but not limited to, the following topics:

  • Vision sensor development and integration
  • Optical, electron, x-ray, polarization imaging, ultrasound, and other nonconventional imaging modalities
  • Nondestructive testing and metrology
  • Image processing, transforms, segmentation, and pattern recognition
  • Process automation, characterization, and control
  • Remote diagnostics
  • Computer-aided diagnosis
  • 3-D vision for manufacturing inspection.

There are many industries that are benefiting from artificial vision today. Papers are particularly encouraged from, but not limited to, the following industries: agriculture, aluminum, biomedical, chemicals, food, forest products, glass, metal casting, mining, petroleum, pharmaceuticals, semiconductors, steel, textiles, medical imaging, and biomedical imaging.

Closed for submissions.


Distributed Smart Cameras

July-August 2016

Advances on Distributed Smart Cameras

Guest Editors:

Jorge Fernández-Berni
CSIC-Universidad de Sevilla
Instituto de Microelectrónica de Sevilla
C/ Americo Vespucio, s/n
41092 Sevilla, Spain
E-mail: berni@imse-cnm.csic.es

François Berry
Institut Pascal, CNRS
24 Avenue des Landais
63170 Aubière Cedex, France
E-mail: berry@univ-bpclermont.fr

Christian Micheloni
University of Udine
Department of Mathematics and Computer Science
Via delle Scienze 206
33100 Udine, Italy
E-mail: christian.micheloni@uniud.it

Call for Papers: Smart camera networks are becoming a fundamental piece of our intelligent cities, buildings, and homes, progressively inserting themselves in our lives, from smart surveillance systems composed of a multitude of smart camera nodes to small wearable cameras able to render a visual log of our daily experience. These devices interact with each other and with a wealth of other smart stuff, including of course the Internet. This rapid development is possible thanks to the convergence of several technologies: from advanced image sensors and vision chips to embedded vision systems capable of efficient feature extraction, image encoding, and wireless transmission of the relevant visual content. This opens the door to new application domains, where video analytics and the extraction of semantic information from the scene is performed in a distributed fashion, implementing a new type of cooperative and/or collaborative vision, and even fusing visual information with other sensory data.

This special section of the Journal of Electronic Imaging is aimed to bring together the works of many experts in this multidisciplinary field, including selected works from the 2015 edition of the International Conference on Distributed Smart Cameras (ICDSC). The special section serves to highlight advances in the many fields involved, from image sensors and dedicated real-time image processing hardware to high-level information processing and smart camera networks.

Relevant topics for this special section include:

Smart image sensors and vision chips

  • Circuits and systems for image sensing
  • Parallel processing hardware
  • Hardware/software codesign for embedded vision
  • Reconfigurable vision-processing arch
  • High-performance image sensors

Emerging applications and case studies

  • Vision-based smart environments
  • Surveillance and tracking applications
  • Distributed multimedia and gaming apps
  • Position discovery and middleware apps
  • Context-aware networks
  • Sports

Smart camera and network architectures

  • Camera system designs and architectures
  • Image sensing/processing for smart cameras
  • Architectures for camera networks
  • Embedded vision programming
  • Distributed video coding

Mobile vision

  • Crowdsourcing
  • Sensing for mixed/augmented reality
  • Structure-from-motion in mobile devices
  • Visual landmark localization
  • Object recognition
  • Egovision

Distributed computer vision

  • Distributed video analytics
  • Resource management and task allocation
  • Multisensor data aggregation
  • Collaborative extraction, information fusion
  • Edge and cloud computing

Visual sensor networks

  • Active vision
  • Self-reconfiguring camera networks
  • Wireless and mobile image sensor networks
  • Topology discovery
  • Social media and big data.

Manuscripts due 31 December 2015.



