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Taddeüs Kroes
uva
Commits
871fe57e
Commit
871fe57e
authored
Oct 09, 2011
by
Taddeüs Kroes
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improc ass3: Resolved conflicts.
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improc/ass3/report/report.tex
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...
...
@@ -35,11 +35,113 @@ color model. An example of non-absolute color model is RGB.
% describe your model in your report. What are the conversion formula’s and why
% was this color model invented?
It is useless to convert an absolute color model to a non-absolute color
model, since it not possible to generate ... We chose the HSV color model.
It is useless to convert an absolute color model to a non-absolute color model,
since it will only lose information without any gain. On the other hand,
conversion between two non-absolute color models can be useful. We chose to
convert the RGB color model the HSV color model.
% Does your model improve the results compared with the RGB model?
In most cases, the HSV color model gives a better result. When comparing
picture 8 with picture 1, 2 and 3, the histogram intersections of the RGB color
model are resp. 52
\%
, 66
\%
and 66
\%
. With the HSV color model, these
intersections are resp. 28
\%
, 61
\%
and 45
\%
.
\begin{figure}
[H]
\center
\includegraphics
[height=3cm]
{
../database/8.jpg
}
\caption
{
Picture 8 from the given database.
}
\end{figure}
If we visually compare picture 8 with the pictures 1, 2 and 3, we can clearly
see that picture 2 shows more similarities (similar yellow color, similar size
and ratio of the object) than the other two pictures.
\begin{figure}
[H]
\center
\includegraphics
[height=3cm]
{
1-2-3.jpg
}
\caption
{
From left to right picture 1, 2 and 3 from the given database.
}
\end{figure}
However, in the RGB model, there is no clear distinction in the histogram
intersections (52
\%
, 66
\%
and 66
\%
), while the HSV model gives picture 1 and 3
a much lower intersection percentage (picture 2 has 61
\%
, picture 1 has 28
\%
and picture 3 has 45
\%
).
So, using the HSV color model does improve the results.
\subsection
{
Histogram intersection tables
}
\begin{table}
[H]
\hspace
{
-1.5in
}
\begin{tabular}
{
r|rrrrrrrrrrrrrrrrrrrr
}
\toprule
&
1
&
2
&
3
&
4
