| Edition |
4th ed. |
| Description |
1 online resource |
|
text txt rdacontent |
|
still image sti rdacontent |
|
computer c rdamedia |
|
online resource cr rdacarrier |
| Bibliography |
Includes bibliographical references and index. |
| Summary |
"Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, ""The main strength of the proposed book is the link between theory and exemplar code of the algorithms."" Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python". |
| Subject |
Computer vision.
|
|
Computer vision -- Mathematics.
|
|
Pattern recognition systems.
|
|
Image processing -- Digital techniques.
|
|
Vision par ordinateur.
|
|
Vision par ordinateur -- Mathématiques.
|
|
Reconnaissance des formes (Informatique)
|
|
Traitement d'images -- Techniques numériques.
|
|
digital imaging.
|
|
Computer vision
|
|
Image processing -- Digital techniques
|
|
Pattern recognition systems
|
| Added Author |
Aguado, Alberto S.
|
| Other Form: |
Print version: 0128149760 9780128149768 (OCoLC)1085211122 |
| ISBN |
9780128149775 (electronic bk.) |
|
0128149779 (electronic bk.) |
|
9780128149768 |
|
0128149760 |
| Standard No. |
AU@ 000066251599 |
|
AU@ 000068128697 |
|
UKMGB 019576772 |
|
