Zwietcovich Et Al - 3D Assessment

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1 I t d ti f t I ti l i t h d f

A 3D Assessment Tool for Precise Recording ofCeramic Fragments Using Image Processing

and Computational Geometry Tools

Fernando Zvietcovich, Benjamn Castaeda, Luis Jaime Castillo and Julio Saldaa

Ponticia Universidad Catlica, Peru

Abstract:

Recording ceramic fragments is essential for archaeological interpretation and conservation. Whendone manually, this task is very time consuming and greatly depends on the experience and skill of the

archaeologist in charge. In this paper, we propose the implementation of a 3D acquisition and processing

method to improve the accuracy and precision of the recording procedure. During the rst step of the

proposed process, 3D mesh models of ceramic fragments are obtained using a laser scanner. Subsequently,

discrete 3D dynamic contour is utilised to extract points from the fragments rim. Orientation and diameter

of the complete vessel are then estimated using a non-linear least square approach. Experiments, using

manual techniques, report precision errors (variability) less than 11.97% in the diameter and 3.75% in

inclination, whereas the 3D method reports errors of 2.07% and 0.42% for the same measures. Moreover,

accuracy experiments report accuracy errors of less than 4.78% in the diameter, and 4.30% in inclination.

These results suggest that the 3D method is accurate and more precise and 13.3% faster than the traditional

methodology.

Keywords:

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1 Introduction of symmetry In particular ceramic potsherds from

A 3D Assessment Tool for Precise Recording of Ceramic Fragments Using Image ProcessingZwietcovich et al

CAA2013 Proceedings of the 41st Conference in Computer Applications and Quantitative Methods in Archaeology,Perth, Australia, 25-28 March 2013

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New methodologies for recording ceramicfragments capable of overcoming these dicultiesare necessary. Several attempts were proposed inthe past. During the last ten years, various researchgroups made important advances in developingcomputerised applications using 3D models offragments (Kampel and Melero 2003; Karasik and

Smilansky 2008; Yao and Shao 2003). They focusedon increasing the accuracy of the recording; inparticular, the extraction of the axis of symmetrywhich is not a trivial task an d still remains an issuein 3D potsherd recording (Karasik and Smilansky2008). On one hand, in the work by Karasik andSmilansky (2008), to estimate the axis of symmetry,it is assumed that the operator who scanned thefragment already positioned it in an approximatelycorrect way (axis of symmetry parallel to the zaxis). Similarly, in the work done by Yao and Shao(2003) the detection of corner points around therim of the fragment for the plane tting procedureand estimation of the orientation is completelydependent of the initial orientation of the fragment.In the work by Kampel and Melero (2003), anormal distribution is used for estimating the axisof symmetry. However, this leads to a non accurateestimation since normal vectors are sensible tonoise. In addition, a good compromise betweenaccuracy and computational cost has not beenproperly achieved.

We propose here a novel methodology forrecording ceramic fragments utilising a laserscanner to digitise the 3D models of fragments andapplying 3D image processing and computationalgeometry tools for the prole estimation. Weutilise a 3D discrete active contour for detectingthe rim of the fragment which makes the procedureindependent to the initial position of the model inthe 3D space. Then, we utilise the detected rim fortting the best plane and estimating the orientationof the fragment. Finally, we estimate the best circlethat ts in the border of the rim for detecting the

axis of symmetry, and therefore, the best prole ofthe fragment. This research measures the accuracyof the proposed techniques, includes a comparativestudy of the time utilised by the traditional methodand the proposed 3D method, as well as the inter-and intra- variability (precision error) assessment ofthe same techniques.

This research only works with indicativeceramic fragments belonging to axial symmetricvessels aliated to the Moche tradition from theNorth Coast of Peru. They were excavated in SanJose de Moro, Chepen, La Libertad, Peru by the SanJos de Moro Archaeological Program between Julyand August of 2012. The proles were calculated

using rst the traditional method and, then, the 3Dproposed technique. Then, both results are comparedin terms of variability and time consumption.