September-October 2016

Intelligent Surveillance for Transport Systems

Guest Editors:

Louahdi Khoudour
CEREMA: Center for Studies and Expertise on Risks, Environment, Mobility, and Urban and Country Planning
Southwest Territorial Division
1, avenue du Colonel Roche
31400 Toulouse, France
E-mail: louahdi.khoudour@cerema.fr

Yassine Ruichek
University of Technology of Belfort-Montbéliard
Research Institute on Transportation, Energy and Society
Systems and Transportation Laboratory
90010 Belfort, France
E-mail: yassine.ruichek@utbm.fr

Sergio Velastin
Universidad Carlos III de Madrid
Department of Computer Science
E-mail: sergio.velastin@iee.org

Call for Papers: Transport operators are facing increasing demands for improved efficiency, safety, and security from the general public as well as from governments. Increasing the use of public transport is also consistent with improving the environment. An important part of the efforts deployed to meet these demands is the ever-increasing use of video surveillance cameras and other sensors throughout transportation networks (roads, rail, public transport, maritime), to monitor the flow of passengers, cars, and trains to enable staff to be informed of possible congestion, and detect incidents or potential incidents without delay. To effectively handle the scale and complexity required in real-world systems, the cameras and sensors also need to be coupled with intelligent processing and inference algorithms. Recent years have seen significant research in these areas addressing road traffic measurement, automatic incident detection, counterflow, etc.

This special section of JEI will highlight the state of the art in this exciting area through contributions from transportation, computer vision, image processing, and other communities. A key goal of this special section is to foster interaction among academia and industry and promote the development of cutting-edge ideas related to research issues for intelligent surveillance for transport systems. Topics of interest include, but are not limited to:

  • Automatic incident detection on roads: cars stopped, obstacle detection
  • Counterflow detection
  • Automatic incident detection on rail networks
  • Human behavior analysis in public transport
  • Sensor networks
  • Automatic traffic measurement and classification
  • Risk and safety analysis, cost-benefit evaluation
  • Sensing, data processing, and fusion
  • Distributed multimodal scene analysis and event interpretation
  • Modeling and tracking
  • Simulation, implementation, test beds, and field tests
  • Performance evaluation metrics
  • Real-time architectures for intelligent surveillance systems
  • Data mining
  • Human factors, behavior modeling.

Manuscripts due 20 December 2015.


November-December 2016

Color in Texture and Material Recognition

Guest Editors:

Raimondo Schettini
University of Milan-Bicocca
Department of Informatics, System and Communication
Viale Sarca 336
20126 Milan, Italy
E-mail: schettini@disco.unimib.it

Joost van de Weijer
Universitat Autònoma de Barcelona
Centre de Visió per Computador
Edifici O, Campus UAB
08193 Bellaterra, Cerdanyola, Spain
E-mail: joost@cvc.uab.es

Claudio Cusano
University of Pavia
Department of Electrical, Computer, and Biomedical Engineering
Via A. Ferrata, 5
27100 Pavia, Italy
E-mail: claudio.cusano@unipv.it

Paolo Napoletano
University of Milan-Bicocca
Department of Informatics, System and Communication
Viale Sarca 336
20126 Milan, Italy
E-mail: paolo.napoletano@disco.unimib.it

Call for Papers: Recognizing real-world materials in images is a challenging task due to the rich variations of lighting conditions, appearance, and surface properties. Color and textures are important components of material appearance.

The study of texture and material recognition have a long history in image analysis and computer vision. Recent works that deal with large collections of images taken from the Internet or that exploit large-scale machine learning techniques have renewed the interest in these topics. The most relevant insight is that features from other domains, such as object recognition, may achieve comparable or sometimes better performance than those achieved with features specially designed for texture and material classification. Moreover, while for some artificial materials color and texture are independent properties, for natural materials they are strongly related. Whether or not color information is useful for texture and material classification is still an open issue, especially "in the wild," where imaging conditions such as lighting color and direction, orientation, sensor type, etc., are unpredictable.

This special section explores these topics by providing new insights for understanding color in texture and material recognition.

