@@ -60,27 +60,27 @@ MATLAB® is used throughout. Tools from the Image Processing Toolbox™, Compute
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6262# Scripts
63- ## [ ** IntrotoImageSegmentation ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/IntrotoImageSegmentation.mlx )
63+ ## [ ** Intro to Image Segmentation ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/IntrotoImageSegmentation.mlx )
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6666| <img src =" Images/image_3.png " width =" 171 " alt =" image_3.png " > <br > | ** In this script, students will...** <br > $\bullet$ examine three image segmentation methods. <br > $\bullet$ work through step\- by\- step examples of applying image segmentation. <br > $\bullet$ distinguish appropriate image segmentation technique based on scenario. <br > | ** Academic disciplines** <br > $\bullet$ Robotics <br > $\bullet$ Computer Vision <br > $\bullet$ Image Processing <br > |
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68- ## [ ** EdgeDetectionTheory ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/EdgeDetectionTheory.mlx )
68+ ## [ ** Edge Detection Theory ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/EdgeDetectionTheory.mlx )
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7171| <img src =" Images/image_4.png " width =" 171 " alt =" image_4.png " > <br > | ** In this script, students will...** <br > $\bullet$ identify and describe the characteristics and sources of edges. <br > $\bullet$ characterize edges in 1D and 2D. <br > $\bullet$ detect edges amid noise. <br > | ** Academic disciplines** <br > $\bullet$ Computer Vision <br > $\bullet$ Image Processing <br > $\bullet$ Medical Imaging <br > <br > |
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73- ## [ ** EdgeDetectionApplied ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/EdgeDetectionApplied.mlx )
73+ ## [ ** Edge Detection Applied ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/EdgeDetectionApplied.mlx )
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7676| <img src =" Images/image_5.png " width =" 171 " alt =" image_5.png " > <br > | ** In this script, students will...** <br > $\bullet$ evaluate edge detection methods. <br > $\bullet$ apply edge detection techniques. <br > | ** Academic disciplines** <br > $\bullet$ Computer Vision <br > $\bullet$ Image Processing <br > <br > |
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78- ## [ ** RegionSegmentation ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/RegionSegmentation.mlx )
78+ ## [ ** Region Segmentation ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/RegionSegmentation.mlx )
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8181| <img src =" Images/image_6.png " width =" 171 " alt =" image_6.png " > <br > | ** In this script, students will...** <br > $\bullet$ explore region segmentation techniques. <br > $\bullet$ compare and contrast including histogram, k\- means clustering, and graph\- cut segmentation techniques. <br > | ** Academic disciplines** <br > $\bullet$ Computer Vision <br > $\bullet$ Image Processing <br > |
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83- ## [ ** OpticalFlow ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/OpticalFlow.mlx )
83+ ## [ ** Optical Flow ** ] ( https://matlab.mathworks.com/open/github/v1?repo=MathWorks-Teaching-Resources/Computer-Vision-Basics&project=ComputerVisionBasics.prj&file=Scripts/OpticalFlow.mlx )
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8686| <img src =" Images/image_7.png " width =" 171 " alt =" image_7.png " > <br > | ** In this script, students will...** <br > $\bullet$ examine assumptions underlying optical flow theory. <br > $\bullet$ implement optical flow algorithms for motion detection. <br > $\bullet$ compare and contrast optical flow techniques. <br > | ** Academic disciplines** <br > $\bullet$ Computer Vision <br > $\bullet$ Image Processing <br > |
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