This paper is organised as follows: in section2 we describe the 3D scanning process using alaser scanner. In section 3, we explain the entiremethodology and algorithms constructed for ndingthe orientation of the fragment, its diameter and the2D prole around its axis of symmetry. In section 4,we describe the design of the experiments over thefragments using the traditional method and the 3Dmethod. In section 5, the results of the experimentspreviously designed are explained and compared.The conclusions of the entire work are explained insection 5. At this point, some potential applicationsare suggested.

2. 3D Acquisition of Potsherds

This study focuses on four fragments of largeceramic containers, locally known as paicas,used for the production and storage of a fermentedbeverage based on corn called chicha. Thesefragments were found during the 20 years of researchin the site of San Jose de Moro, in the JequetepequeValley of northern Peru and they are illustrated inFig. 1 top. The 3D meshes of the ceramic potsherdswere obtained from the commercial 3D laser scannerNext Engine HD (NextEngine Inc., CA, USA).This device projects a laser pattern over the targetsurface and estimates the 3D coordinate positions ofeach point around the pattern via 3D triangulationand image processing tools (Bernardini andRushmeier 2002). The scanner sweeps the laser

pattern around the entire fragment in a single viewpoint. Then, a rotary wheel connected to the scannerrotates the fragment 360 in order to acquire 3Dmodels representing its various views. All views aredisplayed, registered and merged together in orderto create a complete 3D mesh representation ofthe fragment utilising the software ScanStudio HD(NextEngine Inc., CA, USA).

The maximum accuracy of models obtainedby NextEngine laser scanner is 0.13mm while themaximum resolution is 50k points per inch squaredand as reported in the technical specications sectionof its user manual. In the industry, the accuracy ofa system is dened as the degree of closeness ofmeasurements of a quantity to that quantitys actualknown value. The precision of a system measuresthe degree in which repeated measurements of asame quantity under the same conditions describesthe same result. This is also called repeatabilityor reproducibility (the opposite of variability orprecision error) and is strongly correlated to thestandard deviation of the measurements. Both,accuracy and precision are dened in the workby Guidi et al. (2007) in the evaluation of theNextEngine Laser Scanner. Herein, they report aprecision of 0.048 mm. In order to verify the givenvalue of accuracy, we scanned the width of threerectangular metal patterns of known dimensions(1.1mm, 1.2mm and 1.7mm). We found and averageaccuracy error of 0.03mm, less than 0.13 mmreported by NextEngine specications.

The 3D meshes of the fragments have an

average amount of 42k points and took around 9minutes per model. During the scanning procedure,the fragments were located 16.51cm in front of thescanner. The spatial conguration of the scannerand fragments are illustrated in Fig. 2. The data wasexported using object le format which containsinformation of the point coordinates representingthe model, its 3D triangulation, and the texturecolour attached to the mesh. Finally, the four 3D

meshes corresponding to the ceramic fragments instudy are loaded into Meshlab (Visual ComputingLab, ISTI CNR, Italy) for a preprocessing step.Here, a hole-lling algorithm is utilised to ll thegaps around the models (Zhao, Gao and Lin 2007)whereas a Taubin | ltering procedure (=0.5,=-0.53, and 10 iterations)is applied to the modelsin order to remove noise and preserve salient shapefeatures (Taubin 1995). The resulting meshes areillustrated in Fig. 1 bottom.

To assess the inuence of the preprocessingstep in the accuracy of the models we aligned bothmodels before and after applying the noise and holelters. Then, we computed the distance betweenmodels. We report 0.0011mm as the mean distancewith a sigm a of 0.0 37mm. Since the mean distanceis considerably less than the accuracy of models,we conclude that the preprocessing step doesnot alter the reliability of any measurement overpreprocessed models.

3. Algorithm

The entire methodology consists in four steps:rim detection procedure, orientation estimation,estimation of axis of symmetry and the diameterof the rim, and 2D prole calculation. For theexplanation of the sequence, a single ceramicfragment was utilised. Fig. 3 illustrates the owchart of the entire procedure.

