eee508_ImgSegment

Eee508_ImgSegment - Image Segmentation age Seg e tat o Objective to determine(extract object boundaries It is a process of partitioning an image

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Image Segmentation Objective : to determine (extract) object boundaries. It is a process of partitioning an image into distinct regions by grouping together neighboring pixels based on some pre- defined similarity criterion. It can be viewed as a classification technique that forms regions of similarities in the image. The similarity criterion is determined using specific properties or features of pixels representing objects in the image. Much more difficult with non-uniform background as compared to uniform background. EEE 508 3
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Image segmentation Broad classification of methods: ¾ Edge-based methods 9 The edge information is used to determine boundaries of objects. The boundaries are then analyzed and modified to form closed regions belonging to the objects in the image belonging to the objects in the image. ¾ Pixel-based direct classification methods 9 Heuristics or estimation methods derived from the histogram statistics of the image or clustering algorithms are used to form closed regions belonging to the objects in the image. ¾ Region-based methods 9 Pixels are analyzed directly for a region growing process based on a pre defined similarity criterion to form closed regions belonging to the pre-defined similarity criterion to form closed regions belonging to the objects in the image. EEE 508 3
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Edge-based image segmentation General procedure: ¾ Detect edges based on first-order or second-order gradient information. ¾ Track and link relevant edges based on gradient information. Edge detection ¾ The Gradient magnitude commonly used to detect edges EEE 508 3
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Edge Detection One basic tool: Gradient operator ±²±² ± ² ±² ; , , , , 2 1 1 1 2 1 2 1 2 1 » º « ª » » º « « ª w w w ³ n n g n n g n n n n n x n n x n n g x x ( n 1 , n 2 ) –input image ± ² ± ² , , 2 1 2 2 2 1 ¼ ¬ » » ¼ « « ¬ w n x n 2 n 1 gradient: points in direction of greatest change (locally at a pixel) ¾ The Gradient magnitude is commonly used for edge detection 2 1 2 2 1 2 2 1 2 1 , , , ¸ · ¨ § ¸ ¸ · ¨ ¨ § w w ´ ¸ ¸ · ¨ ¨ § w w n n n x n n n x n n g EEE 508 3 2 1 ¸ ¹ ¨ © ¹ © ¹ ©
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Edge Detection ¾ Question: How do we realize (compute) the gradient in discrete- domain? ¾ Example: Robert’s Gradient ± ² ± ² ± ² ± ² 2 1 2 1 2 1 2 1 1 , 1 , 1 , , n n x n n x n n x n n g ³ ´ ´ w ±² 2 1 2 1 2 2 1 2 1 2 1 , 1 1 , , , n n x n n x n n n x n n g n ´ ³ ´ w w w 2 ¾ Interpretation: this is like a cross-wise 2D first backward difference. ± ² ± ² ± ² ± ² ± ² 2 2 1 2 1 2 1 2 1 2 1 , 1 1 , , 1 , 1 , n n x n n x n n x n n x n n g ´ ³ ´ ´ ³ ´ ´ n 2 µ µ µ µ µ µ µ µ µ µ µ µ EEE 508 3 µ µ µ µ n 1
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Edge Detection ¾ In general: ± ² ± ² ± ² ±² ±²±² 2 1 2 2 1 2 1 2 2 1 1 2 1 2 1 1 , , , , , , n n h n n x n n g n n h n n x n n g ³ ³ ³ ³ 2 2 n n g g n n g ´ ¾ Robert’s Gradient ± ² ± ² ± ² 2 1 2 2 1 1 2 1 , , , n n n 2 h 1 ( -n 1,- n 2) n 2 h 2 ( -n 1, - n 2 ) n 1 (1) (-1) (1) (-1) n 1 EEE 508 3
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Edge Detection ¾ Sobel’s Gradient (1) n 2 h 1 ( - n 1 ,-n 2 ) (-1) (-1) n 2 h 2 ( - n 1 ,-n 2 ) (-1)
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This document was uploaded on 03/11/2012.

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Eee508_ImgSegment - Image Segmentation age Seg e tat o Objective to determine(extract object boundaries It is a process of partitioning an image

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