&
5
&
6
&
7
&
8
&
9
&
10
&
11
&
12
&
13
&
14
&
15
&
16
&
17
&
18
&
19
&
20
\\
\midrule
1
&
100
&
57
&
56
&
41
&
40
&
45
&
28
&
52
&
51
&
43
&
45
&
54
&
35
&
54
&
59
&
36
&
51
&
47
&
38
&
44
\\
2
&
57
&
100
&
60
&
56
&
47
&
53
&
36
&
66
&
59
&
39
&
41
&
63
&
39
&
65
&
60
&
51
&
59
&
61
&
36
&
54
\\
3
&
56
&
60
&
100
&
46
&
49
&
63
&
24
&
66
&
60
&
58
&
40
&
75
&
48
&
52
&
57
&
35
&
53
&
54
&
45
&
48
\\
4
&
41
&
56
&
46
&
100
&
47
&
47
&
35
&
50
&
48
&
36
&
39
&
49
&
39
&
42
&
48
&
34
&
40
&
63
&
38
&
35
\\
5
&
40
&
47
&
49
&
47
&
100
&
50
&
27
&
53
&
46
&
40
&
40
&
48
&
38
&
45
&
41
&
34
&
38
&
50
&
38
&
36
\\
6
&
45
&
53
&
63
&
47
&
50
&
100
&
25
&
60
&
53
&
43
&
38
&
59
&
49
&
46
&
47
&
35
&
45
&
55
&
46
&
42
\\
7
&
28
&
36
&
24
&
35
&
27
&
25
&
100
&
29
&
28
&
14
&
28
&
25
&
14
&
28
&
28
&
31
&
28
&
35
&
24
&
28
\\
8
&
52
&
66
&
66
&
50
&
53
&
60
&
29
&
100
&
51
&
44
&
40
&
67
&
44
&
57
&
54
&
43
&
52
&
57
&
44
&
45
\\
9
&
51
&
59
&
60
&
48
&
46
&
53
&
28
&
51
&
100
&
45
&
41
&
56
&
41
&
51
&
49
&
39
&
53
&
50
&
37
&
48
\\
10
&
43
&
39
&
58
&
36
&
40
&
43
&
14
&
44
&
45
&
100
&
29
&
48
&
52
&
35
&
39
&
20
&
35
&
40
&
53
&
27
\\
11
&
45
&
41
&
40
&
39
&
40
&
38
&
28
&
40
&
41
&
29
&
100
&
39
&
25
&
40
&
40
&
31
&
39
&
40
&
26
&
43
\\
12
&
54
&
63
&
75
&
49
&
48
&
59
&
25
&
67
&
56
&
48
&
39
&
100
&
41
&
57
&
62
&
41
&
55
&
56
&
36
&
51
\\
13
&
35
&
39
&
48
&
39
&
38
&
49
&
14
&
44
&
41
&
52
&
25
&
41
&
100
&
31
&
35
&
20
&
36
&
43
&
65
&
25
\\
14
&
54
&
65
&
52
&
42
&
45
&
46
&
28
&
57
&
51
&
35
&
40
&
57
&
31
&
100
&
55
&
51
&
57
&
48
&
31
&
54
\\
15
&
59
&
60
&
57
&
48
&
41
&
47
&
28
&
54
&
49
&
39
&
40
&
62
&
35
&
55
&
100
&
39
&
49
&
52
&
34
&
45
\\
16
&
36
&
51
&
35
&
34
&
34
&
35
&
31
&
43
&
39
&
20
&
31
&
41
&
20
&
51
&
39
&
100
&
57
&
41
&
19
&
45
\\
17
&
51
&
59
&
53
&
40
&
38
&
45
&
28
&
52
&
53
&
35
&
39
&
55
&
36
&
57
&
49
&
57
&
100
&
47
&
32
&
57
\\
18
&
47
&
61
&
54
&
63
&
50
&
55
&
35
&
57
&
50
&
40
&
40
&
56
&
43
&
48
&
52
&
41
&
47
&
100
&
40
&
40
\\
19
&
38
&
36
&
45
&
38
&
38
&
46
&
24
&
44
&
37
&
53
&
26
&
36
&
65
&
31
&
34
&
19
&
32
&
40
&
100
&
25
\\
20
&
44
&
54
&
48
&
35
&
36
&
42
&
28
&
45
&
48
&
27
&
43
&
51
&
25
&
54
&
45
&
45
&
57
&
40
&
25
&
100
\\
\bottomrule
\end{tabular}
\caption
{
Histogram intersection of 20 pictures with the RGB color model.
