Binary Image Analysis
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Transcript of Binary Image Analysis
![Page 1: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/1.jpg)
Binary Image Analysis
![Page 2: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/2.jpg)
YOU HAVE TO READ THE BOOK!
reminder
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What is a binary image?
• An image that has two possible values for each pixel.
![Page 4: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/4.jpg)
Thresholding
• A method that creates binary images.• An operation that divides pixels into two
groups: Foreground pixels and Background pixels
![Page 5: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/5.jpg)
Thresholding
• A simple threshold has one value t.• Usually:
g=image>t;– Pixels with values greater than t are:
foreground pixels.– Pixels with values smaller than t are:
background pixels.
• How else can we do it?
![Page 6: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/6.jpg)
Thresholding
• Threshold above and threshold below.• How do we choose the threshold value?– Simple: mean or median.– Histogram.
• Adaptive thresholding.• Multiband thresholding.
![Page 7: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/7.jpg)
Thresholding1. An initial threshold (T) is chosen, this can be done randomly or according
to any other method desired.2. The image is segmented into object and background pixels, creating two
sets: – G1 = {f(m,n):f(m,n)>T} (object pixels)– G2 = {f(m,n):f(m,n)T} (background pixels) (note, f(m,n) is the value of the pixel
located in the mth column, nth row)3. The average of each set is computed.
– m1 = average value of G1
– m2 = average value of G2
4. A new threshold is created that is the average of m1 and m2 – T’ = (m1 + m2)/2
5. Go back to step two, now using the new threshold computed in step four, keep repeating until the new threshold matches the one before it (i.e. until convergence has been reached).
Wikipedia (Thresholding)
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Histogram
• Display of frequencies of pixel intensity values in an image.
• The number of pixels found for every intensity value.
http://homepages.inf.ed.ac.uk/rbf/HIPR2/histgram.htm
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Multiband Thresholding
http://homepages.inf.ed.ac.uk/rbf/HIPR2/threshld.htm
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Adaptive Thresholding
• Use different threshold values for different regions of the image.
![Page 11: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/11.jpg)
Connected Components Labeling
• Used only with binary images.• It groups objects in images.• Scans the image for similar neighboring pixels.
http://homepages.inf.ed.ac.uk/rbf/HIPR2/label.htm
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Image Morphology
• Analysis and processing of geometrical structures.
• It is used in binary images.• Operations performed by structuring
elements on images.• Erosion, Dilation, Opening, Closing
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Image Morphology
• Structuring element example
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Image Morphology
• Dilation
![Page 15: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/15.jpg)
Image Morphology
• Erosion
![Page 16: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/16.jpg)
Image Morphology
• Opening
![Page 17: Binary Image Analysis](https://reader036.fdocuments.us/reader036/viewer/2022062517/56813207550346895d985ac8/html5/thumbnails/17.jpg)
Image Morphology
• Closing