Are there population differences in minutiae frequencies? A comparative study of two Argentinian population samples and one Spanish sample

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Author's personal copy

Are

there

population

differences

in

minutiae

frequencies?

A

comparative

study

of

two

Argentinian

population

samples

and

one

Spanish

sample

Esperanza

Gutie´rrez-Redomero

*

,

Noemı´ Rivalderı´a

,

Concepcio´n

Alonso-Rodrı´guez

,

Luis

M.

Martı´n

,

Jose´ E.

Dipierri

,

Miguel

A.

Ferna´ndez-Peire

,

Ricardo

Morillo

a

DepartamentodeZoologı´ayAntropologı´aFı´sica,FacultaddeBiologı´a,UniversidaddeAlcala´,Alcala´ deHenares,Spain

b

DepartamentodeMatema´ticas,FacultaddeBiologı´a,UniversidaddeAlcala´,Alcala´ deHenares,Spain

c_{BrigadadePolicı´aCientı´ficadelaComisarı´adeAlcala´ deHenares,Spain}

d_{InstitutoUniversitariodeInvestigacio´nenCienciasPoliciales,UniversidaddeAlcala´,Alcala´ deHenares,Spain} e

InstitutodeBiologı´adelaAltura,UniversidadNacionaldeJujuy,Argentina

f

Comisarı´aGeneraldePolicı´aCientı´fica,Madrid,Spain

1. Introduction

Theskinontheinnerhandsandfingersandonthesolesofthe feetandtoesischaracterizedbyalternatingstripsofraisedridges andfurrowsarrangedinavarietyofpatternsandiscalledfriction skin.Thefrictionskinistheouterlayerofskinthatcontainsmany of the elements and characteristics we use to identify and individualizeaprint.Fingerprintsaretheimpressionor reproduc-tionleftonanymaterialbythefrictionskinofthefingers,andthe scientificstudyoffingerprintsforthepurposeofidentificationis knownasDactyloscopy[1–3].

The formation of epidermal ridges occurs very early on in prenataldevelopment[4,5].Dermalpapillaeridgesarepolygenic

characteristicswithenvironmentaleffectslimitedtothefirstfew monthsofembryoniclife[6].Onceformed,andintheabsenceof lesions,theseridgeswillremainessentiallyunchangedthroughout thelifeoftheindividual.Theexceptionisthat,likeotherpartsof theanatomy,thefingerprintsorfrictionskinincreaseinsizeasthe bodygrows[7].Studiesoftheirvariabilityinhumanpopulations have demonstrated the usefulness of the information obtained aboutthesecharacteristicsforunderstandingtheevolution and geneticstructureof humanpopulations [8,9],forcharacterizing syndromesanddiseases[10–12],andforpersonalidentificationin thefieldofForensicScience[13–15].

Oneofthebasicproceduresintheidentificationprocessusing fingerprintimpressionsisacomparisonoftheminutiaefoundin fingermarksobtainedatthesceneofthecrimewiththoseobserved inthefingerprintstakenfromthesuspect.Theproblemisthatthe minutiae, a term coined by Galton [16] to refer to the small distinguishingfeaturesfoundalongeachindividualridge,present aninter-andintra-populationalvariabilitywhichhasbeenpoorly studied, despite constituting the basis for identification from fingerprintimpressionsinthefieldofCriminalistics,see[17,18]. ForensicScienceInternational222(2012)266–276

ARTICLE INFO

Articlehistory:

Received26August2011 Receivedinrevisedform9June2012 Accepted4July2012

Availableonline25July2012

Keywords:

Fingerprints

Minutiae

Frequencies Identification Argentinapopulation Spanishpopulation

ABSTRACT

Inrecentyears,bothscientificandjudicialsourceshavehighlightedtheneedformoreknowledgeabout minutiaevariability,inordertoimprovetheirstatisticalapplicationtofingerprintidentification.Inline withthistrendtowardimprovingourknowledgeofthissubject,theaimofthepresentstudywasto calculatethefrequencywithwhich20typesofminutiaeappearedin2780fingerprintimpressions obtainedfrom278individualsfromtwoArgentinianpopulationsamples(100individualsfromRamal and178fromPuna–Quebrada).Thedifferenttypesofminutiaewerelocated,identified,andquantified visuallyintwoareasonthefingerprint,theinsideandoutsideofacircle,theradiusofwhichcutfifteen ridges perpendicularly, starting from the center cut of the axes defining the sectors. The non-equiprobabilityfoundinbothpopulationsamplesforthedifferentminutiaetypesstudieddemonstrated that the evidential weight provided by these characteristics is not the same when applied in identificationprocesses,whetherusedquantitatively(numericalstandard)orqualitatively(holistic method).Theresultsobtainedforbothpopulationswerecomparedstatisticallywiththosepublished previouslyforaSpanishpopulationsample,whichhadbeencollectedusingthesamemethodology.This comparisonhasenabledustodemonstrate,forthefirsttime,theexistenceofsignificantdifferences betweenpopulationsinminutiaefrequencies,independentlyfromthemainpatterntype.

ß2012ElsevierIrelandLtd.Allrightsreserved.

