Adaptive Thresholding
Adaptive thresholding is an image segmentation algorithm that appears quite resistent to varying lighting conditions.
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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 Auto-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." -
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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 Auto-Thresholding
- taken from [1]
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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 Auto-Thresholding
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Other Types of Auto-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)
