An Introduction to Image Processing and Artificial Intelligence


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A presentation introducing image processing and artificial intelligence

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An Introduction to Image Processing and Artificial Intelligence

  2. 2. What is an Image? In literature terms: Image is a word or phrase that directs to taste, sound, hear, sight, smell In general term: Image is a picture expressing ones self In computer science an image is an exact replica of the contents of a storage device stored on a second storage device
  3. 3. What is Image Processing? Analyzing and manipulating images with a computer. Image processing generally involves three steps: 1. Import an image with an optical scanner or directly through digital photography. 2. Manipulate or analyze the image in some way. This stage can include image, enhancement and data compression, or the image may be analyzed to find patterns that aren't visible by the human eye. For example, meteorologists use image processing to analyze satellite photographs. 3. Output the result The result might be the image altered in some way or it might be a report based on analysis of the image.
  4. 4. What is Noise? Image noise is the random variation of brightness or color information in images produced by the sensor and circuitry of a scanner or digital camera.
  5. 5. How to Remove Noise from Images An edge-sensitive noise reduction algorithm for digital image processing is proposed. It is designed as C-DLL to run as a macro command under Image-Pro Plus. Its properties are compared to the median filter and a simple smoothing kernel.
  6. 6. Color Enhancement Methods of electronically enhancing one or more color components (C, Y, M) which together represent the chromatic components of a pixel of an image.
  7. 7. Color Enhancement
  8. 8. Sharpening In Image Sharpening is an image-manipulation technique for making the outlines of a digital image look more distinct. Sharpening increases the contrast between edge pixels and emphasizes the transition between dark and light areas. Sharpening increases local contrast and brings out fine detail. There is no strict formula for correctly sharpening all images. Too little sharpening can make for a soft image, but over-sharpening adds noise. Methods of Sharpening the Image Gradient Operator Laplacian operator
  9. 9. Sharpening
  10. 10. Segmentation
  11. 11. Segmentation
  12. 12. Segmentation
  13. 13. Edge Detection Egg Detection
  14. 14. Feature Detection & Recognition
  15. 15. Representation Issues
  16. 16. Questions & Answers
  17. 17. References vision_tutorial_pt3.shtml