Figure 1. 3D mesh models of four ceramic fragments.

Top: pictures of the frgaments during the scanning

process. Bottom: 3D meshes previously processed in

Meslab.Figure 2. The scanning system: a NextEngine laser

escanner connected to a computer and a rotatable

support holding a ceramic fragment.


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3.1 Rim detection procedure

In this step, we attempt to nd pointsbelonging to the rim of the vessel. Since we are

working with indicative fragments, part of the vesselrim is available. A mean curvature algorithms isapplied on the 3D mesh of fragments in order tohighlight sectors of high slope (Dong and Wang2005). Typically, the corner points of the rim locatedin the top part of the vessel depicts high geometricalchanges. Hence, these points will have high valuesof mean curvature, whereas, at areas will havelow values as illustrated in Fig. 4a. Subsequently,a hysteresis thresholding algorithm is utilised inorder to select important edges discriminating sideeects produced by noise. The description of thealgorithm is explained in Hubeli and Gross (2001)and the result is illustrated in Fig. 4b.

A 3D discrete active contour was designedand implemented for the mesh segmentation of the

fragment. The algorithm allows the user to insertthe rst location of the contour over the 3D mesh.Then, the contour will be deformed until it reachesa stop condition dictated by the presence of edges.For more details about the description of the activecontour, we refer to Lobregt and Viergever (1995).The resultant deformed contours are depicted inFig. 4c. Finally, the user manually selects the borderrepresenting the vessel rim in both sides, internal

and external. The result of the user selection isillustrated in Fig. 4d.

3.2 Orientation estimation

The orientation of a vessel is denedby the unitary vector; therefore all pointsbelonging to the vessel rim are contained in aplane normal to this vector. In order to estimatethat plane, a tting procedure based in theleast squares optimisation tool is applied overthe points representing the vessel rim. We callthe set of those Cartesian points representingthe internal and external border P={P

n} and

Q={Qn} respectively, where {[]

n}=[x

n,y

n,z

n]T

and n=1,,N, being N the maximum numberof points detected in the rim. The analyticaldescription of a plane can be written as follows:

z = Ax + By + C (1)

Subsequently, we dene a cost function(Equation 2) consisting on the sum of the

squared errors betweenznandAxn+Byn+C. Theobjective consists in estimating the parametersA, B and C describing the best tted plane inboth borders internal and external.

E(A,B,C) = N(i=1)

A(xi+ By

i+ C) - z

i2 (2)

The unknown parameters AP, B

P, C

P and A

Q,

BQ, C

Qcorresponding to the sets P and Q respectively

are calculated using a least squares procedure. Then,the normal vectors to these planes are given by

UP

= [AP/C

P, B

P/C

P, - 1/C

P]T (3)

UQ = [AQ/CQ, BQ/CQ, -1/CQ]T (4)

and they are illustrated in Fig. 5a. Finally, thevector describing the orientation of the entire ves selis given by the unitary average among vectors U

P

and UQ(Fig. 5b):

(5)

If the angle between UPand U

Qare more than

a threshold of 5, a warning message indicatesthat something is incorrect in the rim detectionprocedure. Then, it is necessary to return to theprevious step.

A rigid transformation is applied over themesh model of the fragment; therefore the planes

containing Pand Qare parallel to the planez=0. Wedene the transformation matrix R as:

R = Icos + sin[u]x

+ (1 - cos)uu (6)

where [vx v

y v

z]T = U[0 0 1]T,

and = arccos(U.[0 0 1]T). Then, the setsof points belonging to the internal and externalrim are also transformed: P

T={P

Tn}={RP

n} and

QT={Q

Tn}={RQ

n}. The new Cartesian location of the

fragment in the 3D space is depicted in Fig. 5c.

3.3 Estimation of the axis of symmetry anddiameter of the rim

Since we are working with axial symmetricvessels, the projection of the rim over the

plane z=0 provides a perfect circumference.Then, the centre of the circumference and thedirection of the orientation vector dene theaxis of symmetry, whereas, the radio allowsestimating the approximate rims diameter ofthe vessel (Fig. 6a).

