Iris Segmentation Code Based on the GST - Revision history

Feralo at 11:46, 15 September 2021

2021-09-15T11:46:13Z

Feralo at 08:23, 15 September 2021

2021-09-15T08:23:37Z

Feralo at 08:17, 15 September 2021

2021-09-15T08:17:31Z

Feralo at 12:12, 29 January 2021

2021-01-29T12:12:33Z

Feralo at 12:05, 29 January 2021

2021-01-29T12:05:07Z

Feralo at 18:03, 27 January 2021

2021-01-27T18:03:20Z

Feralo at 19:16, 21 October 2019

2019-10-21T19:16:58Z

Feralo at 19:16, 21 October 2019

2019-10-21T19:16:07Z

Feralo at 19:50, 6 March 2018

2018-03-06T19:50:08Z

Feralo at 15:25, 25 September 2015

2015-09-25T15:25:05Z

← Older revision		Revision as of 11:46, 15 September 2021
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	}}		}}

		+	{\| class="wikitable"
		+	!colspan="1" \| The content of this page has been moved to our [https://github.com/HalmstadUniversityBiometrics/Iris-Segmentation-GST-Matlab Github repository]. You can read this same content and download the files there.
		+	\|}

	=='''Introduction'''==		=='''Introduction'''==

@@ Line 77: / Line 77: @@
 '''DOWNLOAD THE CODE'''
-Please download the code in our repository in Github, [https://github.com/HalmstadUniversityBiometrics/Iris-Segmentation-GST-Matlab here].
+Please download the code in our Github repository, [https://github.com/HalmstadUniversityBiometrics/Iris-Segmentation-GST-Matlab here].
 <!-- Esto es un comentario

@@ Line 73: / Line 73: @@
 By downloading the code, you agree with the terms and conditions indicated above.
 '''Download the code''' (compiler: Matlab r2009b 32 bits (mcc command) under Windows 8.1) [http://wiki.hh.se/caisr/index.php/File:Release_GST_segmentation_-_winx86_-r2009b.zip here] (latest release: September 2015).
 '''Download the code''' (compiler: Matlab r2018b 64 bits (mcc command) under Windows 10) [http://wiki.hh.se/caisr/index.php/File:Release_GST_segmentation_-_winx64_-r2018b.zip here] (latest release: October 2019).
 You may are also interested in our [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].

@@ Line 91: / Line 91: @@
 # F. Alonso-Fernandez, J. Bigun, “Near-infrared and visible-light periocular recognition with Gabor features using frequency-adaptive automatic eye detection”, [http://digital-library.theiet.org/content/journals/iet-bmt, IET Biometrics], Volume 4, Issue 2, pp. 74-89, June 2015 ([http://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2014.0038 link to the publication in IET Biometrics])
 # C. Rathgeb, A. Uhl, P. Wild, "Iris Biometrics. From Segmentation to Template Security", Springer, 2013
-# Z. He, T. Tan, Z. Sun, X. Qiu, "Toward accurate and fast iris segmentation for iris biometrics", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 31, (9), pp. 1295–1307 ([http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4586378&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4586378 link to the publication in IEEE Xplore])
+# Z. He, T. Tan, Z. Sun, X. Qiu, "Toward accurate and fast iris segmentation for iris biometrics", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 31, (9), pp. 1295–1307 ([https://ieeexplore.ieee.org/document/4586378 link to the publication in IEEE Xplore])
-#J. Daugman, "New methods in iris recognition", IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(5), 2007 ([http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4305270&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4305270 link to the publication in IEEE Xplore]) ([http://www.cl.cam.ac.uk/~jgd1000/NewMethodsInIrisRecog.pdf link to the publication in the author´s web site])
+#J. Daugman, "New methods in iris recognition", IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(5), 2007 ([https://ieeexplore.ieee.org/document/4305270 link to the publication in IEEE Xplore]) ([http://www.cl.cam.ac.uk/~jgd1000/NewMethodsInIrisRecog.pdf link to the publication in the author´s web site])

