iridology bernard jensen

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Overview of abnormal feature
detection method in iris image
Le Chang
changle1105@163.com
Shenyang University of
Technology
Contents
1. The development of iridology
2. The relationship between abnormal features and human health in the iris image 3. Research on detection method of abnormal features in iris image 4. The present problems and our job
China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
1 The development of
iridology
1.1 The development of iridology
Iridology is found by Hungarian physician Von Peczely in 1861.
Fig1.1 Von Peczely
[1] BernardJensen.Iridology:TheScienceAndPractice.1982
Fig1.2 (a) The chart of iridology
Fig1.2 (b) The chart of iridology in Australia
[1]BernardJensen.Iridology:TheScienceAndPractice.1982
Fig1.2 (c) The chart of iridology in France
Fig1.2 (d) The chart of iridology in South Africa
Fig1.2 (e) The chart of iridology in Spanish
Fig1.2 (f) The chart of iridology in China
The development of iridology in another country 【1】：
USA：IridologyisoneofgraduatecourseinMedicalUniversity
Russia：Iridologyissupportedbythenationalministryofhealth
financial
Japan:Iridologyisteachingasdisciplineinschool
In South Africa, Indonesia, Brazil and other countries【２】：
Somescholarsstillstudyontherelationshipbetweeniridolgyand
somediseases
[1]BernardJensen.IridologySimplified.InternationalIridologyPractitioners
Association,2005:15-48.
[2]NatalieStearn，DeWetSwanepoel.IDENTIFYINGHEARINGLOSSBY
MEANSOFIRIDOLOGY.Afr.J.Trad.CAM(2007)4(2):205– 210.
1.2 The development of iridology in China
Fig1.3 Ophthalmology of traditional Chinese Medicine China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
Fig 1.4 Iris image acquisition equipment
In 2007, The State Food and Drug Administration release a document
[2007]71: Iris instrument is mainly used for the analysis of human subhealth state China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
Fig 1.5 Documents and certificates of iris consultant training
1.2 Introduction of iridology
(a) Sodium Ring (b) Venous Congestion Ring
(c) Scurf Rim Fig 1.6 The abnormal features in iris [1] BernardJensen.Iridology:TheScienceAndPractice.1982
(a) Pigment plaque
(b) Plaque (c) Radii solaris
Fig 1.7 The abnormal features in iris [1] BernardJensen.Iridology:TheScienceAndPractice.1982
Fig 1.8 The abnormal features in iris [1] BernardJensen.Iridology:TheScienceAndPractice.1982
2 The relationship between
abnormal features and human
health in the iris image
2 The relationship between abnormal
features and human health
1. Sodium ring is also named “the arcus senilis”in medicine.It is the result of lipid deposition in corneal tissue【1】
2. Symptoms： brain insufficiency, hypertension, stiff neck, forgetful etc..
Fig 2.1 Sodium Ring [1] FenmingLi,DepartmentofOphthalmology，3417
Venous Congestion Ring is also named “K-F Ring”in medicine.It is the result of copper deposition in corneal tissue【1】
2. Symptoms： The function decline of liver and kidney, lack of sleep, slow response etc..
Fig 2.2 Venous Congestion Ring
[1] FenmingLi,DepartmentofOphthalmology，3864
IndonesiaExpertanalyzesthe
irisimagetodetectpancreas
diseases.40casesareused,
including34lesionsand6non
lesion,thesuccessratewas
94%[1]
Fig 2.3 Area is selected to detect pancreas diseases
【1】AdhiDharmaWibawa,MauridhiHeryPurnomo.EarlyDetectiononthe
ConditionofPancreasOrganastheCauseofDiabetesMellitusby RealTimeIris
ImageProcessing[J].CircuitsandSystems,APCCA.4-7Dec.Singapore,2006.
Indonesia'sIPutuDody
Lesmanaetal.12patients
areusedtodetectthe
pancreaticdiseasesbyiris
image，thesuccessrateis
83.3%【1】
Fig 2.4 Area is selected to detect pancreas diseases
【1】IPutuDodyLesmana，IKetutEddyPurnama.Abnormalcondition
detectionofpancreaticbeta-cellsasthecauseofdiabetesmellitusbasedon
irisTechnologyandBiomedicalEngineering（IEEE）2011
In China:
（1）Wang-Lin, Iris diagnosis is verified with high accuracy by analysis of 92 cases
（2）Gao_lin, Ding-Juan tested and verified the accuracy of the iris diagnosis （3） Dong-Feixia, Verify the iris diagnosis significance in the early chronic kidney disease by analysis of 150 cases
（4）Han-ping, Wang-Jiajia, Find that there is a certain correlation between Sub-health and iris abnormal features by analysis of 420 cases
3 Research on detection
method of abnormal features
in iris image
3. Research on detection method of
abnormal features in iris image
1 System design of iris diagnosis
2 Research on the method of iris image partition
3 Research on the detection method of radii solaris
4 Research on the detection method of autonomous nerve wreath
5 Research on the detection method of sodium Ring 6 Research on the detection method of plaque
7 Research on the detection method of specific regional abnormal features
3.1 System design of iris diagnosis
