Table Of ContentStudies in Computational Intelligence 417
Editor-in-Chief
Prof.JanuszKacprzyk
SystemsResearchInstitute
PolishAcademyofSciences
ul.Newelska6
01-447Warsaw
Poland
E-mail:[email protected]
Forfurthervolumes:
http://www.springer.com/series/7092
Valentina Emilia Balas, János Fodor,
and Annamária R. Várkonyi-Kóczy (Eds.)
New Concepts and
Applications in Soft Computing
ABC
Editors
Prof.ValentinaEmiliaBalas Prof.AnnamáriaR.Várkonyi-Kóczy
DepartmentofAutomationand DepartmentofMechatronicsand
AppliedInformatics VehicleEngineering
FacultyofEngineering ÓbudaUniversity
“AurelVlaicu”UniversityofArad Budapest
Arad Hungary
Romania
Prof.Dr.JánosFodor
InstituteofIntelligentEngineeringSystems
JohnvonNeumannFacultyofInformatics
ÓbudaUniversity
Budapest
Hungary
ISSN1860-949X e-ISSN1860-9503
ISBN978-3-642-28958-3 e-ISBN978-3-642-28959-0
DOI10.1007/978-3-642-28959-0
SpringerHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2012935577
(cid:2)c Springer-VerlagBerlinHeidelberg2013
Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartofthe
materialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation,broad-
casting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformationstorage
andretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodologynowknown
orhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnectionwithreviews
orscholarly analysis ormaterial suppliedspecifically forthepurposeofbeingentered andexecuted ona
computersystem,forexclusive usebythepurchaser ofthework.Duplication ofthis publication orparts
thereofispermittedonlyundertheprovisionsoftheCopyrightLawofthePublisher’slocation,initscur-
rentversion,andpermissionforusemustalways beobtained fromSpringer. Permissionsforusemaybe
obtainedthroughRightsLinkattheCopyrightClearanceCenter.Violationsareliabletoprosecutionunder
therespectiveCopyrightLaw.
Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication
doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant
protectivelawsandregulationsandthereforefreeforgeneraluse.
Whiletheadviceandinformationinthisbookarebelievedtobetrueandaccurateatthedateofpublication,
neither the authors northe editors nor the publisher can accept any legal responsibility for any errors or
omissionsthatmaybemade.Thepublishermakesnowarranty,expressorimplied,withrespecttothematerial
containedherein.
Printedonacid-freepaper
SpringerispartofSpringerScience+BusinessMedia(www.springer.com)
Preface
The book New Concepts and Applications in Soft Computing includes recent
theoretical foundationsand practical applications as extended works presented in the
InternationalWorkshopSOFA2009,SOFA2010andadditionalpapers.
SOFA(SOFtcomputingApplication)isawell-recognisedinternationalIEEEevent
proposingtoeacheditionnewresearchontheinnovativeapplicationsofadvancessoft
computingparadigms.
TheideaofSoftComputingwasinitiatedin1981whenProfessorZadehpublished
hisfirstpaperonsoftdataanalysisandconstantlyevolvedeversince.ProfessorZadeh
definedSoftComputingasthefusionofthefieldsoffuzzylogic(FL),neuralnetwork
theory (NN) and probabilistic reasoning (PR), with the latter subsuming belief net-
works, evolutionarycomputingincludingDNA computing,chaos theory and parts of
learning theory into one multidisciplinary system. As Zadeh said the essence of soft
computing is that unlike the traditional, hard computing, soft computing is aimed at
anaccommodationwiththepervasiveimprecisionoftherealworld.Thus,theguiding
principleofsoftcomputingistoexploitthetoleranceforimprecision,uncertaintyand
partialtruthtoachievetractability,robustness,lowsolutioncostandbetterrapportwith
reality.Inthefinalanalysis,therolemodelforsoftcomputingisthehumanmind.
The applications of Soft Computing helps solving nonlinear problems, in which
mathematical models are not available and introduce the human knowledge such as
cognition,recognition,understanding,learningandothersintothefieldsofcomputing.
