Books+ Search Results

Fundamentals of Image Data Mining Analysis, Features, Classification and Retrieval

Title
Fundamentals of Image Data Mining [electronic resource] : Analysis, Features, Classification and Retrieval / by Dengsheng Zhang.
ISBN
9783030692513
Edition
2nd ed. 2021.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2021.
Physical Description
XXXIII, 363 p. 243 illus., 131 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This unique and useful textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments. Topics and features: Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms Develops many new exercises (most with MATLAB code and instructions) Includes review summaries at the end of each chapter Analyses state-of-the-art models, algorithms, and procedures for image mining Integrates new sections on pre-processing, discrete cosine transform, and statistical inference and testing Demonstrates how features like color, texture, and shape can be mined or extracted for image representation Applies powerful classification approaches: Bayesian classification, support vector machines, neural networks, and decision trees Implements imaging techniques for indexing, ranking, and presentation, as well as database visualization This easy-to-follow, award-winning book illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
July 12, 2021
Series
Texts in Computer Science,
Texts in Computer Science,
Contents
1. Fourier Transform
2. Windowed Fourier Transform
3. Wavelet Transform
4. Color Feature Extraction
5. Texture Feature Extraction
6. Shape Representation
7. Bayesian Classification
Support Vector Machines
8. Artificial Neural Networks
9. Image Annotation with Decision Trees.-10. Image Indexing
11. Image Ranking
12. Image Presentation
13. Appendix.
Also listed under
SpringerLink (Online service)
Citation

Available from:

Online
Loading holdings.
Unable to load. Retry?
Loading holdings...
Unable to load. Retry?