* Correspondingauthorat: DepartamentodeZoologı´ay Antropologı´aFı´sica, UniversidaddeAlcala´,CampusUniversitario,Crta.Madrid-BarcelonaKm33,6,E 28871,Alcala´ deHenares(Madrid),Spain.Tel.:+34918855074;

fax:+34918855080.

E-mailaddress:[email protected](E.Gutie´rrez-Redomero).

ContentslistsavailableatSciVerseScienceDirect

Forensic

Science

International

j o urn a l hom e pa g e : ww w . e l se v i e r. c om / l oca t e / f ors ci i nt

0379-0738/$–seefrontmatterß 2012ElsevierIrelandLtd.Allrightsreserved.

Recent challenges to fingerprint evidence in court have strengthened the need for statistical research to underpin the fingerprintidentificationprocess.Theproblemoftheuniqueness of fingerprintimpressionswasearlieraddressed[16],andsince then, various models have been proposed for establishing this uniqueidentity,acriticalanalysisofthemodelsproposedhasbeen madebyStoneyandThornton[19],Stoney[20]andSrihariand Srinivasan[21].Thesemodelshavebeenbasedonvery heteroge-neous, and generally very small, samples and very disparate approaches(studyingdifferenttypesofminutiae,different finger-print patterns, different fingers and different finger areas) see [17,18]. Recently, Neumann et al. [22–24] and Egli et al. [25] reportedontheuseoflikelihoodratiosasameansofobjectively assessingtheevidentialweightofcorrespondingminutiaebetween afingermarkandafingerprint.

Thegrowingrigorwithwhichforensicevidenceisexaminedin thelegislativeareahasresultedintheneedtoreconsidersomeof the basic principles that support forensic disciplines in their recognition assciences[26–38].Inthefieldoffingerprints, itis necessary to study and analyze the scientific principles that determinetheprocessofindividualizationinhumanidentification. Any attempt to establish such premises must be based on increasing knowledge about of minutiae variability, given that these are one of the cornerstones of fingerprint identification, whetherusedquantitatively(numericalstandard)orqualitatively (holisticapproach)[2,18,35–39].Linkedtothisissue,theNational Academyof Sciences(NAS)publishedareportofgreat interna-tional impact entitled ‘‘Strengthening Forensic Science in the UnitedStates.Apathforward’’,[35]whichcitedastudycarriedout with a Spanish population as being one of the few statistical studiesofpopulationswhichhavebeenconductedinthisfieldin recentyears[17],andemphasizedtheneedtoimproveknowledge aboutvariabilityinfingerprintcharacteristics.

In the study conducted on a sample of Spanish population [17,38]thedifferenttypesofminutiaewerelocated,identified,and quantifiedvisuallyonthefingerprint,followinganewmethodof standardization,andtheseshowedsignificantdifferencesbetween intrafingers(topological),interfingers,andgender,whichgiveeach of thetypes ofminutiae a differentdiscriminatoryvalue in the processofidentification.Theaimofthisresearchwastoconducta morein-depthstudyonminutiaevariabilityinotherpopulations following the methodology used previously, thus enabling a comparisonoftheresults.

2. Materialsandmethods

UndertheaegisofaprojectfundedbytheSpanishAgencyfor InternationalCooperation(AECI)forthestudyand characteriza-tionoftheArgentinianpopulation,sampleswerecollectedfrom different populations in the northwesternmost region of the country.Presentinggreatgeographicalheterogeneity,thisregion canbedividedintofourclearlydefinedecologicalunits,regarding totheelevationoraltitudeinmetersabovesealevel(m.a.s.l.):Puna (3500m.a.s.l.),Quebrada(2500m.a.s.l.),Valle(1200m.a.s.l.)and Ramal (500 m.a.s.l.), which have been settled by different populationswitha commongeneticandculturalorigin[40,41]. Fingerprintimpressionsfromalltenfingerswerecollectedfroma sampleofadultindividualsofbothsexesinthreeoftheregions mentionedabove:PunaandQuebrada(>2500m.a.s.l.)andRamal (500m.a.s.l.).

The samples were collected at the Police Academy at San Salvador deJujuyandat variouseducationalinstitutionsin the province,withtheinformedconsentof theindividualsstudied. Sampleswerecollectedfromatotalof278adultindividuals.Of these,100(51malesand49females)werefromthecityofSan PedrodeJujuy,locatedintheRamalregion,and178(85malesand

93females)werefromdifferentlocationsintheregionsofPuna andQuebrada.Totalsamplesize,therefore,was2780fingerprint impressions.Subjectoccupationwastakenintoaccount,andthose whowereemployedinmanualworkwereexcludedfromthestudy asthiscouldaffectthemorphologicalanalysisofdermalpapillae ridges.

Thetechniqueusedtocollectfingerprintimpressionswasa variationontheadhesivepaperandgraphitemethoddescribed byAaseandLyons[42].Fingertippapillaeridgeswerestained homogeneouslywithgraphitepowderandthenrolledoverthe sticky side of an appropriatelysized label.Next, these labels were stuck to transparent acetate sheets which had been designed so that each sheet had ten separate areas for depositing each of the ten fingerprint impressions obtained from a single individual. The fingers were assigned the numbers 1–10, starting from the right thumb, or finger 1 (F1),and endingwith theleftlittlefinger,or finger10(F10). Theimageofthefingerprintimpressionthusobtainedprovides amirrorimageofthefingerprint,similartothatachievedusing the classicalink and paper technique.The fingerprints were digitalized,fingerbyfinger,onthepremisesoftheCommissary of Scientific Police at Alcala´ de Henares (Madrid). Each true color(24bit)jpgimagehadasizeof14962002pixels,witha resolutionof 200ppior 79pixels/cm.

