Neural Network And Entropy Algorithms For Edge Detection In SAR Images

Mohamed A. El-Sayed (u. a.)

ISBN 10: 3659926698 / ISBN 13: 9783659926693

Published by LAP LAMBERT Academic Publishing, 2016

About this Item

Neural Network And Entropy Algorithms For Edge Detection In SAR Images | Mohamed A. El-Sayed (u. a.) | Taschenbuch | 136 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659926693 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 103480430

Bibliographic Details

• Title: Neural Network And Entropy Algorithms For Edge Detection In SAR Images
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 3659926698
• ISBN 13: 9783659926693
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 221 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Edges detection of digital images is used in a various fields of applications ranging from real-time video surveillance and traffic management to Synthetic Aperture Radar (SAR) imaging applications. It can be used in many applications such as segmentation, registration, feature extraction, and identification of objects in a scene. This book deals with the different types of applications of edge detection in real life. It presents a brief study of the fundamental concepts of the edge detection operation, and theories behind different edge detectors. Edge detection models based on first and second order derivatives are presented. Previous works on edge detection models are reviewed and simulated in Matlab. It shows an initial exploration of the effectiveness of using Convolutional Neural Networks (CNNs) for this task. CNNs exploit spatially local correlation by enforcing a local connectivity pattern between neurons of adjacent layers. These techniques are object-independent so that the proposed method can be applied to other types of image processing such as classification and segmentation.

About the Author

Dr. Mohamed A. El-Sayed has obtained his PhD degree in Computer Science in 2007. His research interests include image processing. He is the author of several books and articles published in reputed journals and is a member of different working groups. He is working in Fayoum Univ., Egypt. Currently, he is an As. Prof. at Taif Univ., Saudi Arabia.