Machine Vision and Digital Image Processing Fundamentals
How to apply machine vision technology and digital imaging to an industrial process. Coverage includes: lighting systems, economic aspects, dimensional errors due to quantification, RGB and CMYB color systems, filters, bar code systems. Annotation copyright Book News, Inc. Portland, Or.
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WHAT IS A VISION SYSTEM
FUNDAMENTAL CONCEPTS OF IMAGE
IMAGE ACQUISITION SIGNAL PARAMETERS
5 other sections not shown
adjacent pixels analog signal automated Back lighting bar code label bar code reader bars and spaces binary C-mount capability circle of confusion Codabar coefficients color contains convolution cost depth of field detector Determine digital imaging dimensions distance edge edge detection elements encoded enhance European Article example focal length format function high pass filter histogram human vision system illumination illustrated in Figure image data image matrix image plane image processing input image input matrix inspection integer Laplacian operator lens level system low pass filter machine vision system magnification manufacturing Matching points matrix q maximum measurement microseconds Monadic number of pixels object obtained output image output matrix parameters pixel area pixel location pixel value region represented sampling scan sensor array shown in Figure solid state camera specific structured light surface techniques template tion tube type camera unit Universal Product Code vision technology voltage zero