Identification of theminutiae in this study was based on a modifiedversion,see[17,38],oftheclassificationsystemusedby theSpanishScientificPolice[43].Atotalof20typesofminutiae were identified and quantified visually on the inside and the outside of a circle, the radius of which cuts fifteen ridges perpendicularly,inoneofthedistalquadrants,startingfromthe centercutofthetwoperpendicularaxeslocatedatthecenterofthe fingerprint(Fig.1).Thestandardizationchosenforthisstudyhas beendonewiththeaimofcomparingthecentralandperipheral areasofthefingerprintinallpatterntypes(arches,radialloops, ulnarloops,andwhorls).Therefore,thestandardizationhasbeen made,seekingadistributionofareas,similarinsize,sothatthe designedcircleremains locatedinthecentralareaofthefinger (whichispickedupmorefrequentlyinfingermarks).Thisallowsus toassessthecompletetopologicaldistributionoftheminutiaeon thefingerprint’ssurfaceandtocreateresultscomparableacross populations (Spanish and Argentinian). The circle is used to eliminate, asfaraspossible,theeffectof fingersize.Thus, this standardization allows comparison of minutiae frequencies be-tweendifferentfingers,gendersandpopulations.

Thisfacilitatedtheindividualizationof5560ridgecountareas for analysis; i.e., 2 areas (outside and inside circle) on 2780 fingerprints (Fig. 1), on which 233,251 minutiae were found. Codingofthefingerprintsallowedustobuildadatabaseconsisting of 278 individualsand 412variablesby individual (number of minutiaecountedin2areas10fingers20typesofminutiae, sex, placeof birth and general pattern type for each of the10 fingers).

Author's personal copy

Theresultsobtainedfromthisstudyof Argentiniansamples were compared with those of a Spanish population sample, collected andanalyzedin aprevious study[38]usingthesame methodology. To compare the data obtained for the three populations,weusedthetestfordifferencebetweenproportions and the test for independence of characteristics (Chi-square), conductingacorrespondenceanalysiswheneverdependencewas detected. Furthermore, the interpopulation comparison of the minutiae frequencies has been conditioned by general pattern (arch,loop,andwhorl).

3. Results

The minutiae frequencies, for the total sample and by sex, obtained from 1000 fingerprint impressions from the Ramal sampleand1780fromthePuna–Quebradasampleareshownin Tables 1 and 2, respectively. For the total sample (males and

females),andforbothpopulations,weobservedthatthefrequency ofendings(E)wasconsiderablyhigherthantherestoftheminutiae (Ramal: 50.14%; Puna–Quebrada: 51.69%), followed by the frequency of bifurcations (B) (Ramal: 21.17%, Puna–Quebrada: 19.91%) and convergences (C)(Ramal: 19.19%,Puna–Quebrada: 18.28%). The restof theminutiae presentedconsiderably lower frequencies.IntheRamalsample(Table1),fragments(F),whether large (F-BG) or small (F-SM), crossbars (CR) and bridges (BD) presentedfrequencieswhichrangedfrom1%to2%;whilstinthe Puna–Quebradasample(Table2),fragments(F),whetherlarge (F-BG)orsmall(F-SM),breaks(BR)andpointsbetweenridges(P-BW) werethecharacteristicswhichpresentedfrequenciesbetween1% and2%.Theremainingminutiaeanalyzedpresentedfrequenciesof less than 1%. The distribution of minutiae frequencies in both populations highlighted their non-equiprobability (p<0.01). Insidethe circle,both populations presentedlower frequencies forendings(E)thantheypresentedoutsidethecircle.Incontrast, Fig.1.Idealizationof20typesofminutiaeusedinthisstudyandridgecountareas(insideandoutsidethecircle).

Table1

FrequenciesregisteredforminutiaefromtheRamalsample,totals,malesandfemales,insideandoutsidethecircleandtotalarea(ofthetenfingers),n=totalnumberof

minutiae,a

,b

p<0.05.

Total(n=85,269) Males(n=44,923) Females(n=40,346)

Totalarea Insidecircle Outsidecircle Totalarea Insidecircle Outsidecircle Totalarea Insidecircle Outsidecircle

