Machine vision comprises three integrated processes: acquisition, preprocessing, and image analysis. While many resources discuss application-specific image analysis, there has been no unified account of image acquisition hardware and preprocessing - until now. This is a comprehensive, exhaustive reference text detailing every aspect of acquisition and preprocessing, from the illumination of a scene to the optics of image forming, from CCD and CMOS image capture to the transformation of the captured image.

• Readers will gain an understanding of the optical technology, material science, and semiconductor device technology behind image acquisition devices • Research on image information is stable but slowly growing and several universities globally teach related courses for which this is valuable supplementary reading • This book offers a unique focus on the devices used in image sensors and displays

MV engineering is a truly multidisciplinary area and perhaps because of this, it is plagued with imprecise jargon. This book attempts to collect the fundamental concepts into a single, well-integrated, self-consistent exposition that will serve as a relatively painless introduction to the field of MV Engineering. The ultimate goal is an enlightened practitioner capable of using this powerful new technology effectively.

Image Acquisition and Processing With LabVIEWä combines the general theory of image acquisition and processing, the underpinnings of LabVIEW and the NI Vision toolkit, examples of their applications, and real-world case studies in a clear, systematic, and richly illustrated presentation. Designed for LabVIEW programmers, it fills a significant gap in the technical literature by providing a general training manual for those new to National Instruments (NI) Vision application development and a reference for more experienced vision programmers. The downloadable resources contain libraries of the example images and code referenced in the text, additional technical white papers, a demonstration version of LabVIEW 6.0, and an NI IMAQ demonstration that guides you through its features. System Requirements: Using the code provided on the downloadable resources requires LabVIEW 6.1 or higher and LabVIEW Vision Toolkit 6.1 or higher. Some of the examples also require IMAQ Vision Builder 6.1 or higher, the IMAQ OCR toolkit, and IMAQ 1394 drivers.

Bogen er en grundlæggende lærebog om digital mammografi, hvori digital mammografi og traditionel mammografi også sammenlignes i forhold til screening, diagnoser og radiografisk billedteknik. Der er en komplet billedsamling af cases indenfor digital mammografi.

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics together. By improving readers’ knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The last part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry.

The video digitizer project. Classical image processing. Additional information.