}
\end{table}
\begin{table}
[H]
\hspace
{
-1.5in
}
\begin{tabular}
{
r|rrrrrrrrrrrrrrrrrrrr
}
\toprule
&
1
&
2
&
3
&
4
&
5
&
6
&
7
&
8
&
9
&
10
&
11
&
12
&
13
&
14
&
15
&
16
&
17
&
18
&
19
&
20
\\
\midrule
1
&
100
&
36
&
50
&
22
&
25
&
35
&
20
&
28
&
38
&
29
&
32
&
37
&
17
&
38
&
47
&
28
&
39
&
34
&
16
&
30
\\
2
&
36
&
100
&
48
&
49
&
43
&
48
&
34
&
61
&
52
&
12
&
37
&
55
&
12
&
51
&
50
&
47
&
52
&
57
&
11
&
49
\\
3
&
50
&
48
&
100
&
30
&
33
&
52
&
18
&
45
&
49
&
37
&
32
&
58
&
22
&
38
&
48
&
30
&
51
&
42
&
19
&
45
\\
4
&
22
&
49
&
30
&
100
&
41
&
34
&
33
&
40
&
36
&
5
&
32
&
36
&
7
&
30
&
37
&
26
&
27
&
54
&
10
&
28
\\
5
&
25
&
43
&
33
&
41
&
100
&
42
&
25
&
43
&
38
&
4
&
36
&
39
&
4
&
37
&
35
&
31
&
30
&
40
&
5
&
34
\\
6
&
35
&
48
&
52
&
34
&
42
&
100
&
22
&
48
&
42
&
13
&
34
&
53
&
12
&
42
&
43
&
33
&
41
&
46
&
10
&
40
\\
7
&
20
&
34
&
18
&
33
&
25
&
22
&
100
&
25
&
22
&
4
&
25
&
22
&
4
&
25
&
24
&
27
&
21
&
32
&
15
&
24
\\
8
&
28
&
61
&
45
&
40
&
43
&
48
&
25
&
100
&
41
&
4
&
33
&
56
&
5
&
41
&
40
&
36
&
44
&
47
&
6
&
43
\\
9
&
38
&
52
&
49
&
36
&
38
&
42
&
22
&
41
&
100
&
17
&
35
&
46
&
12
&
44
&
40
&
35
&
48
&
35
&
7
&
43
\\
10
&
29
&
12
&
37
&
5
&
4
&
13
&
4
&
4
&
17
&
100
&
6
&
17
&
45
&
14
&
20
&
5
&
18
&
11
&
42
&
7
\\
11
&
32
&
37
&
32
&
32
&
36
&
34
&
25
&
33
&
35
&
6
&
100
&
35
&
4
&
33
&
34
&
27
&
31
&
35
&
5
&
37
\\
12
&
37
&
55
&
58
&
36
&
39
&
53
&
22
&
56
&
46
&
17
&
35
&
100
&
12
&
48
&
55
&
37
&
51
&
46
&
9
&
48
\\
13
&
17
&
12
&
22
&
7
&
4
&
12
&
4
&
5
&
12
&
45
&
4
&
12
&
100
&
12
&
12
&
4
&
16
&
12
&
58
&
5
\\
14
&
38
&
51
&
38
&
30
&
37
&
42
&
25
&
41
&
44
&
14
&
33
&
48
&
12
&
100
&
46
&
45
&
44
&
40
&
13
&
40
\\
15
&
47
&
50
&
48
&
37
&
35
&
43
&
24
&
40
&
40
&
20
&
34
&
55
&
12
&
46
&
100
&
35
&
44
&
47
&
14
&
38
\\
16
&
28
&
47
&
30
&
26
&
31
&
33
&
27
&
36
&
35
&
5
&
27
&
37
&
4
&
45
&
35
&
100
&
49
&
35
&
5
&
41
\\
17
&
39
&
52
&
51
&
27
&
30
&
41
&
21
&
44
&
48
&
18
&
31
&
51
&
16
&
44
&
44
&
49
&
100
&
39
&
13
&
52
\\
18
&
34
&
57
&
42
&
54
&
40
&
46
&
32
&
47
&
35
&
11
&
35
&
46
&
12
&
40
&
47
&
35
&
39
&
100
&
14
&
36
\\
19
&
16
&
11
&
19
&
10
&
5
&
10
&
15
&
6
&
7
&
42
&
5
&
9
&
58
&
13
&
14
&
5
&
13
&
14
&
100
&
5
\\
20
&
30
&
49
&
45
&
28
&
34
&
40
&
24
&
43
&
43
&
7
&
37
&
48
&
5
&
40
&
38
&
41
&
52
&
36
&
5
&
100
\\
\bottomrule
\end{tabular}
\caption
{
Histogram intersection of 20 pictures with the HSV color model.
}
\end{table}
\section
{
Histogram Backprojection
}
\subsection
{
Finding Waldo
}
...
...
@@ -122,4 +224,6 @@ of 0.25 and a convolution radius of 10 pixels, the result is as follows:
and convolution radius.
}
\end{figure}
\end{document}
\ No newline at end of file
\end{document}
\end{document}
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