E 50.139 45.495 53.168 49.638 45.045 52.511a

50.696 45.970 53.926a

B 21.166 24.015 19.308 21.848 24.967b _{19.898 20.406 23.009}b _18.627

C 19.188 20.221 18.513 19.841 20.836 19.218 18.460 19.571 17.701

F-BG 1.093 1.043 1.126 0.966 0.879 1.020 1.234 1.215 1.247

F-SM 1.495 1.420 1.544 1.269 1.221 1.299 1.747 1.630 1.827

BR 0.814 0.838 0.798 0.759 0.821 0.720 0.875 0.855 0.889

EN-BG 0.911 1.245 0.694 0.850 1.192 0.637 0.979 1.301 0.759

EN-SM 0.774 1.153 0.527 0.748 1.145 0.499 0.803 1.160 0.559

P-BW 0.493 0.556 0.452 0.414 0.486 0.369 0.580 0.629 0.547

P-IN 0.063 0.059 0.066 0.049 0.075 0.033 0.079 0.043 0.104

O 0.751 0.654 0.814 0.735 0.619 0.807 0.768 0.690 0.822

CR 1.328 0.891 1.612 1.701 1.041 2.113 0.912 0.733 1.035

BD 1.230 1.673 0.942 0.761 1.093 0.554 1.752 2.284 1.389

OB 0.224 0.258 0.202 0.127 0.150 0.112 0.332 0.372 0.305

D 0.054 0.056 0.052 0.038 0.040 0.036 0.072 0.073 0.071

TF-B 0.056 0.107 0.023 0.047 0.098 0.014 0.067 0.116 0.033

TF-C 0.024 0.045 0.010 0.013 0.035 0.000 0.035 0.055 0.021

M-B 0.101 0.128 0.083 0.093 0.110 0.083 0.109 0.147 0.083

M-C 0.097 0.146 0.066 0.102 0.145 0.076 0.092 0.147 0.054

E.Gutie´rrez-Redomeroetal./ForensicScienceInternational222(2012)266–276

bifurcations(B)andconvergences(C)weremorefrequentinside the circle. These differences were statistically significant in all cases(Tables1and2).

IntheRamalsample,acomparisonbetweenthesexesshowed thatmalespresentedsignificantlymorebifurcations(B)insidethe circle and fewerendings (E) outside it than females (Table 1). Convergences (C) were more frequent in the males than the females,bothinsideandoutsidethecircle.InthePuna–Quebrada sample(Table2),wefoundthatthemalespresentedsignificantly more endings(E) andfewerconvergences(C)thanthefemales, both inside and outside the circle. Significant differences for bifurcations(B)wereonlyfoundoutsidethecircle,andthesewere lessfrequentinthemales.

The distribution of the different types of minutiae was significantly dependent on finger area (inside and outside the circle)andsex.Thecorrespondenceanalysisforbothpopulationsis showninFig.2.IntheRamalsample,bothdimensionsexplained 97.07% (Fig. 2a) and in the Puna–Quebrada sample, 98.02%

(Fig.2b).Forbothpopulations,thefirstdimensionseparatedthe distribution of minutiae frequencies in the periphery of the dactylogram (outsidethe circle) fromthose in thecentral area (insidethecircle),anditwasthislatterareawhichpresentedthe greatest diversity of minutiae types. The second dimension separated females from males, with the former presenting a greaterdiversityofminutiaetypes.

We explored the relationship between the distribution of minutiaetypesandthefingers(F1,...,F10),consideringtotalfinger surfaceareaandinsideandoutsidethecircle,forbothpopulations, andfoundsignificantdependenceinallareas.Thecorrespondence analysisdemonstratingthisdependenceinsidethecircleinboth populationsisshowninFig.3.IntheRamalsample(Fig.3a),the twodimensionsexplained91.12%ofinertia.Thefirstdimension separatedtherighthandfingersfromthoseofthelefthand,and thesecond dimensionseparated thethumb fingers (F1and F6) fromtherestofthefingers.Endings(E)werelocatedverycloseto thecoordinatecenterandwere,byfar,themostfrequenttypeof Table2

FrequenciesregisteredforminutiaefromPuna–Quebradasample,totals,malesandfemales,insideandoutsidethecircleandtotalarea(ofthetenfingers),n=totalnumberof

minutiaefoundinarea,a_,b_,c_p<0.05.

Total(n=147,982) Males(n=72,073) Females(n=75,909)

Totalarea Insidecircle Outsidecircle Totalarea Insidecircle Outsidecircle Totalarea Insidecircle Outsidecircle

