DEVELOPMENT OF HYBRID VECTORIZING SOFTWARE FOR
DIGITIZATION OF CADASTRAL MAPS
Byoungjun SEO, Jaejoon JEONG, Jaebin LEE and Prof.
Yongil KIM, Korea
Key words:
Abstract
The Cadastral map is a basic data that prescribes lot numbers, the
classification of land category, and the boundaries and ownerships of
land parcels. In Korea, the government has tried to digitalize
cadastral maps and inputted the attribute informations of cadastral
maps. But, the efficiency problems have been raised, because the
cadastral services mainly depend on the manual works. Also, the figure
informations of cadastral maps were not digitalized that there have
been many problems in establishing the efficient land information
systems.
In this study, we developed the hybrid vectorizing software to
enhance the deficiency of the analogue methods and to ensure the
accuracy of the cadastral maps. The hybrid vectorizing adopts a
screen-digitizing method as a prototype and automates the procedure of
searching the intersection of lines with efficiency. Consequently, in
the aspect of the accuracy, there is no difference with the
screen-digitizing method because the hybrid method is based on the
screen-digitizing. In the aspect of the efficiency, we can input the
neatline layers at regular intervals and the deformed neatline layers,
and shorten the data input time.
1. INTRODUCTION
1.1 Background
The cadastral map is the base data that defines a lot of number,
the classification of land category, and the boundaries and ownership
of land parcels. Cadastral services occupy about 80% of the
administrative affairs, especially at the regional administration.
This service includes the location information, the utility
limitation, and the resource management of parcels.
Because the cadastral services had been achieved by manual works,
problems of efficiency have been raised. Also, the problems of
accuracy and management have been raised, because the cadastral maps
which were generated under the rule of Japanese imperialism for the
first time have been in use until now. Therefore, the government has
attempted to digitize cadastral maps. By the policy, the attribute
information of the land and the forest land parcels has been digitized
since 1982. But, there were many difficulties in constructing the
efficient land information systems, because the digitization of
cadastral maps which is the graphic information, is not yet completed.
Since 1978, the Administration of Seoul Metropolis and the Korea
Cadastral Survey corporation introduced CGP/1000 systems of Computer
Vision co. and carried out the reconstruction of cadastral maps. This
procedure has the limitation of working hours for digitization by
manual inputs while it guarantees the high accuracy. It takes about
one day to input a cadastral map of 1/600 scale. Therefore, we need 57
years for digitization of 720,000 sheets of cadastral maps, assuming
270 working days per one year and that the number of CGP/1000 systems
are 50. Thus, we can say that the digitization of all the cadastral
maps is impossible without introducing new input methodology.
To overcome the weakpoints of manual input method, screen
digitizing and automated input method can be introduced. Merits of
these methods are that the original data is not changed, because all
the processes are applied to the scanned cadastral maps. But the
screen digitizing method has no advantage of shortening the input time
compared to the manual input method, and the automated vectorizing
method has the different result in the number and position of vectors
as in the original data. Besides, it can be influenced by the quality
condition of the map. Therefore, these two methods cannot be the
efficient tools in digitizing the cadastral maps. Though there were
numerous attempts to induce the automated vectorizing for the
digitization of the cadastral maps, the automated vectorizing methods
could not be adopted because it could not satisfy the accuracy needed
in the cadastral maps and these works are closely related with the
property rights of the people.
1.2 The scope and methodology
In this study, considering the characteristics that the cadastral
maps can't allow for the error, we developed the precise vectorizing
tools, and the methodology of shortening the input time to increase
the operation efficiency. Therefore, the vectorizing tools are based
on the screen digitizing to insure the resultant accuracy, and we
developed the hybrid type vectorizing method which automated the
look-up procedure of intersection points with the line searching
algorithm to increase the operation efficiency. We developed and
realized the line searching algorithm which best fit for the
characteristics that all lines on the cadastral maps are straight
lines, which link the points determined by the actual field survey.
And many functions that can provide convenience in the screen
digitizing procedure with the operator were attached to the
vectorizing tool.
The constitution of this paper is as followings. We raised problems
of existing vectorizing systems in section 2, and described the
methodology for developing the hybrid vectorizing tools in section 3.
In section 4, we tested the accuracy and efficiency of this approach.
Finally, the conclusion and further researches were presented.
2. PROBLEMS OF THE EXISTING VECTORIZING METHOD
The methods for the digitization of cadastral maps could be
classified as three categories. These are the manual input method
using the mapping table, the screen digitizing method using scanned
cadastral maps on the CRT screen, and the automated input method by
the use of line detection algorithms. Following sections describes the
problems of each method.
2.1 The manual input method
Compared with other methods, the vector products from the manual
input method using mapping digitizers guarantee the high accuracy.