@@ Line 74: / Line 74: @@
 By downloading the code, you agree with the terms and conditions indicated above.
-'''Download the code''' (compiler: Matlab r2009b 32 bits (mcc command) under Windows 8.1) [http://wiki.hh.se/caisr/File:Release_GST_segmentation_-_winx86_-r2009b.zip here] (latest release: September 2015).
+'''Download the code''' (compiler: Matlab r2009b 32 bits (mcc command) under Windows 8.1) [http://wiki.hh.se/caisr/index.php/File:Release_GST_segmentation_-_winx86_-r2009b.zip here] (latest release: September 2015).
-'''Download the code''' (compiler: Matlab r2018b 64 bits (mcc command) under Windows 10) [http://wiki.hh.se/caisr/File:Release_GST_segmentation_-_winx64_-r2018b.zip here] (latest release: October 2019).
+'''Download the code''' (compiler: Matlab r2018b 64 bits (mcc command) under Windows 10) [http://wiki.hh.se/caisr/index.php/File:Release_GST_segmentation_-_winx64_-r2018b.zip here] (latest release: October 2019).
-You may are also interested in our [http://wiki.hh.se/caisr/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].
+You may are also interested in our [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].
 =='''People responsible'''==

@@ Line 9: / Line 9: @@
 =='''Introduction'''==
-'''This page provides a software code for iris segmentation based on the Generalized Structure Tensor (GST)''', based on publications [1] and [2] ([http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References below] in this page). Its development was made mainly during the 2011-2013 [http://islab.hh.se/mediawiki/BIO-DISTANCE FP7 Marie Curie IEF Action BIO-DISTANCE], but it contains some improvements and add-ons incorporated afterwards. We keep working constantly in this topic, so if you are interested, it is maybe worth checking from time to time if new improvements have been added to the code.
+'''This page provides a software code for iris segmentation based on the Generalized Structure Tensor (GST)''', based on publications [1] and [2] ([http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References below] in this page). Its development was made mainly during the 2011-2013 [http://wiki.hh.se/caisr/index.php/BIO-DISTANCE FP7 Marie Curie IEF Action BIO-DISTANCE], but it contains some improvements and add-ons incorporated afterwards. We keep working constantly in this topic, so if you are interested, it is maybe worth checking from time to time if new improvements have been added to the code.
 The software accepts an iris image as input, and outputs segmentation information of the input iris image (see below for more information). It is capable of handling images acquired both in near-infrared (NIR) and visible (VW) spectrum.
@@ Line 22: / Line 22: @@
 <!-- Esto es un comentario -->
-) <u>Specular reflection removal</u> based on the method published in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 3].
+) <u>Specular reflection removal</u> based on the method published in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 3].
 <!-- Esto es un comentario -->
-) <u>Computation of the image frequency</u> based on the method published in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. This helps to customize inner parameters of steps 5-8 to the input image.
+) <u>Computation of the image frequency</u> based on the method published in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. This helps to customize inner parameters of steps 5-8 to the input image.
 <!-- Esto es un comentario -->
-) <u>Adaptive eyelash removal</u> using the image frequency, as indicated in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. The method is based on p-rank filters as published in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 4]. Eyelashes are removed since they create strong vertical edges that may mislead the filters used for eye center estimation and iris segmentation in steps 7 and 9.
+) <u>Adaptive eyelash removal</u> using the image frequency, as indicated in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. The method is based on p-rank filters as published in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 4]. Eyelashes are removed since they create strong vertical edges that may mislead the filters used for eye center estimation and iris segmentation in steps 7 and 9.
 <!-- Esto es un comentario -->
@@ Line 35: / Line 35: @@
 <br />
-) <u>Adaptive edge map computation</u> using the image frequency, as indicated in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. Edge map is the basis for eye center estimation and iris boundaries detection, see references [1, 2] for further details.
+) <u>Adaptive edge map computation</u> using the image frequency, as indicated in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2]. Edge map is the basis for eye center estimation and iris boundaries detection, see references [1, 2] for further details.
 <!-- Esto es un comentario -->
-) <u>Estimation of the eye center</u> based on the method published in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2] using circular symmetry filters. The estimated center is used to mask candidate regions for the centers of iris circles, helping to improve detection accuracy in step 9.
