'Feature Extraction and Image Processing' takes one of the prime targets of applied computer vision, feature extraction and uses it to provide an essential guide to the implementation of image processing and computer vision techniques.

If you're looking for an easy way to work fast in Photoshop CS2, congratulations, you've found it! Matt Kloskowski, Education and Curriculum Developer for the NAPP, shows you how to use the power of automation to instantly save time, money, and frustration. Once you master these powerful tools, you'll wonder how you ever got along without them. You'll learn how to: • Effectively use Adobe Bridge to manage your images • Add automation...

A comprehensive manual for everyone from the aspiring professional to the general enthusiast. Coverage of up-to-the-minute equipment (e.g., neutral density filters) is definitive. Includes tips on everything from what to shoot to how to get vivid colours from the computer screen to the final print.

This book shows you how to build real-time image processing systems all the way through to house automation. Find out how you can develop a system based on small 32-bit ARM processors that gives you complete control through voice commands. Real-time image processing systems are utilized in a wide variety of applications, such as in traffic monitoring systems, medical image processing, and biometric security systems. In Real-Time IoT Imaging with Deep...

Adobe Photoshop Classroom in a Book 2024 Release uses real-world, project-based learning to cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. For beginners and experienced users alike, you can follow the book from start to finish or choose only those lessons that interest you.

Providing a strong combination of practical instruction with visual inspiration, Digital Photography Essentials, covers the basics of photography, different ways to approach a subject, how to develop projects, and image manipulation.

This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms,...