When reading coordinates from a digitizing table, the resultant
accuracy is infulenced by the personality, the degree of skillfulness,
and the mental state of the operator. Therefore, the resultant
accuracy can be varied. And there is a fault that the temperature and
humidity of a operation room can affect map sheets and the reference
coordinates can be changed. Besides, it need so much time for
digitizing that this methods are inapplicable to the digitization of
cadastral maps.
2.2 The screen digitizing method
The screen digitizing method had advantages that the original data
is not changed during the operations and that there are no limitation
of devices. Lastly, the accuracy can be guaranteed as the manual input
method. But in this method the operator has to locate the parcel
boundaries with the moving pointer on a computer screen manually as in
the former method. If there are extensive parcels in the scanned
cadastral map or the scanned resolution is very high, the amount of
works for an operator increases. Consequently, this method cannot be
appropriate for the vectorization of cadastral maps.
2.3 The automated input method
The automated vectorizing with the line searching algorithm are
mainly utilized in the area of the map management and developed for
the efficient digitization of already existing map sheets.
Digitization of map sheets which are in good state can be fully
automated, and incorrect locations and inputs of vectors can be
revised with the digitizing operation on a computer screen.
Figure 1. The vectorizing result using the fully
automatic method
 |
|
(a) |
(b) |
(c) |
 |
| (d) |
(e) |
Figure 2. The problems of the fully automatic
method
Though it can speed up the overall processes, the accuracy of
products cannot be secured and the confidence level of the result from
the pattern recognition techniques is low. In the addition, if the
maintenance state of a map sheet is not good, automated processes
cannot be continued. Generally, a line thinning procedure is performed
before the line searching algorithm. These resulting vectors have
focuses on a line itself, but lines on the cadastral map are just the
linkage of points and have no sense of its own. Therefore,
difficulties in the automated vectorizing algorithms are that it
cannot locate the significant points on cadastral maps. <Fig.
1&2> shows the result from the commercial vectorizing software.
From <Fig.1>, we can see so many redundant vectors, so some
softwares settled these problems with the generalization algorithm(see
Fig. 2). But this process usually cannot locate the position of lines
correctly. In <fig. 2(a)>, the thicker line indicates a scanned
line and the thinner line shows the vector that is to be digitized.
<Fig. 2(b)> shows the primitive results after the execution of a
commercial software and <Fig. 2(c)&2(d)> shows the final
result of a generalizing procedure. As shown, all vectors in <Fig.
2(b), 2(c), &2(d)> are different with the vectors shown in
<Fig. 2(a)> in their numbers and locations. Their
inappropriateness was shown in <Fig. 2(e)>.
3. DEVELOPMENT OF THE HYBRID VECTORIZING METHOD
In this study, considering the vectorizing efficiency and the
characteristics that the cadastral maps don't allow for the error, we
developed the hybrid vectorizing tools. It was based upon the screen
digitizing and automated the look-up procedure of intersection points
with the line searching algorithm, otherwise the operator should seek
them inconveniently(see <Fig. 3&4>). For this purpose, we
developed the new line searching algorithm fitted for the vectorizing
of cadastral maps and many tools were added to relieve the operator of
his discomfort. The Microsoft Visual C++ was used for the software
development.
Figure 3. The procedure of the developed software
Figure 4. The processing window
3.1 Application of the new resampling method
Scanning gives the basic data for all of the vectorizing
procedures. Scanned cadastral maps can be accessed with the open menu
whatever its format is. In this procedure our new resampling method is
applied. When a cadastral map is scanned at the resolution of 400 dpi,
the raster image is larger than 8000×7000 pixels. So, in the general
image processing software, lines in the cadastral map can't be seen in
a scaled-down image. In <Fig. 4>, the left is a cadastral map
resampled within 600 pixels. Because it plays the role of an index map
in the vectorizing procedure, we applied the new resampling method to
provide an operator clear-cut lines. <Fig. 5> shows the
resampled result of 11000×9000 pixels image. <Fig. 5(a)> is the
result using our software, and <Fig. 5(b)> is the scaled-down
image of a general image processing software.
 |
| (a) The scaled-down image using the
new resampling method |
(b) The scaled-down image using the
general image processing software |
Figure 5. Application the new resampling method
3.2 Line thinning
Line thinning algorithms are widely used in areas such as
identifying characters and a fingerprints, a circuit board
manufacturing, and etc.. The purpose of it is to minimize the amount
of data for the automatic recognition of patterns in the image.
In the development of a vectorizing software, the thinning process
is not necessary. But the resultant image created from the thinning
algorithm gives more chances for the point which determine boundaries
of parcels to be located nearer than the result without it. So, this
can offer the convenience to the user.
