Difference between revisions of "Adaptive Thresholding"
(added link: paper that summarizes/compares image thresholding algorithms) |
m ("Auto-Thresholding" => "Thresholding") |
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Below are various algorithms for ''auto-thresholding'', that is, the process by which a threshold value on a histogram of a grayscale image is chosen automatically so as to fall in between the "foreground mound" and the "background mound" of the histogram. Once this threshold value is chosen, the "foreground" and "background" components of an image can be distinguished by comparing pixel values to the chosen threshold value. | Below are various algorithms for ''auto-thresholding'', that is, the process by which a threshold value on a histogram of a grayscale image is chosen automatically so as to fall in between the "foreground mound" and the "background mound" of the histogram. Once this threshold value is chosen, the "foreground" and "background" components of an image can be distinguished by comparing pixel values to the chosen threshold value. | ||
| − | === Otsu | + | === Otsu Thresholding === |
A somewhat technical overview of the Otsu algorithm can be found in section 2 of [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf this paper]. The same paper additionally proposes a modified version of the Otsu algorithm in section 3 that it asserts is less computationally expensive than the traditional Otsu algorithm. | A somewhat technical overview of the Otsu algorithm can be found in section 2 of [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf this paper]. The same paper additionally proposes a modified version of the Otsu algorithm in section 3 that it asserts is less computationally expensive than the traditional Otsu algorithm. | ||
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--[[User:DavidF|David]] 21:14, 7 Nov 2005 (EST) | --[[User:DavidF|David]] 21:14, 7 Nov 2005 (EST) | ||
| − | === Maximum Entropy | + | === Maximum Entropy Thresholding === |
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--[[User:DavidF|David]] 21:27, 7 Nov 2005 (EST) | --[[User:DavidF|David]] 21:27, 7 Nov 2005 (EST) | ||
| − | === Mixture Model | + | === Mixture Model Thresholding === |
==== Links ==== | ==== Links ==== | ||
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** [http://rsb.info.nih.gov/ij/plugins/download/jars/Mixture_Modeling.jar Original Source Code] | ** [http://rsb.info.nih.gov/ij/plugins/download/jars/Mixture_Modeling.jar Original Source Code] | ||
| − | === Other Types of | + | === Other Types of Thresholding === |
* '''Binary Clustering''' | * '''Binary Clustering''' | ||
* '''Metric''' | * '''Metric''' | ||
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* [http://homepages.inf.ed.ac.uk/rbf/HIPR2/adapthreshdemo.htm Demo] | * [http://homepages.inf.ed.ac.uk/rbf/HIPR2/adapthreshdemo.htm Demo] | ||
| − | === Other Types of | + | === Other Types of Thresholding === |
* '''Niblack Thresholding''' | * '''Niblack Thresholding''' | ||
* '''Bernsen Thresholding''' | * '''Bernsen Thresholding''' | ||
* '''Abutaleb Thresholding''' | * '''Abutaleb Thresholding''' | ||
* '''Sauvola Thresholding''' | * '''Sauvola Thresholding''' | ||
Revision as of 23:14, 7 November 2005
Adaptive thresholding is an image segmentation algorithm that appears quite resistent to varying lighting conditions.
This recent paper attempts to summarize and compare various image thresholding algorithms/techniques.
Contents
Global Value Adaptive Thresholding
(useful for barrel-in-sunlight detection)
Below are various algorithms for auto-thresholding, that is, the process by which a threshold value on a histogram of a grayscale image is chosen automatically so as to fall in between the "foreground mound" and the "background mound" of the histogram. Once this threshold value is chosen, the "foreground" and "background" components of an image can be distinguished by comparing pixel values to the chosen threshold value.
Otsu Thresholding
A somewhat technical overview of the Otsu algorithm can be found in section 2 of this paper. The same paper additionally proposes a modified version of the Otsu algorithm in section 3 that it asserts is less computationally expensive than the traditional Otsu algorithm. -class variance with an exhaustive search." -
Links
I've been trying to analyze the source code of this image filter (not written by me) in order to figure out how the Otsu Thresholding algorithm works. I've had limited success, in that I have completely figured out how GrayLevelClass.java works. However I have not been able to decode OtsuThresholding.java which appears to contain the essential details specific to the Otsu algorithm. --David 21:14, 7 Nov 2005 (EST)
Maximum Entropy Thresholding
- taken from [1]
Links
Once again, I've tried to analyze the source code of this image filter in order to figure how the algorithm its using works. --David 21:27, 7 Nov 2005 (EST)
Mixture Model Thresholding
Links
Other Types of Thresholding
- Binary Clustering
- Metric
- Moment-Preserving Thresholding
- "Moment preserving thresholding is a parametric method which segments the image based on the condition that the thresholded image has the same moments as the original image." - taken from [2]
- Inner-class Variance
Local Value Adaptive Thresholding
(useful for line-on-grass detection)
Other Types of Thresholding
- Niblack Thresholding
- Bernsen Thresholding
- Abutaleb Thresholding
- Sauvola Thresholding
