Thresholding (image processing): Difference between revisions

Revision as of 15:58, 8 December 2018

Revision as of 15:59, 8 December 2018

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Histogram shape-based methods in particular, but also many other thresholding algorithms, make certain assumptions about the image intensity probability distribution. The most common thresholding methods work on bimodal distributions, but algorithms have also been developed for [[Unimodal thresholding|unimodal distributions]], multimodal distributions, and [[Circular thresholding|circular distributions]].

== Automatic Thresholdingthresholding ==

Automatic Thresholdingthresholding is a great way to extract useful information encoded into pixels while minimizing background noise. This is accomplished by utilizing a feedback loop to optimize the threshold value before converting the original grayscale image to binary. The idea is to separate the image into two parts; the background and foreground<ref>{{Cite book|url=https://www.worldcat.org/oclc/1016899766|title=Digital Image Processing and Analysis with MATLAB and CVIPtools, Third Edition|last=E.,|first=Umbaugh, Scott|isbn=9781498766074|edition=3rd|oclc=1016899766}}</ref>.

# Select initial threshold value, typically the mean 8-bit value of the original image.

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The limit mentioned above is user definable. A larger limit will allow a greater difference between successive threshold values. Advantages of this can be quicker execution but with a less clear boundary between background and foreground. Picking starting thresholds is often done by taking the mean value of the grayscale image. However, it is also possible to pick out the starting threshold values based on the two well separated peaks of the image histogram and finding the average pixel value of those points. This can allow the algorithm to converge faster; allowing a much smaller limit to be chosen.

=== Method Limitationslimitations ===

Automatic thresholding will work best when a good background to foreground contrast ratio exists. Meaning the picture must be taken in good lighting conditions with minimal glare.