Furthermore,they open the way for constructingintelligent systems like autonomous
self-tuningsystems,andautomateddesignedsystems.
Thefactthatnaturallanguageisfuzzyisfullyacceptedandverywellknownthese
days.However,itis notquiteexpectedthatan artificialformallanguagein whichthe
vocabularyispurelynumericaltosharethevaguenessofthenaturallanguage.Suchan
exampleisgivenherealongtheChapter1 byValentinaE. Balas, IuliaM. Motocand
AlinaBarbulescuwhichpointoutthatbinaryiriscodesarenothingelsethanimprecise
informationaboutsomerealiridesandtherefore,theirmatchingisfuzzy.Ontheother
hand,practicingaTuringtestofirisrecognitionshowsthatahumanneedsonlytwoval-
ues(0and1)toencodethemeaningofthetwodifferent,complementaryandmutually
exclusiveconcepts(namely‘genuine’and‘imposter’comparisons)whereasastatistical
VI Preface
irisrecognitionsystemencodesthesimilaritybetweentwoiridesusingcertainmethods
ofcomputingavaguesimilarityscorebelongingin[0,1]interval.Hence,theconcepts
‘genuine’and‘imposter’arecrispinhumanperception/understandingand,paradoxi-
cally,theyarefuzzyintheartificialperceptionofanartificialsoftwareagentpracticing
statisticalrecognition.Thefactthatintheartificialperceptionofsomeirisrecognition
system the two conceptsare seen as beinginsufficiently distinct(the genuineand the
imposterscoresdefinetwofuzzyintervalswhicharesimultaneouslydifferentinmean-
ing and overlapping each other), and consequently not quite complementary and not
quite mutually exclusive,is nota reason to believethat the iris recognitionand those
two conceptsare indeed fuzzy in their nature. This fact provesonly how much room
for improvement exists between two paradigms of iris recognition, namely between
the presentstatistical / bimodaliris recognitionapproaches,on the one hand, and the
naturalrecognitioncertifiedasbeingpossiblebytheTuringtest,ontheother.Toward
such an improvement, Chapter 1 shows that combining Haar-Hilbert and Log-Gabor
encodingincreasesirisrecognitionperformanceleadingtoalessambiguousbiometric
decisionlandscapeinwhichtheoverlapbetweentheexperimentalintra-andinter-class
scoredistributionsdiminishesorevenvanishes.Haar-Hilbert,Log-Gaborandcombined
Haar-HilbertandLog-Gaborencodersaretested,bothforsingleanddualirisapproach.
Theexperimentalresultsconfirmthatthebestperformanceisobtainedforthedualiris
approach when the iris code is generated using the combined Haar-Hilbert and Log-
Gabor encoder, and when the matching score fuses the information from both Haar-
HilbertandLog-Gaborchannelsofthecombinedencoder.
Chapter 2 by Alex Torma´si and Ja´nos Botzheim introduces a new on-line single-
strokerecognitionmethodbasedonfuzzylogic.Eachofthecharactersaredefinedby
onlyoneninedimensionalfuzzyrule.Inadditiontothelowresourcerequirement,the
solutionisabletosatisfymanyoftheuser’scurrentdemandsinhandwritingrecogniz-
ers,likespeedandlearning.Eightoftheninefeaturesareextractedusingafour-by-four
grid.Forthelearningphasetheauthorsdesignedanewpunish/rewardbacterialevolu-
tionaryalgorithmthattunesthecharacterparametersrepresentedbyfuzzysets.
Chapter3byTudorBarbu,MihaelaCostinandAdrianCiobanuprovidesandcom-
parestwocolor-basedimageretrievaltechniquesforRGBimagedatabases.Theirpro-
posed CBIR systems use the query by example approach and a relevance feedback
mechanism.The feature extractionprocess is performedby computinga globalcolor
histogramforeachimage.Featurevectorsarefirstcomparedusingthehistograminter-
sectiondifferencemetric.A distancebasedon Chi-squaredmeasureis also proposed.
