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ICSES Transactions on Image Processing and Pattern Recognition
Vol. 4, No. 4, Dec. 2018

ImgSeg2018: Cover Page, Bibliography, Preface and Table of Contents

Hamid Reza Boveiri a,mail_outline, Vikramsingh Parihar b
a Sama College, IAU, Shoushtar Branch, Shoushtar, Iran
b PRMCEAM, Amravati, India


Highlights and Novelties
1- First of all, this book will prove as a center of knowledge for recent image segmentation and image mining techniques and their advancement and contribution in the field of image processing.

2- Secondly, few methods are provided with their in-depth working and simulations. Rigorous analysis is done on them and each and every happening is thoroughly explained.

3- Thirdly, an exhaustive literature review is done and detailed knowledge of various important and noteworthy contributions in the image processing field is mentioned.

4- This book is intended to give basic and detailed knowledge of image segmentation techniques to those who are willing to understand, study and contribute in digital image processing field.


Manuscript Abstract
Today, the medical industry, astronomy, physics, chemistry, forensics, remote sensing, manufacturing, and defense are just some of the many fields that rely upon images to store, display, and provide information about the world around us. The challenge to scientists, engineers and business people is to quickly extract valuable information from raw image data. This is the primary purpose of image processing - converting images to information. The main aim of image segmentation is to identify meaningful objects from a given image. For example, a boy of just four years can see/detect/locate a pen on a table, as he is naturally equipped with image segmentation power. However, robots cannot do it, until they use image segmentation algorithms. To perform an image segmentation task, several techniques have been developed. The simplest and flexible techniques are discussed in this book from basics. This book explains how to segment images using state-of-the-art methods and recent innovations incorporating Deep Learning. Also, image segmentation is usually the first step towards various image processing applications like medical imaging, object detection, machine vision, recognition, image mining, image restoration, image enhancement, etc. and thus, is a critical topic to study. In this book, each chapter introduces image segmentation topics and includes information regarding when one method may be preferred over another to obtain specific image features. Numerous step-by-step examples illustrate the processing and analysis routines, allowing you to quickly understand how to get the desired results when working with your own image data. This book is not intended to be a complete source for image processing knowledge, an advanced image processing manual or an image processing reference guide. This book is designed to teach people how to segment images effectively and does not assume that they are already experts in the field of image processing.


 Deep Learning   Image Processing   Image Segmentation Image Segmentation Applications   Image Segmentation Innovations   Medical Image Segmentation   Object Detection 


Copyright and Licence
Copyright © International Computer Science and Engineering Society (ICSES). This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution Non Commercial 4.0 International (CC BY-NC 4.0) license, supported by creativecommons.orgcall_made


Cite this manuscript as
Hamid Reza Boveiri, Vikramsingh Parihar, "ImgSeg2018: Cover Page, Bibliography, Preface and Table of Contents," ICSES Transactions on Image Processing and Pattern Recognition, vol. 4, no. 4, pp. 1-6, Dec. 2018.


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Manuscript ID: 241
Pages: 1-6
Submitted: 2018-12-30
Accepted: 2018-12-30
Published: 2018-12-30

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Journal's Title
ITIPPR Cover Page


ICSES Transactions on Image Processing and Pattern Recognition
ISSN: 2645-8071

ISSN: 2645-8071
Frequency: Quarterly
Accessability: Online - Open Access
Founded in: Mar. 2015
Publisher: ICSES
DOI Suffix: 10.31424/icses.itippr