Fr. 192.00

Advances In Machine Vision: Strategies And Applications

English · Hardback

Shipping usually takes at least 4 weeks (title will be specially ordered)

Description

Read more










This book describes recent strategies and applications for extracting useful information from sensor data. For example, the methods presented by Roth and Levine are becoming widely accepted as the 'best' way to segment range images, and the neural network methods for Alpha-numeric character recognition, presented by K Yamada, are believed to be the best yet presented. An applied system to analyze the images of dental imprints presented by J Côté, et al. is one of several examples of image processing systems that have already been proven to be practical, and can serve as a model for the image processing system designer. Important aspects of the automation of processes are presented in a practical way which can provide immediate new capabilities in fields as diverse as biomedical image processing, document processing, industrial automation, understanding human perception, and the defence industries. The book is organized into sections describing Model Driven Feature Extraction, Data Driven Feature Extraction, Neural Networks, Model Building, and Applications.

Product details

Assisted by Colin Archibald (Editor), Emil Petriu (Editor)
Publisher World Scientific Publishing Company
 
Languages English
Product format Hardback
Released 01.04.1992
 
EAN 9789810209766
ISBN 978-981-02-0976-6
No. of pages 380
Series World Scientific Series In Computer Science
World Scientific Series In Computer Science
World Scientific Computer Scie
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT

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.