Fr. 69.00

Video Text Detection

English · Hardback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more

This book presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems. Features: explains the fundamental theory in a succinct manner, supplemented with references for further reading; highlights practical techniques to help the reader understand and develop their own video text detection systems and applications; serves as an easy-to-navigate reference, presenting the material in self-contained chapters.

List of contents

Introduction to Video Text Detection.- Video Pre-Processing.- Video Caption Detection.- Text Detection from Video Scenes.- Post-Processing of Video Text Detection.- Character Segmentation and Recognition.- Video Text Detection Systems.- Script Identification.- Text Detection in Multi-modal Video Analysis.- Performance Evaluation.

About the author










Dr. Tong Lu is an Associate Professor in the Department of Computer Science and Technology, and a member of the State Key Lab for Novel Software and Technology at Nanjing University, China.
Dr. Shivakumara Palaiahnakote is a Senior Lecturer in the Faculty of Computer Science and Information Technology at the University of Malaya, Kuala Lumpur, Malaysia.
Dr. Chew Lim Tan is a Professor in the School of Computing at the National University of Singapore.
Dr. Wenyin Liu is a Senior Research Fellow and Associate Director of the Multimedia Software Engineering Research Center at City University of Hong Kong.


Summary

This book presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems. Features: explains the fundamental theory in a succinct manner, supplemented with references for further reading; highlights practical techniques to help the reader understand and develop their own video text detection systems and applications; serves as an easy-to-navigate reference, presenting the material in self-contained chapters.

Product details

Authors Wenyin Liu, Ton Lu, Tong Lu, Shivakumar Palaiahnakote, Shivakumara Palaiahnakote, Chew Lim Tan
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 26.05.2014
 
EAN 9781447165149
ISBN 978-1-4471-6514-9
No. of pages 264
Dimensions 163 mm x 20 mm x 243 mm
Weight 526 g
Illustrations X, 264 p. 160 illus.
Series Advances in Pattern Recognition
Advances in Computer Vision and Pattern Recognition
Advances in Computer Vision and Pattern Recognition
Advances in Pattern Recognition
Subject Natural sciences, medicine, IT, technology > IT, data processing > Application software

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.