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Introduction to Machine Vision l
Basic Algorithms for Machine Vision
Recognition of Shapes and Positions
4 other sections not shown
abnormal Akira Furuya algorithm automatic automation binary image brightness calculated character chips classification color computer vision configuration defect candidates defect-extraction circuit design pattern detected defect dilation dimensional direction-coded image distance distance transform edge Ejiri Electronics erosion example exclusive-OR executed extraction feature parameters filter general-purpose image processor gray-level image signal imaging device industrial applications input image inspection Japanese linear local-parallel m x n machine vision machine-vision system Mahalanobis distance mainframe computers matching Microcomputer microscopic multiprocessor multiprocessor image processor normal number of pixels object surface obtained original image output image parallel pattern-matching photomask pipeline pixel data pixels plane portions printed-circuit boards processing element production recognition recognized recursive filter resulting robot scan sensor sequentially shape shift register shown in Figure standard pattern stored subarea surface normals texture three-dimensional threshold tion TV camera two-dimensional local memory usually utilized wafer width window Yoda