We project PTover the planez=0in order

to obtain a 2D representation of the points

Figure 4. Rim detection procedure. (a) Colorized mean

curvature of the fragment. (b) Edge discrimination

procedure via hysteresis thresholding algorithm. (c)

3D discrete active contour utilized for the borders

segmentation. (d) Manual selection of the internal and

external border of the rim.

Figure 6.Estimation of the axis of symmetry and diameter

of the rim. (a) Denition of features in a idealized complete

vessel. (b)-top: Fitting procedure of a circunference using

the points of the rim. (b)-bottom: Location of the fragment

model around the axis os symmetry.

Figure 5. Orientation estimation and rigid transformation.

(a)-top: Calculation of the normal vectors UP and UQ to

the planes belonging to the borders P and Q respectively.

(a)-bottom: The average vector U (between UP and UQ).

(b) Rigid transformation of the 3D mesh of the fragment.Figure 3. Flow chart of algorith proposed for the 2D

prole extraction of ceramic fragments.


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PT={P

Tn}=[x

n, y

n]T, n=1,,N. Hence, a non-

linear least square tting procedure is utilisedover P

T in order to nd the equation of the

circumference. The analytical description of a2D circumference can be written as follows:

L(a,b,r) = ((x - a)2 + (y - b)2) - r = 0 (7)

It can be interpreted from equation 7 thatfor all coordinated points (x,y) which satisfyL(a,b,r)=0, then, those points depict part of acircumference dened by the centre (a,b)andradio r. We dene a cost functional F as thesquare dierence betweenL(a,b,r) and cero:

F(a,b,r) = N(i=1)

L(a,b,r)2 (8)

The unknown parameters a, b and r arefound by minimisingFusing Simplex iterativeprocedure until a desired convergence isreached. Initial values of the parameters arerequired by the algorithm. Subsequently, theaxis of symmetry is dened with the followingline equation:

(t) = [a,b,0]T+ t[0,0,1]T (9)

where t, and the diameter is dened as:

D = 2r (10)

Fig. 6b illustrates the estimation of the 2Dcircumference around the axis of symmetry whereasFig. 6.c depicts the location of the 3D mesh of thefragment around this same circumference.

3.4 2D prole calculation

In this step we attempt to extract the 2D proleof the fragment that contains more information ofits shape utilising a cutting procedure. A verticalcut consists in the intersection of a plane and the

triangulated mesh model of the fragment. Theresultant points belong to the same plane andrepresent the prole of the fragment. The cuttingplane must always contain the axis of symmetryand its normal vector must be always parallel tothe planez=0. Then, there exist innite planes thatcould cut the 3D mesh. A procedure consisting inthe extraction of a nite number of vertical cuts isapplied over the mesh model of the fragment. Then,

an automatic selection procedure discriminatesamong cuts and selects the one with the largestperimeter (see Fig. 7a).

A 2D diagram depicting the prole around itsaxis of symmetry is created. First, the cutting planewhich contains the points be longing to the prole isrotated parallel to the planex=0. Finally, the axis ofsymmetry is located on the left, whereas, the proleis located in the right of the gridded map (see Fig.

7b). The resultant 2D diagram allows the user toidentify the rims diameter, thickness, inclinationwith respect to the horizontal lines and the shape ofthe fragment in an automatic fashion.

4. Experiments

In this step, we design four experiments inorder to assess the precision, accuracy, and thedepiction/processing time in both methods: thetraditional and the 3D method.

4.1 Precision test (inter/intra variability) of thetraditional method

The precision error is dened as the standarddeviation of a series of measurements (see Guidi et

al. 2007). Then, the percentage precision error, alsoknown as variability is dened as:

(11)

where N is maximum number of measurements, x

i

corresponds to the quantity of a single measurement,and is the average of all the measurements.