Arelevancefeedbackmechanismisusedintheretrievalprocessinbothretrievalcases.
Chapter4byDraganG.Radojevic´showsthatReal-valuedimplication(R-implication)
isaBooleanconsistentgeneralizationoftheclassicalbinaryimplication.R-implication
plays importantroles in real-valued set (R-set) theory as a generalizationof classical
set theory as well as in many applications such as morphologyin image processing,
associationrulesindatamininganddecisionmakinggenerally.
Inchapter5theauthorsToma-LeonidaDragomir,Flavius-MaximPetcu¸tandAdrian
Korodi show that the maximum power point tracking strategies designed to control
the solar panels are based on using as referencesthe coordinatesof maximumpower
pointofthesolarpanelexternalcharacteristicI(V).Thetrackingproblemmakessense
Preface VII
due to the variability of the external characteristic with respect to panel temperature
and total radiation absorbed by the panel. The chapter presents a solution to obtain
the coordinate of the maximum power point from the variable that may be directly
measured:airtemperature,normaldirectradiationanddiffusehorizontalradiation.As
startingpointtodevelopthemodelofthesolarpanelandtoextractthemaximumpower
point coordinates, a two diodes electrical circuit was considered. Finally, a generator
block consisting in a look up model is designed. Because for practical cases only a
smallnumberofexperimentalexternalcharacteristicsareavailable,thegeneratoruses
a global interpolation method. The presentation is built on a case study that exploits
experimentalcharacteristicstakenfromreferences.
Chapter 6 by Hooman Tahayori and Alireza Sadeghian introduced the concept of
ShadowedFuzzySetandsomeofitsrelatedoperations.ShadowedFuzzySetenables
localizationoftheunderlyinguncertaintyoffuzzygradesintype-2fuzzysetsthrough
exploitationofshadowedsets.Itprovidesacapableframeworkthatdespitepreserving
the uncertainties of fuzzy grades in type-2 fuzzy sets, adheres the simplicity of the
conceptandoperationsofintervaltype-2fuzzysets.
In chapter 7 by Viorel Nicolau the variations of sound speed in air as a function
of air properties are studied, along with their influence on the accuracy of ultrasonic
sensing.Themostimportantaircharacteristicisairtemperature,whiletheairpressure
andrelativehumidityaffectthesoundspeed,especiallyathightemperaturevalues.The
influenceofCO2 concentrationonthesoundspeedisverysmall.Fuzzyrulesaregen-
erated forsound speedvaluesused in outdoorapplications.Also, fuzzy estimation of
soundspeedisstudied,usingexpertrulesgeneratedfromthesoundspeedmodel.Dif-
ferentfuzzysystemsweretested,withvariousmembershipfunctionsandfuzzyrules.
The selection was made based on the relative error and the mean square error of the
fuzzyoutput,comparedwiththeoutputofsoundspeedmodel.Accurateestimationof
soundspeedisobtained.Theoutputsurfaceandtherelativeerroroftheselectedfuzzy
estimatorarealsopresented.
Chapter 8 by Hsunhsun Chung discussed on some membership functions and ap-
proximate reasoning conducted with these membership functions. The author also
explains how to apply approximate reasoning to educational evaluation. For the pur-
pose, the author evaluates a student’s work (drawing) by approximate reasoning and
discussesthepracticaleffectivenessoftheanalysismethod.
Chapter9byTudorBarbu,MihaelaCostin andAdrianCiobanuproposedanunsu-
pervisedautomaticmoment-basedimagerecognitiontechnique.Thepracticalproblem
hereisclassifyingtheimagesfromaset,usingthecontentsimilarity.Inthefeatureex-
tractionstage,theauthorscomputeasetoffeaturevectorsusingdiscreteareamoments.
Anautomaticunsupervisedfeaturevectorclassificationmethodisfurtherproposed.It
usesahierarchicalagglomerativeclusteringalgorithm,theoptimalnumberofclusters
beingdeterminedusingsomevalidationindexes.Someexperimentsperformedwiththe
proposedapproacharealsodescribedinthisarticle.
