Thresholding Filters
Thresholding filters output an image composed to two basic classes — foreground and background. These images can be used as masks for segmentation purposes or other image processing tasks.
Adaptive
Applies an adaptive threshold to an array.
References
Isodata
Return threshold value(s) based on ISODATA method. That is, returned thresholds are intensities that separate the image into two groups of pixels, where the threshold intensity is midway between the mean intensities of these groups.
References
[1] Ridler, TW & Calvard, S (1978), “Picture thresholding using an iterative selection method”
[2] IEEE Transactions on Systems, Man and Cybernetics 8: 630-632, http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4310039
[3] Sezgin M. and Sankur B. (2004) “Survey over Image Thresholding Techniques and Quantitative Performance Evaluation” Journal of Electronic Imaging, 13(1): 146-165, http://www.busim.ee.boun.edu.tr/~sankur/SankurFolder/Threshold_survey.pdf
Li
Return threshold value based on adaptation of Li’s Minimum Cross Entropy method.
References
[1] http://scikit-image.org/docs/dev/api/skimage.filters.html?highlight=adaptive%20filter#threshold-li
Otsu
This filter an implementation of the Otsu thresholding technique and outputs an image composed of two basic classes — foreground and background. In this thresholding technique, the optimal value that minimizes the weighted within class variances of these two classes is computed. You should note that minimizing the within class variance is the same as maximizing the between class variance.
One of the main advantages of the Otsu thresholding technique is speed. However, the technique assumes uniform illumination and doesn’t use any object structure or spatial coherence. Since Otsu thresholding operates over the histograms, you should analyze the image histogram before applying this filter. See Working with Histograms.
References
Yen
Return threshold value based on Yen’s method.
References
[1] http://scikit-image.org/docs/dev/api/skimage.filters.html?highlight=adaptive%20filter#threshold-yen
[2] Yen J.C., Chang F.J., and Chang S. (1995) “A New Criterion for Automatic Multilevel Thresholding” IEEE Trans. on Image Processing, 4(3): 370-378
[3] Sezgin M. and Sankur B. (2004) “Survey over Image Thresholding Techniques and Quantitative Performance Evaluation” Journal of Electronic Imaging, 13(1): 146-165, http://www.busim.ee.boun.edu.tr/~sankur/SankurFolder/Threshold_survey.pdf
