Image Segmentation - Part 1 - IMAGE SEGMENTATION Part 1...

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IMAGE SEGMENTATION Part 1
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Introduction Segmentation subdivides an image into its constituents regions or objects. The purpose of image segmentation is to partition an image into meaningful regions (that represents objects or meaningful parts of objects ) with respect to a particular application
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Image segmentation --- for homogeneous grey/color/texture region processes
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Introduction The segmentation is based on data measurements taken from an image which might be grey level intensity , colour , texture , depth or motion
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Introduction Image segmentation is an initial and vital step in a series of processes aimed at overall image understanding
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Introduction Applications of image segmentation include: Identifying objects in a scene for object-based measurements such as size and shape Identifying objects in a moving scene for object- based video compression (MPEG4) Identifying objects which are at different distances from a sensor using depth measurements from a laser range finder enabling path planning for a mobile robots
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Introduction to IS Methods IS methods will look for objects that either have some measure of homogeneity within themselves or have some measure of contrast with the objects on their border.
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Introduction The homogeneity and contrast measures can include features such as: Grey levels (intensity/brightness) Color Texture Motion
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Example: monochrome images Segmentation are based on two basic properties of gray-level values: Discontinuity/contrast , i.e. to partition the image based on abrupt changes in intensity (gray levels), e.g. edges Similarity/homogeneity , i.e. to partition the image into similar (according to predefined criteria) regions, e.g. thresholding , region growing, shrinking, splitting and merging, clustering
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Detection of Discontinuities 3 basic types of gray-level discontinuities: Points, Lines, Edges Common method of detection: run a mask through the image.
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Point Detection T: nonnegative threshold: = = + + + = 9 1 9 9 2 2 1 1 ... i i i z w z w z w z w R | R | T
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Point Detection A point has been detected at the location on which the mask is centered if: |R|>T The gray level of an isolated point will be quite different from the gray levels of its neighbors measure the weighted differences between the center point and its neighbors
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Line Detection If at a certain point |R i |>|R j |, this point is more likely associated with a line in the direction of mask i.
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Image Segmentation - Part 1 - IMAGE SEGMENTATION Part 1...

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