Chapter10byCorneliaGyo˝ro¨di,RobertGyo˝ro¨di,MihaiDersidan,GeorgePecherle
andLiviaBandicidescribesanimprovedhebbianneuralnetworkthathasthecapability
ofaddingnewneuronstoitandcanconnectneuronsusinganassociationrule.Sincethe
mainprobleminneuralnetworkdesignistheactualconstructionoftheinter-neuronal
VIII Preface
relations,theauthorstrytosolvethisissueatleastpartiallybyallowingthenetworkto
modifyitselfdependingonitsresponsetodifferentstimuli.
Chapter11byAlinaMa˘da˘linaLonea,HuagloryTianfieldandDanielaElenaPopescu
presentsthefundamentalsofCloudComputing.Afterwards,thetechnicalsecurityas-
pectsinCloudComputingareclassifiedfromtwoperspectives:webapplicationssecu-
rity issues and virtualization security issues. Both security issues include the threats
implied with their mitigation techniques, which consolidates the request to provide
anadequateIdentityandManagementarchitectureforCloudComputing.Further,this
paper addresses the Identity and Access Management(IAM) security categoryof the
CloudComputingfield,whichincludesthesecurityrequirements,thestandardsofin-
terest and the current Identity and Access Management solutions. A trusted Identity
and Access Managementarchitecture for cloud services assumes establishing the list
ofthesecurityrequirementsandusingthesuitablestandards.Thepaperalsorelatesan
evaluationoftheexistingIdentityAccessManagementsolutions.
Chapter12byEugenIoanGergely,LauraCoroiuandHelgaMariaSilaghifocuseson
anewtechniqueforanalyzingthedependabilityofPLCI/Omodules.Thistechniqueis
basedonthemodeinwhichtheI/Omodulesfulfilltheirtasksandnotontheirstructure.
SuchanapproachallowsaunifiedanalysisofI/Omodules,regardlessoftheirtype,for
almosttheentireanalysiswork.TheparticularizationoftheI/Omoduletypebecomes
necessaryonlyatthefinalstageoftheanalysis.Therearerealizedqualitative&quan-
titative analyses of I/O modulesdependability.For this, and because reliability is not
aneloquentparameterinanysituation,therearedefinedprobabilisticparametersboth
foroneI/OpointandforI/Opointssystems.Inaddition,therearemadecomparisons
betweensomeI/Opointconfigurations.Finally,thereareproposedseveralarchitectures
consideredoptimalandtheprocessesforwhichtheymaybesuitable.
We believe that research on soft computing will stimulate the interest among
researchers and practitioners in this field. We hope that the reader will share our ex-
citementandfindourvolumebothusefulandinspiring.
Theeditorsaregratefultotheauthorsandreviewersfortheirgreatcontribution.
We are also gratefullyto Prof. Janusz Kacprzyk(Editor-in-Chief,SpringerStudies
inComputationalIntelligenceSeries)forgivingustheopportunitytopublishthebook
asGuestEditors.
Special thanks go to Dr. Thomas Ditzinger (Springer EngineeringInhouse Editor)
forhispatienceandexcellentcollaborationduringtheelaborationofthisvolume.