Three experienced archaeologists were trainedto record four ceramic fragments using the followingprocedure:

To locate a planar plate over the rim of the ceramicfragment; therefore the contact between the rimand plate is maximal. Then both the fragment an d

the plate are positioned perpendicular to a papersheet, thus the plate is parallel to the horizontal.Then, the symmetry axis is perpendicular to thatplate. This procedure is made for estimating theorientation of the fragment.

To record the shape and thickness of thefragments prole using a prole gauge. Bothinternal and external proles are drawn by handover the paper sheet taking into account theinclination registered in the previous step.

To estimate the diameter of the vessel rim bymanually positioning it over a rim chart. Thischart contains concentric circumferences ofseveral radios. The circumference that best tswith the rim o f the fragment is selected. Finally,the axis of rotation is depicted as a vertical line

separated from the rim by the radio selected inthe previous description.

Inter-person variability assessment: threedierent archaeologists depicted the fragmentproles of four ceramic fragments using thetraditional method. Intra-person variabilityassessment: each archaeologist depicted the samefragment prole three times. In summary, eachfragment has nine manual depictions obtained fromthe traditional method.

4.2 Precision test (inter/intra variability) of theproposed 3D method:

Three experienced archaeologists were trainedto record ceramic fragments using the following

procedure:

To operate the 3D laser scanner to obtain 3Dmeshes of ceramic fragments. Then, the meshesare opened in Meshlab for a pre-processing step.

To manage gradually the entire methodologyproposed in this research until the 2D depictionsof the fragment proles are obtained. This

procedure is performed using an interactivetechnique in Matlab (The MathWorks Inc., USA).

Inter-person variability assessment: threedierent archaeologists calculate the fragmentproles of four ceramic fragments using the 3Dmethod. Intra-person variability assessment: each

archaeologist calculates the same fragment prolethree times. In summary, each fragment has nineprole depictions obtained by the proposed 3Dmethod.

4.3 Accuracy test of the proposed 3D method

The accuracy error is dened as is in the workdone by Guidi et al.:

Ea= |[1/N N

(i=1)x

i] - x

true| (12)

where N is maximum number ofmeasurements, x

i corresponds to the quantity of a

single measurement andxtrue

is the real value of thequantity. We dene the percentage accuracy error asE

a%= E

a/x

true*100%.

We select the manual depictions of themost experienced archaeologist as the real truemeasurements. Then, the average of quantitiesextracted from these 2D proles is considered asx

true. We use the nine calculations per fragment

obtained by the 3D method as xi(N=9).

4.4 Assessment of the time utilised by the traditionalmethod and the 3D proposed method:

The time utilised in recording the prole ofeach fragment utilising both methods is registeredwith a chronometer in order to ass ess and compareecacy. The time utilised by the NextEngine laserscanner in digitising the fragments and for thepreprocessing and manual steps was taken intoaccount. However, since our approach is able to

work with any other 3D acquisition methods, a fasterlaser device can be utilised for obtainin g complex 3Dmodels in few seconds (Center of Advance SpatialTechnologies 2013).

4.5 Denition of metrics

We dene three metrics which properlydescribe the prole representations obtained from

Figure 7. 2D prole calculation. (a) Estimation of the

prole with more information of the vessel shape. (b)

Calculation of a 2D diagram with the prole of the

ceramic fragment. Here, the radio of the vessel rim and

the location of the axis of symmetry can be deduced.


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the ceramic fragments: diameter of the vessel rim,orientation angle of the fragment prole, and shapedierence.

Diameter: it consists of two times the radio ofthe circumference extracted from the rim of theceramic fragments (see Fig. 8a).

Orientation angle: it is the angle formed by ahorizontal line and the line that best ts the

points corresponding to the external boundaryof the prole (see Fig. 8a).

Shape dierence: this metric measures theaverage error among the locations of points ofvarious aligned proles. It aims to estimate howsimilar is the shape of various prole depictionsdiscriminating other error sources such as thediameter estimation or the orientation angle (seeFig. 8b).

