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Overview Overview Matrix Computer Vision Aliases: machine vision image analysis image understanding computational vision Traditionally computer vision and machine vision imply endowing a computer or other machine with visual capabilities, suggesting robotics and other autonomous computer-guided devices Image analysis and image understanding generally refer to figuring out the content of images -- a part of computer vision but without the implication of the computer having immediate access to live video (seeing). Computational vision is starting to gain favor as a term that refers to the modeling of visual processes by computational means. Introduction to Image Processing Image Acquisition scanner, video camera, digital still camera Image Description Resolution, field-of-view, color depth, statistics, spatial-frequency content Image Storage file formats (TIF, TGA, BMP, GIF, JPG, IMG), HTML Image Processing manipulation, transformation, analysis Image Display output devices (video, print), figures in reports and theses, limitations Software for Image Processing XV (Unix) Lview, Microsoft Photo Editor, Adobe PhotoShop (Windows) Matlab C or Java routines for image processing image processing software packages Image Model Sampling and Quantization Types of pixels Relationships between pixels Imaging Geometry Color Achromatic images Color models Color coordinate systems Image Acquisition Image Acquisition refers to the creation of new images. Digitization, scanning, sampling Converting pictures to discrete (digital) form Reconstruction Digital reconstruction images from its projections. Examples: Computerized tomography, ultrasonic imaging, nuclear medicine. Computer Graphics software whose output is an image text editing programs (page composition) paint programs page layout compositing, overlaying images from several different sources Image Enhancement Point Processing Geometrical Operations Neighborhood Operations Image Transform Op
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