Algorithms used in this study is the parallel thinning algorithm
using weighted-value which is robust to the noise and provides good
quality. While other thinning algorithms have the distorted results
around the intersection points, this algorithm has less distorted
results around the intersection point and the broken points which is
the linear features mainly used in the cadastral map.
Followings are the procedures of the thinning algorithm proposed in
this study.
- Step 1. Determine the weight of each black pixel.
- Step 2. Each of the exterior pixels has a weight of K. If the
eliminating condition is satisfied then, it is
eliminated.(Including the case that the weight is 9)
- Step 3. Determine the weight of each black pixel.
- Step 4. The exterior pixels has each weights as K.
- Step 5. Repeat the step 3 and 4, until there are no black pixels
which satisfy the eliminating condition.
3.3 Automatic line searching algorithm.
As formerly mentioned, the manual input method has the problem of
efficiency and the fully automatic vectorizing method has the problem
that it can't guarantee the accuracy. Because the cadastral map is
related with the individual right of property, the vectorizing method
using allowable errors can't be used in vectorizing. Also, because the
lines in the cadastral map just connect the points, the lines has no
sense of itself. Only the points i.e. the intersection points of lines
is the element composing the parcels. Therefore, to minimize the
allowable error we developed the hybrid vectorizing method.
Automatic line searching algorithm is as followings.
- Step 1. Input manually the broken points and the intersection
points.
- Step 2. Input the indicative points (the direction of
vectorizing) on the lines in cadastral maps.
- Step 3. Calculate the inclination between the intersection
points and the indicative points or the broken points. And
determine the shape of template to be used.
- Step 4. If the line thinning process isn't used, the center of
line is controlled to coincided with the center of a template. And
recalculate the inclination of the indicative direction of
template.
- Step 5. Move the template along to the line using the direction
determined from step 2, the shape of template from step 3, and the
inclination from step 4. If the value of 0 exists at both
extremities of a template, then it is considered as the broken
point or the intersection point. And stop the advance of a
template, and wait for the user input.
In step 3, according to the inclination between the broken point or
intersection point and the indicative point the rule of determining
the shape of a template is as followings. In <Fig. 6>, the
center of the coordinates is the point inputted by user. If the
inclination has the value between -1 and 1, then we use the vertical
shaped template. If the inclination has the value more than 1 or less
than -1, then we use the horizontal shaped template. The length of
template is determined from the scanned resolution. The higher the
resolution is (the thicker the line is) , the longer the length of
template is.
Figure 6. Determining the template using in the
automatic line searching algorithm
Step 4 is the stage that locate the template correctly on the line
and recalculate the direction of searching.(see <Fig. 7>)
Firstly, the template is located on the line at random. Calculate the
drift between the center of the template and the center of line, and
move the template by the amount of the drift. Then, the center of the
template shall coincide with and the center of line. Also, the
inclination between this center and the formerly inputted point is the
moving direction of the template. If the line thinning is done, there
is no need for step 4.
Figure 7. The procedure of the automatic line
searching
In step 5, the template moves according to the defined rules, and
the broken point and the intersection point are automatically found
and appear on the screen. When moving the template, it is monitored
whether the value of 0 exists at both extremes in the template or not.
If the value of 0 exists, then it will stop moving the template and
show the message that the broken point and the intersection point are
found. <Fig. 8> shows the example that the template is stopped.
Figure 8. The procedure of determining the
intersection point using the automatic line searching
The user can input the accurate point among these points. To find
the more accurate point, the thinning procedure need to be performed.
The advantage of this algorithm is that it need less computing time
and can detect the broken point in an acute angle, which could not be
done in a fully automatic process. Moreover, vectorizing is possible
in the case that the boundary of parcels are broken.
3.4 Input and saving layers
To computerize cadastral maps, 7 layers should be digitalized. (Gr:
lattice point, Jm: land category, Jp: lot number, Li: boundary line,
Po: matching reference point, Qu: neat line) But, layers to be
digitized in the vectorizing program are the boundary line layer and
the neat line layer.
The neat line layer is used to correct the distortion of the
cadastral map after performing the vectorizing. The neat line of the
cadastral map are composed of 4 straight lines. But, because of the
distortion of the map sheet program require the user's input at the
pixel corresponding to 3-4 cm. Also we used the line detection
algorithm to update the vectors in the case that the map boundary line
isn't rectilineal. Therefore, the number of input vector at one side
of neat line is 10.
The inputted vector data is saved as a dxf file format, and it can
hold the information of the layers.
4. TEST OF THE ACCURACY AND THE EFFICIENCY.
 |
| (a) The scanned cadastral map |
(b) Output dxf file |
Figure 9. The scanned cadastral map and Output dxf
file
To test the accuracy and the efficiency of the developed program in
this study, the vectorizing method using the developed software was
compared with the screen digitizing method using the autocad program.