E 51.690 45.458 55.756 53.469 46.676a

57.626b

50.001 44.387a

53.890b

B 19.906 22.806 18.014 19.161 22.271 17.259c

20.613 23.278 18.766c

C 18.278 21.033 16.480 16.977 20.169a

15.024b

19.513 21.794a

17.932b

F-BG 1.415 1.354 1.455 1.469 1.276 1.588 1.363 1.423 1.322

F-SM 2.284 2.198 2.340 2.356 2.230 2.433 2.216 2.169 2.248

BR 1.122 1.145 1.108 1.224 1.385 1.125 1.026 0.933 1.091

EN-BG 0.758 1.030 0.580 0.795 1.118 0.597 0.722 0.953 0.562

EN-SM 0.988 1.427 0.701 0.814 1.203 0.577 1.153 1.625 0.825

P-BW 1.039 1.195 0.937 1.371 1.521 1.279 0.723 0.908 0.595

P-IN 0.099 0.087 0.107 0.121 0.113 0.125 0.079 0.064 0.089

O 0.793 0.649 0.888 0.795 0.654 0.881 0.792 0.644 0.894

CR 0.809 0.556 0.974 0.688 0.450 0.834 0.923 0.650 1.113

BD 0.576 0.779 0.444 0.513 0.691 0.405 0.636 0.856 0.484

OB 0.080 0.096 0.069 0.082 0.099 0.072 0.078 0.093 0.067

D 0.076 0.050 0.093 0.097 0.058 0.121 0.055 0.042 0.065

TF-B 0.020 0.034 0.010 0.014 0.022 0.009 0.025 0.045 0.011

TF-C 0.014 0.027 0.006 0.010 0.018 0.004 0.018 0.035 0.007

M-B 0.032 0.034 0.030 0.029 0.022 0.034 0.034 0.045 0.027

M-C 0.020 0.036 0.009 0.011 0.018 0.007 0.028 0.051 0.011

R 0.002 0.005 0.000 0.003 0.007 0.000 0.001 0.003 0.000

Author's personal copy

minutiaeinallfingers.Convergences(C)wereassociatedwiththe middle(F3),ring(F4)andlittle(F5)fingersoftherighthand.In contrast,bifurcations(B)weremoreassociatedwiththelefthand, andinparticular,withtheindex(F7),middle(F8),ring(F9)and little(F10)fingers.Theremainingminutiaewerelargelyassociated withthethumbs(F1andF6) andindexfingers(F2 andF7).All convergentminutiae(C,TF-C,M-C),ornegativedirection(sensu Champod,[44]),weremorefrequentontherighthand;incontrast,

itwasthebifurcateminutiae(B,TF-B,M-B),orpositivedirection (sensuChampod,[44]),thatweremostfrequentonthelefthand.In the Puna–Quebrada sample (Fig. 3b), the two dimensions significantlyexplained89.42%ofinertia,andthefirstdimension separatedtherighthandfingersfromthoseofthelefthand,whilst theseconddimensionseparatedthethumbsofbothhands(F1and F6)andthelefthandindexfinger(F7)fromtherestofthefingers. In the Ramal sample, the association between fingers and

Fig.4.Frequenciesforthetypeofpatternsbyfinger(F1,...,F10):(a)Ramalsample;(b)Puna–Quebradasample.Analysisofcorrespondencebetweengeneralpatternsandthe fingers:(c)Ramalsample;and(d)Puna–Quebradasample.

Fig.3.Analysisofcorrespondencebetweenthetypesofminutiaeandthetenfingers(F1,...,F10)inthecentralareaofthefingerprint(insidecircle):(a)Ramalsample;(b) Puna–Quebradasample(theminutiaeR,farawayfromallothers,havebeencutfromthegraphandplacedontheperiphery–lowerleftcorner–forabettervisualizationof therelationshipsamongoftheotherminutiae).

E.Gutie´rrez-Redomeroetal./ForensicScienceInternational222(2012)266–276

bifurcations and convergences presented the same pattern. In addition,itcanbeseenthatthethumbsseparatedfromtheother fingers.Thispatternofassociationalsoappearedoutsidethecircle, in both populations. Similarly, when the total sample (both populations)wasanalyzedbysex,wefoundthatbothmalesand femalespresentedthesametypeofassociationanddependence betweenthedistributionofminutiaetypesandfingers.

Thefrequencyfoundformainpatterntypesbyfinger,forboth Argentinian samples,is shown in Fig. 4.These didnot present significant differences between samples or between sexes. In Fig.4a–b,similarvaluesbetweenhomologuefingerscanbeseenin bothpopulations:whorlsweremorefrequentonthumbsandring fingers(F1,F4,F6andF9),whilstulnarloopsweremorefrequent onthemiddleand littlefingers (F3,F5,F8and F10).Theindex fingersofbothhands(F2andF7)presentedahigherfrequencyof archesandradialloops,withsimilarfrequenciesforwhorlsand ulnarloops.Correspondenceanalysisbetweenmainpatterntype

and fingers revealed a significant association between them (Fig.4c–d):inbothpopulations,thethumbs(F1andF6)andring fingers(F4andF9)wereassociatedwithwhorls,themiddle(F3 andF8)andlittle(F5andF10)fingerswithulnarloops,andthe indexfingers(F2andF7)witharchesandradialloops.IntheRamal sample, thetwo dimensionsexplained97.95%of thevariability found, whilst in the Puna–Quebrada sample, they explained 98.77%.Inbothsamples,thefirstdimensionseparatedthemiddle (F3andF8)andlittle(F5andF10)fingers,whichpresentedmore ulnarloops,fromtherestofthefingers,whichhadmorewhorls. Thedependencebetween theminutiaeandthemainpattern types,byfingers(F1,...,F10),wasstatisticallysignificantinboth populations(Fig.5).Forthesampleinsidethecircle,Fig.5shows theCAbetweenthetypesofminutiaeandthetwomostfrequent typesofpatterns,ulnarloops(UL)andwhorls(W)foreachfinger. Thereturnminutia(R)isanoutlier,i.e.farawayfromallothersand fromthepointoforigin,andthereforethisminutiaindicatesaclear Fig.5.Analysisofcorrespondencebetweenthetypesofminutiaeandthetwomostfrequenttypesofpatterns:ulnarloop(UL)andwhorl(W),foreachfinger(1,...,10):(a) Ramalsample;(b)Puna–Quebradasample.

