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IFDFIA 2015 : Image Feature Detectors: Foundations, Innovations, and Applications

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Link: http://staff.www.ltu.se/~ismawa/ifd/
 
When N/A
Where A Book by Springer
Submission Deadline TBD
Categories    image processing   invariant features   biometrics images   robust features
 

Call For Papers

Call for Book Chapters

http://staff.www.ltu.se/~ismawa/ifd/

Image Feature Detectors
Foundations, Innovations, and Applications

Aim and Scope:
Detectors of image interest points such as corner detectors, blob detectors, and edge detectors go long way back in time. Feature detectors are new model for selecting interest points in an image. Those selected points can be invariant to scale, shift, and rotation. Feature detectors have a wide scope of applications in computer vision, pattern recognition, object recognition and tracking, image retrieval and matching, classification, and video processing and mining. The most popular feature detectors encompass: Scale Invariant Feature Transform (SIFT), Speeded Up Robust Feature (SURF), and Features from Accelerated Segment Test (FAST). The principal aim of the book is to assemble an up-to-date body of knowledge documenting the major advances and key emerging trends in the feature detectors with respect to foundations, new directions, and applications. Moreover, studies which couple computational theories and algorithms with real-time applications of image features will be considered. The book covers a wide range of image features and feature detectors that find emerging application in biotechnology, industrial inspection, Internet applications, radar imaging, and object recognition. The book will cause a change to the literature on computer vision and machine learning. Besides, it is both a reference for engineers and scientists and a teaching resource by featuring survey chapters and research papers on image feature detectors. The book will provide comprehensive reviews of cutting–edge state-of-the-art algorithms, technologies, and applications, providing new insights into a range of fundamentally important topics in image processing, computer vision, and pattern recognition,which basically depend on image features and feature detectors. Topics of interest include, but are not limited to:

Foundations and Innovations
2D/3D feature detectors
Invariant feature detectors
Interest points detectors
Affine region detectors
Keypoints extraction
Feature robustness
Performance evaluation
Image feature extraction
Feature descriptors

Applications
Biometrics imaginary
Medical imaginary
Image retrieval
Video processing
Object tracking

Publication Schedule:
The tentative schedule of the book publication is as follows:
Deadline for chapter submission: December 15, 2014
First round notification : February 2, 2015
Second round submission: February 16, 2015
Final notification : March 1, 2015
Camera-ready submission : March 15, 2015
Publication date: Second quarter of 2015

Submission Procedure:
Submitted chapters should conform to the authors guidelines of the Springer's LNCS book chapter format mentioned on the book website. Chapters should be prepared using Latex, Microsoft Word is not recommended , and according to the Springer's "llncs2e" template that can be downloaded from the book website.
Prospective authors need to electronically submit their chapters using EasyChair submission system (See the book website). Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance. The accepted contributions will be published as a volume in the prestigious "Studies in Computational Intelligence" series by Springer. More information about "Studies in Computational Intelligence" and the authors instructions can be found on the book website.

Volume Editors:
Dr.: Ali Ismail Awad
Associate Senior Lecturer
Department of Computer Science, Electrical and Space Engineering
Luleå University of Technology
Luleå, Sweden
E-mail: ali.awad[at]ltu.se

Dr.: M. Hassaballah
Assistant Professor
Department of Mathematics
Faculty of Science
South Valley University
Qena, Egypt
E-mail: m.hassaballah[at]svu.edu.eg

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