Edge detection - PowerPoint PPT Presentation
NPR Today
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Computer Vision. Spring 2006 15-385,-685 Instructor: S. Narasimhan Wean 5403 T-R 3:00pm – 4:20pm. Aliasing - Really bad in video. Text Aliasing. Edge Detection Lecture #7. Edge Detection. Convert a 2D image into a set of curves Extracts salient features of the scene
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Chapter 10: Image Segmentation. Digital Image Processing. Preview. Segmentation is to subdivide an image into its component regions or objects. Segmentation should stop when the objects of interest in an application have been isolated. Principal approaches.
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For Monday. No new reading No homework. Program 5. Any questions?. Generation. Producing a syntactically “good” sentence Interesting issues are largely in choices What vocabulary to use What level of detail is appropriate Determining how much information to include. Perception/Vision.
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Edge detection
Edge detection. You can find edges in images by subtracting adjacent pixel values: edges show up where they are different. Whether this works depends on how sharp the edges are. Printed letters are very, very sharp. Most stains are not.
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Chapter 10 Image Segmentation
Chapter 10 Image Segmentation. Image segmentation divides an image into regions that are connected and have some similarity within the region and some difference between adjacent regions. The goal is usually to find individual objects in an image.
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Image Segmentation – Edge Detection. Dr. Jiajun Wang School of Electronics & Information Engineering Soochow University. Image Segmentation - 1. Contents. Edge detection Gradient operators Edge linking Hough transform. Image Segmentation - 1. Revisit - Goals of image processing.
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Introduction to Digital Image Processing using MATLAB. Lecture 11 Image Segmentation 2. By Dr. Khin Thu Zar Win Associate Professor Department of Mechatronic Engineering Yangon Technological University (YTU), Myanmar. Outline of Lecture. Edge Detection Edge Detection Filters.
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Edge detection of high temperature plasmas. Laurence Choi Sean Burke. Plasmas are all over the place. High temperature Often transient Major focus of energy research. UW has 3 major fusion expts. HSX MST Pegasus Short pulse periods Transient instabilities Equilibrium Calculations.
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Image Filtering. Problem!. Noise is a problem, even in images!. Gaussian Noise. Salt and Pepper Noise. What to do?. Try to think of ways to remove the noise!. Gaussian Noise. Salt and Pepper Noise. Smoothing. The most obvious and easy way to remove the noise is by averaging.
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