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Enhancing Image Analysis: Techniques for Machine Vision Systems

Learn about the latest image acquisition and analysis techniques in machine vision systems, including resolution ability, contrast detection, windowing, thresholding, histogramming, edge detection, and local edge elements. Explore advanced methods like Roberts Cross-Operator and Filters for precise image processing.

carlosmiddleton
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Enhancing Image Analysis: Techniques for Machine Vision Systems

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  1. Machine Vision

  2. Image Acquisition> Resolution Ability of a scanning system to distinguish between 2 closely separated points.> ContrastAbility to detect shades of difference from pixel to pixel.The lowest quality machine vision system uses a simple two-state sensor that registers each pixel as being either black or white.

  3. Image Analysis Techniques > WindowingConcentrating vision system analysis on a small field of view to conserve computer resources of run time & storage. > ThresholdingReducing an image to binary black or white pixels. > HistogrammingA frequency histogram is constructed for the pixel counts at each level of gray accommodated by the system.

  4. Edge Detection > Binary Logic SearchGuide a search through an image, one pixel at a time, as the search finds an edge, it will follow it completely around the object. > Local Edge Elements Roberts Cross-Operator Template & Filters

  5. Roberts Cross-OperatorComputes the square root of the sum of the squares of the adjacent diagonal differences between pixel gray-scale values.

  6. FilterSmall template for finding a “Vertical” edge. -1 0 1 -1 0 1 -1 0 1Find the sum of products of each point in the image matrix with all points in the filter matrix.

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