CIPA 2003 XIX th International Symposium, 30 September - 04 October, 2003, Antalva, Turkey 
The smoothness of the visualization of the reconstructed 
3D-model depends on n. Larger n means smoother, but 
slower to display. Experiments have shown that 180 < n 
< 360 is the best trade off between performance and qual 
ity of the visualization of the reconstructed object. 
Reconstruction is done by rotating the profiCe 360° about 
the rotational axis using R z (7). 
object — {projiie * R z (7i)}, i = 1.. .n, 
7i = 0, 7 i+ i = 7i + A7, A7 = 2 * rx/n (5) 
Figure 10a shows the reconstruction of a pot and Figure 10b 
shows the reconstruction of fragment. The reconstruction 
of these two Figures were based on the longest profile line 
from Figure 8. 
4 RESULTS 
Experiments were done on the 33 sets of 3D images stored 
in box 1 and 2 and 26 real data sets from box 3 of archaeo 
logical fragments given by archaeologists for testing. Each 
set contained one image of the inner half and one of the 
outer half of the sherd. In 29% of the sherds the estimation 
of the rotational axis returned a correct result. 31% of the 
results had two different types of minor errors, which are 
still acceptable for further processing. 
The first acceptable error was a to large distance between 
the inner and out half (2 to 3 cm). The second acceptable 
error was a slightly twisted (less than 10°) inner half com 
pared to the orientation of the outer half. These two errors 
have been observed on small sherds or sherds with a small 
curvature (Sablatnig and Kampel, 2002). For 7 sets the es 
timation of the rotational axis did not have a correct result, 
because the sherd were to small, to flat, contained a handle 
or were part of a bottom fragment. All of these 7 sets have 
normal vectors, which do not point at the rotational axis. 
So the estimation of the rotational axis was not done cor 
rectly. 
The success rate for correct extraction of the profile line 
and consequently the percentage of sherds, which is used 
for further classification is 50% of the sherds found at the 
excavation site. This has to be seen with respect to man 
ual archivation done by archaeologists (Orton et al., 1993): 
for coarse ware 35% (Degeest, 2000) and for fine ware 
50% (Poblome, 1999) of the findings are used for further 
classification. It depends on the ratio between bending of 
the curvature (Matas et al., 1995, Bennett and MacDon 
ald, 1975) and the fragment and its diameter (Sablatnig 
and Kampel, 2002) (e.g. handle, flat fragments like bot 
tom pieces, small size, etc.). 
The execution time using a prototype written in MAT LAB 
running on a Pentium III 1 GHz is less than a minute per 
sherd. The estimation of rot takes 70% to 80% of the exe 
cution time for processing one sherd described by the inner 
and outer view. Comparing the execution time for the ex 
traction and segmentation of profile lines to the time used 
by archaeologists drawing a profile line by hand shows that 
the number of classification per day can be increased dra 
matically. 
The estimation of the rotational axis will also be used to 
reconstruct whole objects from several sherds. Figure 10a 
displays a reconstructed pot (gray object) out of one frag 
ment (dark object) based on the profile line (light line) 
and its axis of rotation (dashed line). Figure 10b shows 
a detailed part of the same object as Figure 10a. Table 2 
(b) 
Figure 10: (a) Reconstructed (gray) pot and (b) fragment, 
cross-section (light gray line), recorded fragment (dark 
gray) and its rotational axis (vertical dashed line). 
shows successfully estimated features for further classifi 
cation of box 1 and box 2. These features are the diameter 
at the highest point of the sherd (rim-diameter rdm in cm). 
The maximum diameter of thb sherd orthogonal to the ro 
tational axis (wall-diameter wdm in cm). The diameter 
at the lowest point of the sherd (bottom-diameter bdm in 
cm). The overall height (h max in cm) of the sherd and 
the characteristic ratio crat = h : rdm. Box 3 contains 
Box 
Nr 
rdm 
wdm 
bdm 
hmax 
crat 
1 
04 
25,16 
75,61 
24,94 
7,12 
0,33 
1 
08 
31,78 
50,16 
32,08 
5,63 
0,63 
1 
16 
30,68 
49,32 
30,9 
6,68 
0,62 
1 
17 
32,64 
42,31 
34,32 
8,81 
0,77 
1 
18 
32,34 
31,06 
32,1 
4,68 
1,04 
1 
19 
28,9 
33,80 
29,38 
9,15 
0,85 
1 
20 
26,78 
30,15 
27,32 
7,09 
0,89 
1 
22 
22,8 
27,62 
23,86 
6,04 
0,83 
1 
23 
24,58 
44,61 
25,32 
7,4 
0,55 
2 
01 
20,68 
54,22 
20,8 
7,05 
0,38 
2 
02 
32,58 
35,02 
32,9 
8,94 
0,93 
2 
04 
12,54 
35,66 
17,38 
6,9 
0,35 
2 
05 
19,92 
25,79 
20,56 
6,15 
0,77 
2 
06 
6,84 
22,85 
7 
10,15 
0,30 
2 
09 
24,66 
19,05 
25,76 
6,96 
1,29 
Table 2: Results of proper registered and orientated sherds.