Digital Image Processing : An Algorithmic Introduction [3rd ed.] / Wilhelm Burger , Mark J. Burge

By:

Burger, Wilhelm

Contributor(s):

Burge, Mark J

Material type: Text

9783031057434

Subject(s):

DDC classification:

006.37 BurD3

Summary: This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated 3rd edition of the definitive textbook on Digital Image Processing has been completely revised and expanded with new content, improved illustrations and teaching material. Topics and features: Contains new chapters on fitting of geometric primitives, randomized feature detection (RANSAC), and maximally stable extremal regions (MSER). Includes exercises for most chapters and provides additional supplementary materials and software implementations at an associated website. Uses ImageJ for all examples, a widely used open source imaging environment that can run on allmajor platforms. Describes each solution in a stepwise manner in mathematical form, as abstract pseudocode algorithms, and as complete Java programs that can be easily ported to other programming languages. Presents suggested outlines for a one- or two-semester course in the preface. Advanced undergraduate and graduate students will find this comprehensive and example-rich textbook will serve as the ideal introduction to digital image processing. It will also prove invaluable to researchers and professionals seeking a practically focused self-study primer.

List(s) this item appears in: New Arrivals 15-30 November 2025, Vol. 06, Issue 31

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	Indian Institute of Technology Tirupati General Stacks	Computer Science	006.37 BurD3 (11650) (Browse shelf(Opens below))	Copy 01	Available	11650

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Previous	006.32 YEG/A Artificial Neural Networks	006.32 YEG/A Artificial Neural Networks	006.32 YEG/A Artificial Neural Networks	006.37 BurD3 (11650) Digital Image Processing : An Algorithmic Introduction [3rd ed.] /	006.37 DavA (11516) Advanced Methods and Deep Learning in Computer Vision /	006.37 HOW/L Learning OpenCV 4 Computer Vision with Python 3: Get to Grips with Tools, Techniques, and Algorithms for Computer Vision and Machine Learning [3rd ed.] /	006.37 SzeC2 (11601) Computers Vision : Algorithms and Applicaitons [2nd Ed.] /	Next

This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated 3rd edition of the definitive textbook on Digital Image Processing has been completely revised and expanded with new content, improved illustrations and teaching material.

Topics and features:

Contains new chapters on fitting of geometric primitives, randomized feature detection (RANSAC), and maximally stable extremal regions (MSER).
Includes exercises for most chapters and provides additional supplementary
materials and software implementations at an associated website.
Uses ImageJ for all examples, a widely used open source imaging environment that
can run on allmajor platforms.
Describes each solution in a stepwise manner in mathematical form, as abstract pseudocode algorithms, and as complete Java programs that can be easily ported to other programming languages.
Presents suggested outlines for a one- or two-semester course in the preface.

Advanced undergraduate and graduate students will find this comprehensive and example-rich textbook will serve as the ideal introduction to digital image processing. It will also prove invaluable to researchers and professionals seeking a practically focused self-study primer.

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