This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.
By:
Reinhard Klette Imprint: Springer London Ltd Country of Publication: United Kingdom Edition: 2014 ed. Dimensions:
Height: 235mm,
Width: 155mm,
Spine: 28mm
Weight: 7.545kg ISBN:9781447163190 ISBN 10: 1447163192 Series:Undergraduate Topics in Computer Science Pages: 429 Publication Date:20 January 2014 Audience:
Professional and scholarly
,
Undergraduate
Replaced By: 9781447174141 Format:Paperback Publisher's Status: Active
Dr. Reinhard Klette, FRSNZ, is a Professor at the Tamaki Innovation Campus of The University of Auckland, New Zealand. His numerous other publications include the Springer title Euclidean Shortest Paths: Exact or Approximate Algorithms.