ASCMLIP 2017 - ASCMLIP 2017 : Advances in Soft Computing and Machine Learning in Image Processing (Springer)

Advances in Soft Computing and Machine Learning in Image Processing
To be published by Intelligent Systems Reference Library by Springer
http://www.springer.com/series/8578
Introduction
Nowadays the use of digital images and videos has been extended to different fields as surveillance, manufacturing, medicine, agriculture, etc. They are easy to obtain from various environments, and it is necessary to recognize the objects contained in the scenes. In order to achieve this goal, several computational approaches have been developed. However, considering the technological advances problems as image size, noise, illumination and the ones proper from the scenes, it is necessary to develop new methodologies and improve the classical algorithms. On the other hand, a tendency is that the computer vision and image processing systems should be able to automatic extract the desired features for a particular task. Computational Intelligence (CI) approaches are alternative solutions to for automatic computer vision and image processing systems; they include the use of tools as machine learning and soft computing. Researchers from all over the world are working hard creating new algorithms that combine the methods provided by computational intelligence to solve the problems of image processing and computer vision.
This Book aims to provide a collection of high quality research works that address broad challenges in both theoretical and application aspects of soft computing and machine leering in image processing and computer vision. We invite colleagues to contribute original book chapters that will stimulate the continuing effort on the application of CI approaches to solve image-processing problems and computer vision problems.
We invite all researchers and practitioners who are developing algorithms, systems, and applications, to share their results, ideas, and experiences. Besides the main topic covering all related Soft Computing and Machine Learning in Image Processing
Topics of interest include, but are not limited to, the following:
? Machine Learning
? Computer vision
? Soft Computing
? Image processing
? Evolutionary Computation Algorithms
? Swarm Optimization
? Image thresholding
? Multilevel segmentation
? Object recognition
? Coding and compression
? Sampling and interpolation
? Quantization and halftoning
? Quality assessment
? Filtering and enhancement
? Morphology
? Edge detection and segmentation
? Feature extraction
? Quantum Image Processing
? Applications
Chapter Submission
Submitted manuscripts should conform to the standard guidelines of the Springer's book chapter format. Manuscripts must be prepared using Latex, Word is not accepted, and according to the Springer's svmlt template that can be downloaded from the (link). Manuscripts that do not follow the formatting rules will be ignored. They can be in WORD format just follow the Springer guidelines.
Prospective authors should send their manuscripts electronically to the following email address: (doliva-AT-ucm.es), with the subject title as: "Soft Computing and Machine Learning in Image Processing - Book Chapter" in PDF. 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 in Intelligent Systems Reference Library by Springer. More information about Intelligent Systems Reference Library can be found (here).
Publication Schedule
The tentative schedule of the book publication is as follows:
Deadline for paper submission: December 31, 2016 (Tentative)
First round notification: Feb. 15, 2017
Camera-ready submission: March 25, 2017
Publication date: 2nd quarter of 2017
Volume editors
Aboul Ella Hassanien
Scientific Research Group in Egypt (SRGE) www.egyptsceince.net
Faculty of Computers & Information, Cairo University, Cairo, Egypt
Email: aboitcairo-AT-gmail.com
Diego Oliva
Departamento de Ciencias Computacionales, Tecnológico de Monterrey, Campus Guadalajara, México. diego.oliva-AT-itesm.mx, doliva-AT-ucm.es
Departamento de Electrónica
Universidad de Guadalajara, CUCEI, México