Adaptive Thresholding - Revision history

Joldenburg6: Categorize

2018-06-14T02:04:50Z

Categorize

202.185.32.16: /* Other Thresholding Algorithms */

2011-06-06T10:43:11Z

‎Other Thresholding Algorithms

DavidF: /* Links */ split off part of Links section into a new Progress section

2005-11-10T00:56:15Z

‎Links: split off part of Links section into a new Progress section

DavidF: /* References */ added comments

2005-11-10T00:54:41Z

‎References: added comments

DavidF: added References section

2005-11-10T00:44:03Z

added References section

DavidF: /* Otsu Thresholding */ added Issues subsection

2005-11-10T00:10:50Z

‎Otsu Thresholding: added Issues subsection

DavidF: /* Otsu Thresholding */ added Implementation subsection

2005-11-10T00:00:44Z

‎Otsu Thresholding: added Implementation subsection

DavidF: /* Otsu Thresholding */

2005-11-09T23:53:25Z

‎Otsu Thresholding

DavidF: /* Otsu Thresholding */ more info on Otsu found (including the original paper!)

2005-11-09T23:52:00Z

‎Otsu Thresholding: more info on Otsu found (including the original paper!)

DavidF: /* Links */ plans to incorporate Otsu algorithm into ImageFilterDemo

2005-11-08T21:04:17Z

‎Links: plans to incorporate Otsu algorithm into ImageFilterDemo

@@ Line 11: / Line 11: @@
 === 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.
-* "method chooses the optimal thresholds by maximizing the between-class variance with an exhaustive search."
+* "Otsu�s method chooses the optimal thresholds by maximizing the between-class variance with an exhaustive search."
-* "The Sahoo et al. study on global thresholding, concluded that method was one of the better threshold selection methods for general real world images with regard to uniformity and shape measures. However, method uses an exhaustive search to evaluate the criterion for maximizing the between-class variance. As the number in classes of an image increases, method takes too much time to be practical for multilevel threshold selection."
+* "The Sahoo et al. study on global thresholding, concluded that Otsu�s method was one of the better threshold selection methods for general real world images with regard to uniformity and shape measures. However, Otsu�s method uses an exhaustive search to evaluate the criterion for maximizing the between-class variance. As the number in classes of an image increases, Otsu�s method takes too much time to be practical for multilevel threshold selection."
 Another paper's take on Otsu thresholding:
-* method is an early, but still popular histogram-based global threshold algorithm. It proposed a criterion for maximising the variance of the between-class pixel intensities to perform thresholding. However, algorithm is very time-consuming for image binarisation because of its inefficient formulation of the between-class variance, and the performance varies with image types.
+* Otsu�s method is an early, but still popular histogram-based global threshold algorithm. It proposed a criterion for maximising the variance of the between-class pixel intensities to perform thresholding. However, Otsu�s algorithm is very time-consuming for image binarisation because of its inefficient formulation of the between-class variance, and the performance varies with image types.
 Ah ha! I've located the citation for Otsu's original paper:
-* Otsu, N.: threshold selection method from grey level , ''IEEE Trans. Syst. Man Cybern.'', 1979, '''9''', (1), pp. 62 66
+* Otsu, N.: �A threshold selection method from grey level histogram�, ''IEEE Trans. Syst. Man Cybern.'', 1979, '''9''', (1), pp. 62 � 66
 ==== Links ====
@@ Line 67: / Line 67: @@
 * Inner-class Variance
 * Pun Thresholding
-** "In method, as modified by Kapur et al., the picture threshold is found by maximizing the entropy of the histogram of gray levels of the resulting classes." - taken from [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf]
+** "In Pun�s method, as modified by Kapur et al., the picture threshold is found by maximizing the entropy of the histogram of gray levels of the resulting classes." - taken from [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf]
 == '''Local Value Adaptive Thresholding''' ==
@@ Line 98: / Line 98: @@
 ** Has a very useful set of tables (on the third and fourth pages) that list the various common thresholding algorithms that have been developed since 2005.
 ** Proposes its own interesting thresholding algorithm that involves analyzing an image and then choosing one of the historical thresholding alogrithms to apply to it, based on the image's characteristics. (This algorithm would take way too long to implement, even though it is very good.)
-* Otsu, N.: threshold selection method from grey level , ''IEEE Trans. Syst. Man Cybern.'', 1979, '''9''', (1), pp. 62 66
+* Otsu, N.: �A threshold selection method from grey level histogram�, ''IEEE Trans. Syst. Man Cybern.'', 1979, '''9''', (1), pp. 62 � 66
 ** Original article proposing the [[#Otsu Thresholding|Otsu thresholding algorithm]]

@@ Line 79: / Line 79: @@
 * Abutaleb Thresholding
 * Sauvola Thresholding
 == Unassessed Thresholding Algorithms ==

@@ Line 26: / Line 26: @@
 *** [[:Image:OtsuThresholdingModified.zip|v1.0]] - Initial version
 *** [[:Image:OtsuThresholdingModified_v2_0.zip|v2.0]] - Fixed mistranslation of <tt>magic_calcMuAndOmega</tt> in <tt>addToEnd</tt>
 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.

@@ Line 90: / Line 90: @@
 == References ==
 * [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf A Fast Algorithm for Multilevel Thresholding]
 * [[:Image:AdaptiveThresholdingArticle.pdf|Decompose algorithm for thresholding degraded historical document images]]

← Older revision		Revision as of 00:44, 10 November 2005
Line 87:		Line 87:
	* Kittler-Illingworth Thresholding // Minimum Error Thresholding		* Kittler-Illingworth Thresholding // Minimum Error Thresholding
	* Kapur, Sahoo, Wong Thresholding		* Kapur, Sahoo, Wong Thresholding
		+
		+	== References ==
		+	* [http://www.iis.sinica.edu.tw/JISE/2001/200109_01.pdf A Fast Algorithm for Multilevel Thresholding]
		+	* [[:Image:AdaptiveThresholdingArticle.pdf\|Decompose algorithm for thresholding degraded historical document images]]
		+

@@ Line 36: / Line 36: @@
 ==== Implementation ====
 I've implemented the Otsu algorithm in the '''OtsuThresholdingAlgorithm''' class, included with [[ImageFilterDemo]] [[:Image:ImageFilterDemo_v1_3_1.zip|v1.3.1]]. The '''GrayscaleLevelHistogram''' filter in [[ImageFilterDemo]] [[:Image:ImageFilterDemo_v1_3_2.zip|v1.3.2]] uses this algorithm to calculate a threshold value which is displayed as a vertical red line on the output histogram. --[[User:DavidF|David]]
 === Maximum Entropy Thresholding ===

@@ Line 33: / Line 33: @@
 After several hours of work, I've finally decoded the Otsu algorithm! Not only that - I have written my own implementation of the algorithm which seems to produce good results when given sample images. To the right is a histogram augmented with a vertical red line indicating the thresholding level selected by the Otsu algorithm. In the near future I will incorporate the Otsu algorithm into the next [[ImageFilterDemo]] distribution.
 --[[User:DavidF|David]] 16:01, 8 Nov 2005 (EST)
 === Maximum Entropy Thresholding ===

← Older revision		Revision as of 23:52, 9 November 2005
Line 13:		Line 13:


		+
		+	Another paper's take on Otsu thresholding:
		+
		+
		+	Ah ha! I've located the citation for Otsu's original paper:
		+

	==== Links ====		==== Links ====