Author's personal copy

deviationfromwhatwewouldexpectundercomplete indepen-dence.Ithasbeencutfromthegraphandplacedontheperiphery, toprovideabettervisualizationoftherelationshipsbetweenthe other minutiaein the Puna–Quebrada sample(Fig. 5b).For the Ramal sample, correspondence analysis explained 79.23% of inertia (Fig. 5a), and 81.73% for the Puna–Quebrada sample (Fig.5b).Thefirstdimensionseparatedtherighthandfingersfrom thoseofthelefthand,inbothpopulations.Fingerswithulnarloops asthemainpatterntypeweregreaterdeterminantsofdependence betweenminutiaetypesandfingers,andtheirdistributioninthe analysiswasthusfoundtobefurtherfromthecenterofgravity. Meanwhile,theseconddimensionseparatedthethumbsofboth hands,whetherwithwhorlsorulnarloops,fromtherestofthe fingers,whichweremoreassociatedwithconvergences(C)onthe righthand(F2,....,F5)andbifurcations(B)onthelefthand(F7,...., F10). In the analysis, endings (E) were located close to the coordinate axis, or center of gravity, contributing less to dependencesincetheywerethemostfrequenttypeminutiaeof inbothsamples(Fig.5).

AcomparisonisshowninFig.6ofthefrequencyresultsforthe Argentinian populations and the Spanish population sample published previously[38], consideringendings (E), bifurcations (B)andconvergences(C),bothinsideandoutsidethecircle.The differencesobservedinthesethreetypesofminutiae(endings-E, bifurcations-Bandconvergences-C)betweentheSpanishsample and the Ramal and Puna–Quebrada samples were statistically significantbothinsideandoutsidethecircleandforbothsexes: endings (E) were more frequent in the Spanishsample, whilst bifurcations(B)andconvergences(C)weremorefrequentinthe Argentiniansamples.Puna–Quebradamalespresented significant-lymoreendings(E)andfewerbifurcations(B)thanRamalmales, bothinsideandoutsidethecircle.Inaddition,thePuna–Quebrada malespresentedfewerconvergences(C)outsidethecirclethanthe Ramalmales.Incontrast,both insideandoutside thecirclethe Puna–Quebradafemalespresentedsignificantlylowerfrequencies ofendings(E)andmorebifurcations(B)thantheRamalfemales.In addition,thePuna–Quebradafemalespresentedsignificantlymore convergences(C)insidethecirclethantheRamalfemales(Fig.6). The relationship between ending (E), bifurcation (B) and convergence (C) frequencies and the three samples (Two ArgentinianpopulationsamplesfromRamalandPuna–Quebrada and a Spanishpopulation sample) was statistically dependent.

Consequently,weconductedacorrespondenceanalysis,shownin Fig.7.InFig.7a,thetwodimensionsexplained99.99%ofinertia, withthefirstdimensionseparatingtheSpanishpopulation,who presentedahigherfrequencyofendings(E),fromtheArgentinian populations (Ramaland Puna–Quebrada),whopresented lower frequencies of bifurcations (B) in the Ramal sample, and of convergences(C)inthePuna–Quebradasample.Fig.7bshowsthe results of the correspondence analysis considering sex. In this analysis,thetwodimensionsexplained99.26%ofinertia.Thefirst dimensionseparatedbothsexesoftheSpanishpopulationfrom theArgentinianpopulation,whilsttheseconddimension separat-edallfemalesandtheRamalmalesfromthePuna–Quebradaand Spanishmales.

Astheinfluenceofpatterntypeonthenumberofminutiaeis shownbyanincreasefromarches(nodelta)toloops(onedelta)to whorls(two or more deltas and complexity of the center)the impact of general pattern on interpopulation variation was investigated. Fig. 8 shows that pattern frequencies are quite different between the Argentinian and Spanish populations.

Moreover, the dependence on the main pattern types by

populationwasstatisticallysignificantinbothpopulations,with chi-square=95.06andp<0.0001.Therearelowerfrequenciesof ulnarloopsandwhorls,buthigherfrequenciesofarchesandradial loops in the Spanish populations than in the Argentinian populations.

Fig.7.(a)Analysisofcorrespondencebetweenthetypesofminutiae(endings–E,bifurcations–Bandconvergences–C),andArgentinianpopulations(RamalandPuna– Quebrada)andtheSpanishpopulationsamples.(b)Analysisofcorrespondencebetweenthetypesofminutiae(endings–E,bifurcations–Bandconvergences–C),genders (males:maandfemales:fe)andareas(insidecircle:Iandoutsidecircle:O)forArgentinianpopulations(RamalandPuna–Quebrada)andtheSpanishpopulationsamples.

Fig.8.Frequenciesforthepatterntypebypopulation:SpanishandArgentinian (RamalandPuna–Quebradatogether).

