Concise Computer Vision
An Introduction into Theory and Algorithms
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Application Software, Computer Graphics, General Computing
| Author: | Reinhard Klette | ISBN: | 9781447163206 |
| Publisher: | Springer London | Publication: | January 4, 2014 |
| Imprint: | Springer | Language: | English |
| Author: | Reinhard Klette |
| ISBN: | 9781447163206 |
| Publisher: | Springer London |
| Publication: | January 4, 2014 |
| Imprint: | Springer |
| Language: | English |
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.
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.