J. V. Martyshevcky etc【1】, design a computer aided diagnosis system .
【1】J.V.Martyshevcky,V.A.Kormilin,V.M
Khoroshaev.Computationalsystemof
iridodiagnostics，1996，Russia.
Fig 3.1 Iris diagnosis system
【1】Zuraini Othman，AntonSatria
PrabuwonoPreliminary StudyonIris
RecognitionSystem:Tissues ofBody
OrgansinIridologyIEEE EMBSConference
onBiomedicalEngineering&Sciences，
2010
Fig3.2 The improved iris diagnosis China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
system
Guangdong University of Technology , He Jia-Feng, etc., A system of computer-aided iridiagnosis in 2004.
Harbin Institute of Technology , Ma Lin , etc. Design and implementation of iris diagnosis information system，2006. China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
Foreign countries have developed related products：
（1）Telelris-Analysis System2002 from Canada （2）Patientdetails from USA
（3）Bexel IRINA system from Korea 。
The Bexel IRINA system has obtained FDA certification in Korea and Russia。
Iris diameter, area, the diameter of the pupil, boundary deformation degree, distance between the pupil center of the iris, detection of the autonomous nervous wreath 【1-2】。
Fig3.3 Detection results of Bexel IRINA system
[1]http://www.iridologyinternational.com/content/bexel-irina-software-research-cnriedu
[2]http://aprodeus.narod.ru/Information/Canada2001/Computerized_IRINA_Diagnostic_Rep
ort_.html.
3.2 Research on the method of iris image partition
Fig 3.4 iris image partition
Reference：MaLinetal.Studyontheirispartitionandsegmentation[J],
CombinedwiththenationalseminaroftraditionalChinesemedicineand
WesternMedicine2008:143-146.
3.3 Radii solaris detection
Fig 3.5 Detecting radii solaris based on Gaussian Filter
[1] BoShen,YongXu,GuangmingLu,DavidZhang.
DetectingIrisLacunaeBasedonGaussianFilter.ThirdInternationalConferenceon
InternationalInformationHidingandMultimediaSignalProcessing,2007.
Presence[C].InformationManagementandEngineering,ICIME’09.3-5April,Kuala
Lumpur,
Fig 3.5 Radii Solaris Extraction through Primitive Modelling
【1】Wangjunhui.RadiiSolarisExtractionthroughPrimitiveModelling SpringerVerlagBerlinHeidelberg2010.
Fig3.6 Radii Solaris Extraction through Hough transformation
Reference：XINGuo-dong,WANGWei.Studyonfeatureextractionincomputeraidediridology [J]ComputerEngineeringandDesign，27(18)3322-3325.
3.4 Autonomous nerve wreath detection
【1】XINGuo-dong,
WANGWei.Studyon
collarette extraction
[J].Computer
Engineeringand
Design.2008-5-,29
(9):2290-2292.
Fig 3.7 Extract the autonomous nerve wreath based
on the max sum of gray gradient
China-Korea
Bilmetrics Recognition Joint Seminnar（CKBR2013）
3.4 Autonomous nerve wreath detection
Fig 3.8 Extracting the autonomic nerve wreath of iris based on an improved
[1] LiYu,KuanquanWang,DavidZhang.
Extractingtheautonomicnervewreathofirisbasedonanimproved
snakeapproach[J].Neutrocomputing.2007
3.5 Sodium Ring detection
Fig 3.10 The process of Sodium Ring detection [1]R.A.Ramlee,S.Ranjit.
UsingIrisRecognitionAlgorithem,DetectingCholesterol2009.
3.6 Plaque detection
Fig 3.11 Plaque detection base on color information
[1]A.LodinandS.Demea,DesignofanIris-BasedMedicalDiagnosisSystem[C].
ProceedingInternationalSymposiumonSignals,CircuitsandSystems， IEEE2009.
3.6 Plaque detection
Fig 3.12 Iris Plaque Detection Method Based on Level Set
[1] XiaoNanLiu,WeiqiYuan.IrisPlaqueDetectionMethodBasedonLevel
Set[C].CCBR2011
3.7 Specific regional abnormal feature detection
Fig 3.13 The detection of pancreatic beta-cells [1] IPutuDodyLesmana，IKetutEddyPurnama.Abnormalcondition
detectionofpancreaticbeta-cellsasthecauseofdiabetesmellitusbasedon
irisTechnologyandBiomedicalEngineering（IEEE）2011
3.7 Specific regional abnormal feature detection
Fig 3.14 Early Detection on the Condition of Pancreas Organ [1] AdhiDharmaWibawa,MauridhiHeryPurnomo.EarlyDetectionontheCondition
ofPancreasOrganastheCauseofDiabetesMellitusbyRealTime IrisImage
Processing[J].CircuitsandSystems,APCCA.4-7Dec.Singapore,2006.
4 The present problems and
our job
4 Problems and our job
Problems:
（1）The image acquisition equipment Fig 4.1 The image acquisition equipment and iris image
The work already undertaken:
Fig 4.2 The iris image acquisition device is developed
Problems：
（2）Building the iris image database
Fig 4.3 Related data we used to build the iris image database
The work already undertaken:
In cooperation with Shenyang Medical College Fengtian Hospital to build the iris image database.
Fig 4.4 The Cooperation Department China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
Problems：
（3）Detection method for abnormal features needs further improvement
Fig 4.5 Detection method for abnormal features China-Korea Bilmetrics Recognition Joint Seminnar（CKBR2013）
Thanks for your attention!
Welcome the valuable advice !

iridology bernard jensen

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