E.Gutie´rrez-Redomeroetal./ForensicScienceInternational222(2012)266–276

When conditioning using general pattern, the relationship between ending (E), bifurcation (B), and convergence (C) frequencies and thethree samples(twoArgentinianpopulation

samples from Ramal and Puna–Quebrada and one Spanish

population sample)wasstatisticallydependent,both insideand outside thecircle,as shownin Fig.9. Theresultsrevealhigher

frequenciesofendings(E)andlowerfrequenciesofbifurcations(B) and convergences (C) for all pattern types in the Spanish population than in theArgentinianpopulations. The significant dependency among minutiae(E,B, and C), type ofpattern, and population is shown in Fig. 10. The graph obtained with correspondence analysis highlights the association of endings withtheSpanishpopulation in allpattern types(arches,radial loops,ulnarloops,andwhorls)andtheassociationofbifurcations andconvergenceswiththeArgentinianpopulation.

4. Discussion

Although numerous studies have been carried out on the fingerprints of human populations, some of their inherent characteristicshave received moreattentionthan others.These includeaspectssuchasfrequencyofthemainpatterntypes (arch-A,radialloop-RL,ulnarloop-ULandwhorl-W)andthepartial(RC) ortotal(RCT)ridgecount,aswellastheirvariabilityandheredity in different human populations (see bibliography checklist in [45,46]). However, other features, such as the minutiae, have receivedcomparativelylessattention,despitebeingof consider-ableinterestduetotheirdirectrelevanceinpersonalidentification and despite early recommendations from various specialists [13,47–52].

Thus, it is difficult to compare the results obtained in the presentstudywiththosewhichhavebeenpublishedpreviously due to the different criteria employed, not only as regards classification ofthe minutiae,but alsoin termsof themethods employedfortheirassessment[47–57].Allotherstudies,withthe exception of those conducted by Gutie´rrez-Redomero et al. Fig.9.Frequencyofendings(E),bifurcations(B),andconvergences(C)ofthetenfingersfortheSpanish(S)[38]andArgentinian[Ramal(R)andPuna–Quebrada(PQ)] populationsampleswhenconditioningbygeneralpattern[arch(A),radialloop(RL),ulnarloop(UL),andwhorl(W)],considering(a)insideand(b)outsidethecircle.

Author's personal copy

[17–38],havebeenbasedonfingerprintsamplesfrommales,and vary considerably as regards sample size (from 39 to 1000 fingerprintimpressions),numberof fingersselectedforanalysis (only the thumb, only the index and middle fingers, or other combinations),thefingerareasassessed(distaltips,nucleararea, deltaarea,etc.)andthetypeofmainpatterntypeselected(usually the ulnar loop-UL and Whorl-W). The recent classifications by Ashbaugh[3]and Champod[44],withninemain types,arethe mostsimilartotheclassificationswhichwereusedinthepresent study.Standardizationofminutiaeclassificationcriteriaisahighly desirable objective in order to facilitate comparison between differenthumanpopulationsusingagreaternumberof morpho-logical minutiae characteristics. The advantage of using more minutiaetypesstemsfromthefactthatthelessfrequenttypesare accordinglythemostexceptional,andtherefore,themostuseful foridentificationpurposes[2,13,18,30,57].Forallthesereasons,it wasonly possibletoconducta very generalcomparison ofthe minutiaefrequenciesobtainedinourstudywiththemajorityof those which have already been published. Nevertheless, this general comparison indicated that the most frequent types of minutiaeareendings,followedbyconvergencesandbifurcations, althoughin themajorityofthesamplesfromotherstudies,the lattertwotypesofminutiaewerenotanalyzedseparately.Asinour study, the rest of the minutiae have been found to present considerably lower frequencies. In contrast, it was possible to compare the data we have presented here with the findings reported by Gutie´rrez-Redomero et al., [17,38] for a Spanish population sample,which wascollectedand analyzedusingthe samemethodology.

Theresultsobtainedinthisstudyshow,forthefirsttime,the topological, fingerand sex differences presentingin fingerprint impressionstakenfromtwoArgentinianpopulationsamples.Our resultsforbothsamplesreflecttheheterogeneousdistributionof minutiaeonthefingerarea,withdifferencesinfrequencybetween the different areas assessed. Coinciding with findings for the Spanish population [38], endings were located with more frequencyoutside thecircle(peripheralarea ofthefingerprint), whilstbifurcationsandconvergencesweremorefrequentinside thecircle(centralareaofthefingerprint).Otherauthors,suchas Kingston[48],Lin[53]andSclove[52],havereportedthatminutiae densityvariesaccordingtolocationonthefingerprintimpression, and more recently, Champodand Margot [55]have confirmed theseresults,findingahigherdensityofminutiaeinthenuclear anddelta(triradii)areasthanintheperipheryoftheimpression.In relation tosex, and in contrast tothe Spanishpopulation [38] wherenosexdifferenceswerefoundinminutiaetypefrequencies, bothArgentinianpopulationsdidpresentdifferencesforendings and bifurcations; the females presented a higher frequency of endings,andthemales,ofbifurcations.

Given the mirror image the hands present, the bifurcate minutiaeassessed(B,TFBandMB)wereassociatedwiththeleft hand, whilst the convergent minutiae (C, TFC and MC) were associated withtherighthand,coincidingwithfindingsforthe Spanishpopulation [38].Champodand Margot[55]highlighted theassociationofbifurcationsinapositivedirection(referredtoas bifurcationsinthisstudy)withulnarloopsonthelefthand,and bifurcationsinanegativedirection(referredtoasconvergencesin thisstudy)withulnarloopsontherighthand.AswiththeSpanish population,inthepresentstudywefoundthatthisassociationalso holdstrueforwhorls.