We acknowledge with our thanks the editorial team of Springer-Verlag for their
supportduringthepreparationofthemanuscript
ValentinaEmiliaBalas–Romania
Ja´nosFodor–Hungary
Annama´riaR.Va´rkonyi-Ko´czy–Hungary
Contents
CombinedHaar-HilbertandLog-GaborBasedIrisEncoders ............ 1
ValentinaE.Balas,IuliaM.Motoc,AlinaBarbulescu
Single-StrokeCharacterRecognitionwithFuzzyMethod ................ 27
AlexTorma´si,Ja´nosBotzheim
Color-BasedImageRetrievalApproachesUsingaRelevanceFeedback
Scheme .......................................................... 47
TudorBarbu,MihaelaCostin,AdrianCiobanu
Real-ValuedImplicationasGeneralizedBooleanPolynomial ............. 57
DraganG.Radojevic´
ReferenceValueGeneratorofMaximumPowerPointCoordinatesofthe
PhotovoltaicPanelExternalCharacteristic ............................ 71
Toma-LeonidaDragomir,Flavius-MaximPetcu¸t,AdrianKorodi
ShadowedFuzzySets:AFrameworkwithMoreFreedomDegreesfor
HandlingUncertaintiesThanIntervalType-2FuzzySetsandLower
ComputationalComplexityThanGeneralType-2FuzzySets............. 97
HoomanTahayori,AlirezaSadeghian
Sound Speed EstimationUsing Fuzzy Logic Approachfor Outdoor
UltrasonicApplications ............................................ 119
ViorelNicolau
ApplicationofApproximateReasoningUsingTriangularandSine-curved
MembershipFunctions............................................. 141
HsunhsunChung
AnUnsupervisedContent-BasedImageRecognitionTechnique........... 157
TudorBarbu,MihaelaCostin,AdrianCiobanu
X Contents
AnImprovedHebbianNeuralNetworkwithDynamicNeuronalLifeand
RelationsandItsConnectiontoaDecisionGroup ...................... 165
Cornelia Gyo˝ro¨di, Robert Gyo˝ro¨di,Mihai Dersidan, George Pecherle,
LiviaBandici
IdentityManagementforCloudComputing ........................... 175
AlinaMa˘da˘linaLonea,HuagloryTianfield,DanielaElenaPopescu
DependabilityAnalysisofPLCI/OSystemsUsedinCriticalIndustrial
Applications...................................................... 201
EugenIoanGergely,LauraCoroiu,HelgaMariaSilaghi
AuthorIndex ........................................................ 219
Combined Haar-Hilbert and Log-Gabor
Based Iris Encoders
Valentina E. Balas1,*, Iulia M. Motoc2,**, and Alina Barbulescu3,***
1 Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania
[email protected]
2 Artificial Intelligence and Computational Logic Laboratory,
Department of Mathematics and Computer Science,
Spiru Haret University, Bucharest, Romania
[email protected]
3 Faculty of Mathematics and Computers Science,
Ovidius University of Constanta, Romania
[email protected]
Abstract. This chapter shows that combining Haar-Hilbert and Log-Gabor
improves iris recognition performance leading to a less ambiguous biometric
decision landscape in which the overlap between the experimental intra- and
inter-class score distributions diminishes or even vanishes. Haar-Hilbert, Log-
Gabor and combined Haar-Hilbert and Log-Gabor encoders are tested here both
for single and dual iris approach. The experimental results confirm that the best
performance is obtained for the dual iris approach when the iris code is
generated using the combined Haar-Hilbert and Log-Gabor encoder, and when
the matching score fuses the information from both Haar-Hilbert and
Log-Gabor channels of the combined encoder.
1 Introduction
In 1970s, Flom and Safir [11], two American ophthalmologists noticed that the iris
texture differs from one person to another and later asked Daugman to develop a sys-
tem for identifying persons using their iris. The system patented by Daugman in 1994
[4] and based on a 2-dimensional Gabor filter was the first fully functional iris recog-
nition system. In the same period, Wildes et al [61] proposed a different iris recogni-
tion system.
Compared to 1990s, iris recognition is nowadays a relatively popular research topic,
many new segmentation, encoding or matching methods being proposed in the last two
decades as original solutions produced by well-established research teams from Bath
University ([29], [47]), CASIA ([23]-[25], [54]-[57]), NIST ([13], [31]), Notre-Dame
University ([1], [18], [22], [33]), Kent University ([46], [51], ) or by individual re-
searchers around the world: L. Masek - [28], C. Tisee [59], S. Yang [62], S. Yoon [63],
* IEEE Senior Member, Associate Professor.
** IEEE Student Member.
*** Associate Professor.
V.E. Balas et al. (Eds.): New Concepts and Applications in Soft Computing, SCI 417, pp. 1–26.
springerlink.com © Springer-Verlag Berlin Heidelberg 2013