+) <u>Estimation of the eye center</u> based on the method published in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 2] using circular symmetry filters. The estimated center is used to mask candidate regions for the centers of iris circles, helping to improve detection accuracy in step 9.
 <!-- Esto es un comentario -->
@@ Line 44: / Line 44: @@
 <!-- Esto es un comentario -->
-) <u>Detection of iris boundaries</u> based on the method published in [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 1] using the Generalized Structure Tensor (GST). In NIR images, the inner (pupil) circle is detected first, while in VW images, the outer (sclera) filter is detected first. This is because in NIR images, pupil-to-iris transition is sharper than iris-to-sclera transition, thus more reliable to detect in the first place. The opposite happens with VW images.
+) <u>Detection of iris boundaries</u> based on the method published in [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 1] using the Generalized Structure Tensor (GST). In NIR images, the inner (pupil) circle is detected first, while in VW images, the outer (sclera) filter is detected first. This is because in NIR images, pupil-to-iris transition is sharper than iris-to-sclera transition, thus more reliable to detect in the first place. The opposite happens with VW images.
 <!-- Esto es un comentario -->
-) <u>Irregular contour fitting</u> based on active contours as published in reference [http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 5].
+) <u>Irregular contour fitting</u> based on active contours as published in reference [http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References reference 5].
 <br />
@@ Line 70: / Line 70: @@
 Certain parameters of the code are customizable, please read the documentation included with the code for more information.
-'''Please remember to cite references [1] and [2] ([http://islab.hh.se/mediawiki/index.php/Iris_Segmentation_Code_Based_on_the_GST#References below]) if you make use of this code in any publication'''.
+'''Please remember to cite references [1] and [2] ([http://wiki.hh.se/caisr/index.php/Iris_Segmentation_Code_Based_on_the_GST#References below]) if you make use of this code in any publication'''.
 By downloading the code, you agree with the terms and conditions indicated above.
-'''Download the code''' (compiler: Matlab r2009b 32 bits (mcc command) under Windows 8.1) [http://islab.hh.se/mediawiki/File:Release_GST_segmentation_-_winx86_-r2009b.zip here] (latest release: September 2015).
+'''Download the code''' (compiler: Matlab r2009b 32 bits (mcc command) under Windows 8.1) [http://wiki.hh.se/caisr/File:Release_GST_segmentation_-_winx86_-r2009b.zip here] (latest release: September 2015).
-'''Download the code''' (compiler: Matlab r2018b 64 bits (mcc command) under Windows 10) [http://islab.hh.se/mediawiki/File:Release_GST_segmentation_-_winx64_-r2018b.zip here] (latest release: October 2019).
+'''Download the code''' (compiler: Matlab r2018b 64 bits (mcc command) under Windows 10) [http://wiki.hh.se/caisr/File:Release_GST_segmentation_-_winx64_-r2018b.zip here] (latest release: October 2019).
-You may are also interested in our [http://islab.hh.se/mediawiki/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].
+You may are also interested in our [http://wiki.hh.se/caisr/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].
 =='''People responsible'''==
-* [http://islab.hh.se/mediawiki/index.php/Fernando_Alonso-Fernandez Fernando Alonso-Fernandez] (contact person)
+* [http://wiki.hh.se/caisr/index.php/Fernando_Alonso-Fernandez Fernando Alonso-Fernandez] (contact person)
-* [http://islab.hh.se/mediawiki/index.php/Josef_Bigun Josef Bigun]
+* [http://wiki.hh.se/caisr/index.php/Josef_Bigun Josef Bigun]

@@ Line 66: / Line 66: @@
 This code is provided "as is", without any warranty, and for research purposes only.
-The code is provided in the form of executables compiled with Matlab (mcc command) under. It accepts as input grayscale and RGB images in any format supported by Matlab "imread" (uint8 only).
+The code is provided in the form of executables compiled with Matlab (mcc command) under Windows. It accepts as input grayscale and RGB images in any format supported by Matlab "imread" (uint8 only).
 Certain parameters of the code are customizable, please read the documentation included with the code for more information.

← Older revision		Revision as of 15:25, 25 September 2015
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	'''Download the code''' [http://islab.hh.se/mediawiki/index.php/File:Release_GST_segmentation.zip here] (latest release: September 2015). '''Please request password''' of the the file to: [[Fernando Alonso-Fernandez]].		'''Download the code''' [http://islab.hh.se/mediawiki/index.php/File:Release_GST_segmentation.zip here] (latest release: September 2015). '''Please request password''' of the the file to: [[Fernando Alonso-Fernandez]].
		+
		+	You may are also interested in our [http://islab.hh.se/mediawiki/Iris_Segmentation_Groundtruth database of iris segmentation groundtruth].

	=='''People responsible'''==		=='''People responsible'''==