5. Results

5.1 Precision test (inter/intra variability) of thetraditional method.

This study reports the inter-person and intra-

person variability of the three proposed metrics usingthe traditional recording method. Table 1 reportsinter-person variability less than 6.68%, 4.22% and19.39 mm in orientation angle, diameter and shapedierence respectively, whereas Table 2 reportsintra-person variability less than 3.75%, 11.97%and 9.91 mm of the same metrics. Intra-personvariability evaluates the degree of dissimilitudeof metrics within a person. Since three persons

performed the experiment, we have three values ofintra-person variability. We show the minimum andthe maximum of those three results. The 2D prolesobtained by this method are depicted in Fig. 9 top.

5.2 Precision test (inter/intra variability) of theproposed 3D method.

This study reports the inter-person and intra-person variability of the three proposed metricsusing the 3D method. Table 3 reports inter-personvariability less than 1.14 %, 2.97% and 0.88 mm inorientation angle, diameter and shape dierencerespectively, whereas Table 4 reports intra-personvariability less than 0.42%, 2.07% and 0.77 mm ofthe same metrics. In Table 4, as in the previous case,we show the minimum and the maximum of thosethree results. The obtained 2D proles are depictedin Fig. 9 bottom.

5.3 Accuracy test of the proposed 3D method.

This study reports the percentage accuracyerror of the rst two proposed metrics using the 3Dmethod. Table 5 reports accuracy errors less than4.78%, and 4.30% in orientation angle and diameterrespectively. Since the shape dierence metric iscalculated using more than two depictions and wedo not have a true pattern for the comparison, theaccuracy error of that metric cannot be calculated.

5.3 Assessment of the time utilised by the traditionalmethod and the 3D proposed method:

The study reports that the traditional methodtakes an average of 15 minutes per fragment,whereas, the 3D method takes around 2 minuteswithout considering the acquisition time and thepreprocessing step and manual interventions.

Considering 9 minutes for the acquisition time withNextEngine laser scanner and 2 minutes for the othertasks, the whole procedure takes around 13 minutes.Then, 13.3% of reduction in the time utilised by themanual methods in recording the prole of thefragments is achieved by the 3D method proposedin this research.

Figure 8. Denition of metrics. (a) The diameter and the

angle of inclination of the fragment are extracted from the

2D prole. (b) The shape error is dened as the average

difference between two prole representations. Figure 9. Inter/intra-person variability measurements

of four ceramic fragments. Top row: prole depictions

done using the traditional method. Bottom row: prole

dections calculated by the 3D system. It is possible to

deduce that the proposed 3D technique suffers of less

variability compared with the manual techique.

Table 5. Accuracy Error Test Of The Proposed 3D Method For Recording Proles Of Ceramic Fragments. A Total Of

72 Meassurements Were Made Over 4 Ceramic Fragments.

Fragment 1 Fragment 2 Fragment 3 Fragment 4

Min Max Min Max Min Max Min Max

Angle 2.57% 6.68% 1.29% 5.46% 0.94% 4.74% 1.41% 3.61%

Diameter 0% 2.1% 0% 4.22% 1.54% 3.43% 1.12% 2.11%

Shape error (mm) 4.25 6.49 4.15 18.60 7.31 19.39 4.80 14.66

Table 2. Intra-Person Variability Test Using The Traditional Method For Recording Proles Of Ceramic Fragments. A

Total Of 108 Meassurements Were Made Over 4 Ceramic Fragments.

F ra gm en t 1 F ra gm en t 2 Fr agm en t 3 Fr agm en t 4

Angle 0.14% 0.22% 0.15% 0.42%

Diameter 0.19% 0.88% 2.07% 0.55%

Shape error (mm) 0.51 0.53 0.54 0.77

Table 3. Inter-Person Variability Test Using The Proposed 3D Method For Recording Proles Of Ceramic Fragments.

A Total Of 108 Meassurements Were Made Over 4 Ceramic Fragments.

Table 4. Intra-Person Variability Test Using The Proposed 3D Method For Recording Proles Of Ceramic Fragments.


