Image Segmentation 1st Edition

Grab the definitive guide to modern segmentation techniques with Image Segmentation (1st Edition) by Tao Lei and Asoke K. Nandi. This authoritative volume cuts through complexity to deliver clear, practical coverage of image segmentation fundamentals and advanced methods used across computer vision today.

Inside, readers will find a balanced mix of theory and practice: from classic approaches such as edge detection, region growing, and graph cuts to contemporary deep learning solutions for semantic and instance segmentation. Detailed explanations of algorithms, evaluation metrics, and performance trade-offs make complex concepts accessible for students, researchers, and industry practitioners. Real-world examples—spanning medical imaging, remote sensing, autonomous driving, and robotics—demonstrate how segmentation drives real applications across North America, Europe, and Asia.

What sets this book apart is its structured, pedagogical approach. Step-by-step derivations, comparative analyses, and clear illustrations help you understand not only how methods work, but when to apply them. Whether you’re a graduate student building a thesis, a data scientist developing vision pipelines, or an engineer integrating segmentation into Books, you’ll find actionable insights and practical guidance.

Packed with up-to-date techniques and written by respected authors in the field, Image Segmentation (1st Edition) is an essential resource for anyone serious about mastering image segmentation. Order your copy today to elevate your computer vision skills and bring precision segmentation to your projects worldwide.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.