Asregardsmainpatterntype,theSouthAmericanIndianshave greatervariationinfrequencythananyotherAmericanpopulation (Eskimos,NorthAmericanIndiansandCentralAmericanIndians) [58,59]. The finger pattern type frequencies found in the two Argentiniansamplesfellwithinthedistributionrangedescribed for South American populations, and as withall other Andean

populations analyzed, the Puna–Quebrada sample presented a highfrequencyofradialloops[58,60].TheArgentiniansamples werecharacterizedby presentingmorewhorlsand fewerulnar loopsthanotherSpanishpopulation samples.Themain pattern frequencydistributionforeachfingershowsthattheuniversally observedpatternofanassociationbetweenwhorlsandthumbs and ring fingers, ulnar loops and middle and little fingers and archesandradialloopsandindexfingers[10:pp.79]isalsoevident inthesesamples.

Although the topological distribution pattern presented by endings (E), bifurcations (B) and convergences (C) in the ArgentinianandSpanishpopulationscoincided,wefound signifi-cantdifferences,forthefirsttime,inthefrequencyofminutiaein alltheareascompared(totalareaandoutside/insidethecircle). Thus, the Spanish population presented significantly higher frequenciesofendings(E),andlowerfrequenciesofbifurcations (B)and convergences(C)thaneitheroftheArgentinian popula-tions.Giventhedifferencesobservedbetweenthetwopopulations intermsofthefrequenciesofpatterntypesandtheimpactthis mighthaveonthesignificantdifferencesfoundforthethreetypes ofminutiae(E,BandC),acomparisonofconditioningbygeneral pattern was conducted, which confirmed previous results. Therefore, the frequencies of minutiae change in relation to population,butitshouldchangeindependentlyofthepatterntype. Thishighlightstheexistenceofsignificantdifferencesasregards theminutiaefrequenciespresentedbythesepopulations.Further research is nevertheless required in order to determine the magnitudeofthesedifferencesinotherhumanpopulations.

In an identification process based on the comparison of morphologicalcharacteristicssuchastheminutiae,itisimportant tobearinmindthediscriminatorypowerofthesecharacteristics, giventhedifferentfrequencieswithwhichtheyappearindifferent populations[15,18].Forthisreason,inafingerprintidentification, whether or not based on a numerical standard, the evidential weightofminutiaesuchasendings(E), withfrequencies which range from 45% to 66% depending onthe fingerarea, sex and populationanalyzed,cannotbethesameasthatofbifurcationsor convergences,withfrequencieswhichvarybetween12%and25%, ortherestoftheminutiae,suchaspoints(P-BWoP-IN),crossbars (CR),bridges(BD)oroppositedbifurcations(OB),withfrequencies whichrangebetween3%and0.1%.

Theapplicationofmathematical modelsfor theprobabilistic calculationofidentitybasedonfingerprintimpressionswouldbe usefulintheidentificationprocess,andtohavequantitativedata relatedtodifferenttypesofminutiaeandtheirdistributionscould beofgreatinterest.Unfortunately,currentknowledgeaboutthese papillaecharacteristicsisstillinsufficientforthispurpose,asno systematicstudieshavebeenconductedontheirdistributionand variability, and thus important aspects of their biology and geneticsareunknown.Therefore,asscientificandjudicialsources haverecognizedforalongtime[18,35,37,39,61,62],itisnecessary to conduct multidisciplinary studies in order to provide new information andimprove theapplicationof thistechnique, and thusconsolidateitsscientificbasis.

5. Conclusions

We have confirmed the non-equiprobability of different minutiae types in two population samples, and have found significanttopological,fingerandsexdifferences.

We have demonstrated, for the first time, the existence of significantdifferences in minutiaefrequencies between popula-tions,independentlyfrommainthepatterntype.Thesedifferences were present both between the two Argentinian populations studied(RamalandPuna–Quebrada),andbetweeneachofthese andaSpanishsample.

E.Gutie´rrez-Redomeroetal./ForensicScienceInternational222(2012)266–276

Furtherresearchisrequiredinordertoincreaseourknowledge aboutthevariabilityofthesecharacteristicsinhumanpopulations, inordertofacilitatecomparisonandapplicationinprobabilistic calculationofidentity.Tothisend,werecommendthe standardi-zation of nomenclature criteria and the adoption of clear and precisedefinitionstominimizesubjectivitywhenapplied.

Acknowledgements

The authors are grateful to research assistants E. L. Alfaro Go´mez,B.C.Farfa´n,V.Pintado,E.Romero,C.Rodrı´guezPacho,L.E. Herna´ndez-Hurtado, J.L. Rodrı´guez-Villalba, J. L. Nieva, and J. Comendeiro fortheir help inthiswork, and totheanonymous reviewersfortheirvaluablesuggestionswhichhavecontributedto enhancementofthequalityofthepaper.Thisworkwassupported inpartbytheAgenciaEspan˜ oladeCooperacio´nInternacionalpara elDesarrollo(AECID)underprojectA/01575/07,andinpartbythe University Institute of Investigation on Police Sciences under projectIUICP/PI2007/008.

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