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Lecture-9
Region Segmentation
Segmentation
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Image Segmentation: Region Based Techniques and Histogram Analysis, Study notes of Computer Science
Region segmentation techniques in image processing, specifically focusing on methods that partition an image into sub-images based on gray level constraints. Simple segmentation, histogram analysis, and connected component labeling. Histogram analysis involves creating a graph of the number of pixels in an image with a particular gray level, which can be used to detect good peaks and segment the image into binary images. Connected component labeling is used to find connected regions in each binary image.
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Pre 2010
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Lecture-
Region Segmentation
Segmentation
Segmentation
- Partitionthe following constraints are satisfied:– f ( x,y ) into sub-images: R 1 , R 2 , ….,R (^) n such that
- – Each sub-mage satisfies a predicate or set of predicates
- • All pixels in any sub-image musts have the same gray levels.All pixels in any sub-image must not differ more than somethreshold
- • All pixels in any sub-image may not differ more than somethreshold from the mean of the gray of the regionThe standard deviation of gray levels in any sub-image must besmall.
- – Each sub-mage satisfies a predicate or set of predicates
R^ U iin =^1 I RiR^ = jf =( f x ,,^ yi^ )≠ j
Simple Segmentation
B ( x , y )= (^) ÁÁËÊ^01 Otherwiseif f ( x , y )< T B ( x , y )= (^) ÁÁËÊ^01 ifOtherwise T^1 < f ( x , y )< T^2 B ( x , y )= (^) ÁÁËÊ^01 Otherwiseif f ( x , y )Œ Z
Segmentation Using Histogram
B 1 ( x , y )= (^) ÁÁËÊ^01 Otherwiseif^0 < f ( x , y )<^ T^1 B 2 ( x , y )= (^) ÁÁËÊ^01 ifOtherwise T^1 < f ( x , y )<^ T^2 B 3 ( x , y )= (^) ÁÁËÊ^01 ifOtherwise T^2 < f ( x , y )<^ T^3
Realistic Histogram
Peakiness Test
Peakiness = (^) ÁËÊ^1 - ( Va 2 + PVb )˜¯ˆ.ÁÁËÊ 1 - ( WN. P ) ˜˜¯ˆ
Connected Component
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Recursive Connected ComponentAlgorithm
Sequential
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Component Algorithm^ Sequential Connected
Recursive
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Example-II
93 peaks
Smoothed Histograms
Smoothed histogram(averaging using maskOf size 5) 54 peaks (once)After peakiness 18 Smoothed histogram21 peaks (twice)After peakiness 7 Smoothed histogram11 peaks (three times)After peakiness 4
Regions
(0,40) (40, 116)
Regions
(116,243) (^) (243,255)