This special section covers different areas, including color science, computer vision, computer graphics, and machine learning. This is an open call for papers, soliciting original contributions in addition to selected works from the 2015 International Workshop on Color in Texture and Material Recognition (ICIAP-CTMR2015). Papers should address a wide range of theoretical and practical issues including, but not limited to:

  • Feature design: texture features, features from other domains, features obtained by deep learning
  • Color science: photometric invariants, color invariants, color saliency, color constancy
  • Vision science: color texture and material perception
  • Machine learning: feature selection algorithms and representation learning methods applied to texture and color
  • Performance evaluation: databases under controlled conditions, classification in the wild
  • Applications: remote sensing, medical imaging, food recognition, industrial inspection.

Submissions due 15 February 2016.


Published Special Sections:

Image/Video Quality and System Performance (November-December 2014)
Guest Editors: Mohamed-Chaker Larabi, Sophie Triantaphilliadou, and Andrew B. Watson

Stereoscopic Displays and Applications (January-February 2014)
Guest Editors: Nicolas Holliman and Takashi Kawai

Video Surveillance and Transportation Imaging Applications (Oct-Dec 2013)
Guest Editors: Robert Loce and Eli Saber

Compressive Sensing for Imaging (April-June 2013)
Guest Editors: Fauzia Ahmad, Gonzalo R. Arce, Ram M. Narayanan, Dimitris A. Pados

Mobile Computational Photography (January-March 2013)
Guest Editors: Todor Georgiev, Andrew Lumsdaine, Sergio Goma

Quality Control by Artificial Vision (April-June 2012)
Guest Editors: Jean-Charles Pinoli, Karen Panetta, and Seiji Hata

Stereoscopic Displays and Applications (January-March 2012)
Guest Editors: Neil Dodgson and Nick Holliman

Quality Control by Artificial Vision (September-December 2010)
Guest Editors: Edmund Y. Lam, Shaun S. Gleason, and Kurt S. Niel

Digital Photography (April-June 2010)
Guest Editors: Peter B. Catrysse and Sabine Süsstrunk

Image Quality (January-March 2010)
Guest Editors: Susan Farnand and Frans Gaykema

Quality Control by Artificial Vision (July-September 2008)
Guest Editors: Hamed Sari-Sarraf, David Fofi, and Nelson H. C. Yung

Biometrics: Advances in Security, Usability, and Interoperability (January-March 2008)
Guest Editors: Claus Vielhauer, Berrin Yanikoğlu, Sonia Garcia-Salicetti, Richard M. Guest, and Stephen J. Elliott

Security, Steganography, and Watermarking of Multimedia Contents (October-December 2006)
Guest Editors: Jana Dittmann and Edward J. Delp

Color Imaging: Processing, Hard Copy, and Applications (October-December 2006)
Guest Editors: Reiner Eschbach and Gabriel Marcu

Quality Control by Artificial Vision (July-September 2004)
Guest Editors: Kenneth W. Tobin, Fabrice Meriaudeau, and Luciano da Fontoura Costa

Retinex at 40 (January-March 2004)
Guest Editors: John J. McCann

Imaging through Scattering Media (October-December 2003)
Guest Editors: David A. Boas, Charles A. Bouman, and Kevin J. Webb

Model-Based Medical Image Processing and Analysis (January-March 2003)
Guest Editors: James C. Gee; Mostafa Analoui

Internet Imaging (October-December 2002)
Guest Editors: Giordano Beretta and Raimondo Schettini

Storage, Processing, and Retrieval of Digital Media (October-December 2001)
Guest Editors: Minerva M. Yeung, Chung-Sheng Li, Rainer Lienhart,and Boon-Lock Yeo

Process Imaging for Automatic Control (July-September 2001)
Guest Editors: David M. Scott and Hugh McCann

Statistical Issues in Psychometric Assessment of Image Quality (April-June 2001)
Guest Editors: John C. Handley and John Bunge

Human Vision and Electronic Imaging (January-March 2001)
Guest Editors: Bernice E. Rogowitz, Thrasyvoulos N. Pappas, and Jan P. Allebach

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