Fragment 1 Fragment 2 Fragment 3 Fragment 4

Min Max Min Max Min Max Min Max

Angle 0.21% 0.94% 0.29% 1.14% 0.14% 0.53% 0.05% 1.01%

Diameter 0.58% 2.07% 1.03% 2.12% 2.36% 2.97% 1.15% 3.23%

Shape error (mm) 0.41 0.57 0.48 0.56 0.37 0.65 0.65 0.88


Angle 2.16% 3.75% 2.68% 1.72%

Diameter 5.57% 11.97% 3.47% 3.16%

Shape error (mm) 5.14 9.51 9.91 7.41

Table 1. A Inter-Person Variability Test Using The Traditional Method For Recording Proles Of Ceramic Fragments.



Angle 3.41% 3.40% 2.13% 4.78%

Diameter 3.21% 2.19% 4.30% 1.67%


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6. Conclusions

The proposed 3D method can record and obtainprole representations of ceramic fragments withmore precision (less variability) than the traditionalmethod as reported in inter/intra variability andaccuracy tests. Traditional methods show that no

matter how well-trained the archaeologist is, it ispretty improbable for them to draw one fragmentexactly the same as they repeat the experiment. Thiscould get worst with large amount of fragments. Theachieved accuracy of the proposed 3D method isacceptable (accuracy error less than 5%) when thedepictions of the most experienced archaeologistare taken as reference. Likewise, the 3D methodreduces in 13.3% the time utilised by the manualmethods in recording the prole of the fragments.This is fundamentally important since archaeologyis an expensive discipline in which time is prettyvaluable. The percentage of time reduction includingthe acquisition process with the NextEngine laserscanner is not considerably high. However, therecent development on 3D recording methodsallows acquiring 3D models of objects in secondsand could reduces the time of the entire procedure

in more than 50%.

In addition, the eld of applicability of thisresearch allows implementing a large 3D data baseof ceramic fragments in which the systematisedinformation is based on the metrics calculatedautomatically. It would allow archaeologists tomanage more information in less time for a lowcost and will enable them to share and publish theirinformation in an easier and better approachablefashion. Finally, this research opens the possibilityof processing the 3D information of the fragmentswith other purposes such as the 3D reconstructio nof the entire vessel based only on the informationof the fragment, or the estimation of the amount ofmaterial utilised for its fabrication. A future researchmust be focused on the assessment of accuracy of

the method in a higher amount of fragments.

Acknowledgements

The authors would like to thank the supportof San Jos de Moro Archaeological Program(Per) for providing access to all the material,technical information and professional assistance.In particular, we want to thank to Andrew Lorey

for the revision and correction of this document.This research was partially supported by theInterdisciplinary Research Project DGI 2013-0113from thePonticia Universidad Catlica del Per.

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1. instead of indicative ceramic fragments, it is

suggested to use diagnostic ceramic fragments

2. experimented archaeologists was changed in

experienced archaeologists

3. Lagarias, J., J. Reeds, M. Wright, and P. Wright.

1988 : this entry is listed in nal bibliography but there is

not in-text reference. please provide one or delete it

4. Guidi, G., F. Remondino, G. Morlando, A. Del Mastio,

F. Uccheddu, and A. Pelagotti. 2007: missing editor of

proceedings

5. Hubeli, A., and M. Gross. 2001: missing place of

publication; please check title of proceedings as it does

not appear to be correct

6. Kampel, M., and F.J. Melero. 2003: missing place

of publication

7. Lagarias, J., J. Reeds, M. Wright, and P. Wright: is

this a electronic-only journal? if it has a printed version

no doi is needed.

8. Lobregt, S., and M. Viergever: is this a electronic-

only journal? if it has a printed version no doi is needed.

9. Mara, H., and R. Sablatnig. 2005: missing place ofpublication and publisher

10. Taubin, G. 1995 : missing place of publication

11. Yao, F., and G. Shao. 2003 missing editor, place of

publication and publisher.

Zwietcovich Et Al - 3D Assessment

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