Howtosignalprocessing
- What is the primary limitation of Otsu's method for thresholding?
- What is the basic idea behind Otsu's method?
- What is Otsu method for image segmentation?
- How is Otsu thresholding calculated?
What is the primary limitation of Otsu's method for thresholding?
Otsu's algorithm is one of the most well-known methods for automatic image thresholding. 2D Otsu's method is more robust compared to 1D Otsu's method. However, it still has limitations on salt-and-pepper noise corrupted images and uneven illumination images.
What is the basic idea behind Otsu's method?
In summary, Otsu's method looks at every possible value for the threshold between background and foreground, calculates the variance within each of the two clusters, and selects the value for which the weighted sum of these variances is the least.
What is Otsu method for image segmentation?
OTSU method (OTSU) is a global adaptive binarization threshold image segmentation algorithm, it is put forward by Japanese scholars OTSU in 1979. This algorithm takes the maximum inter class variance between the background and the target image as the threshold selection rule.
How is Otsu thresholding calculated?
This is simply the sum of the two variances multiplied by their associated weights. This final value is the 'sum of weighted variances' for the threshold value 3. This same calculation needs to be performed for all the possible threshold values 0 to 5.