Comparison with the fully automatic vectorizing method couldn't be
performed because the number of vectors and the accuracy of the
automatic vectorizing method were variable.
The result of the test is as followings. The computer system
equipped the Pentium II -233MHz CPU and 128 MB RAM was used. The map
was scanned at the resolution of 400 dpi and the size of a scanned map
was 8000×6700 pixels.
4.1 Comparison between these vectorizing methods
Because these methods are mainly based on the screen digitizing,
the accuracy test among these methods is the matter of the operator's
sincerity and skill, not the method itself. Therefore, we just
performed the comparison among these methods in the aspect of
efficiency.
<Table 1> shows the result of the comparison. There were no
differences in inputting layers of the map boundary lines. But, using
the developed software we could input the map boundary lines at the
same interval, and could input the map boundary lines effectively even
if the map boundary lines were distorted. And, when inputting the
layers of the boundary lines, we could save time(approximately 30
minutes) using the developed software. This means that the operator's
charge could be reduced. because the pointer was located within less
than 1-2 pixels from the center of the parcel boundary lines.
Consequently, there is no problem in the accuracy. And we could
save 30 minutes for the processing.
4.2 The accuracy of the vectorizing
When computerizing the cadastral map, the most impotent issue is
the error between the raw data(the cadastral map) and the digital
data(the result of vectorizing). As the vetorizing method, the
expression of the accuracy is different. In the manual input method,
the visual interpretation technique has been used. But, when we use
the raster file scanned from the cadastral map sheet, the accuracy
should be examined in three aspects like followings.
Table 1. Comparison between these vectorizing
methods
- the accuracy between the cadastral map and the raster file.
- the accuracy between the raster file and the input vector file
using this raster file.
- the accuracy between the cadastral map and the input vector
file.
Among these, the first is related the accuracy of a scanner.
Generally, the drum scanner is better than the flat bed scanner. But,
the drum scanner can't be used in digitizing the cadastral map because
the cadastral map is made from the aluminum kent paper or the Korean
paper. Also, when we use the flat bed scanner, there is the problem
that the size of the flat bed scanner does not match with the size of
the cadastral map. But, these problems can be solved because the
accuracy and the size of a flat bed scanner are increased recently.
Secondary, aspect of the accuracy is dependent on the operator's
character, career, and etc.. Therefore, the accuracy can't be tested
from this point of view. When we digitize the cadastral map with the
developed software, the thickness of lines in the cadastral map is
approximately 3 pixels. If we have a mistake in inputting the center
point, the error of 1 pixel will be occurred in the x, y direction. It
can be calculated as the distance on the map sheet. The value is
0.0898(mm).
It is less than the limit of the allowable drawing error(0.2mm)
which is generally used in a map drawing. Also, it is less than the
resolution of the automatic drawing instrument(0.1mm) in a digital
map. Therefore, there will be no problem if there is no mistake of an
operator.
Finally, the accuracy between the cadastral map and the vector file
is determined by the first and the second accuracy. So, if there is no
problem at the first and second accuracy, there will be no problem at
the third aspect of the accuracy.
5. CONCLUSION AND FURTHER RESEARCH
The main issue of digitizing the cadastral map is how we can input
the cadastral map correctly and efficiently.
The methods to make up for the weak point of the manual input
method are the screen digitizing method and the automatic input
method. A strong point of these two methods is not transforming the
raw data, because these methods are operated after scanning the
cadastral map. But the screen digitizing method is not more efficient
in reducing the input time than the manual input method. The automatic
input method produces different positions and numbers of vectors, and
sometimes, it is difficult to be applied according to the condition of
maps. So, these two methods can't be adopted for efficient digitizing
of the cadastral map. Especially, there was an attempt to use the
automatic input method as a tool for digitizing the cadastral map, but
the automatic input method couldn't be applied, because the cadastral
map is related with the right of property, and cannot allow for the
error.
In this study, we developed the hybrid vectorizing software to
enhance the deficiency of the analogue methods and to ensure the
accuracy of the cadastral maps. The hybrid vectorizing adopted a
screen-digitizing as a protype and automated the procedure of
searching the intersection of lines with efficiency. We developed and
applied the new line searching algorithm suitable for the cadastral
map, and added some functions to give an operator convenience at the
screen digitizing task.
The result of developed software was found that there are no
vectorized lines which are exceed map boundaries in the visual
interpretation. So it is same as the screen digitigizing method in the
accuracy. Also, we test the efficiency by comparing the software
developed in this study with the screen digitizing method using the
AutoCad program. As a result, we can save 35 minutes using this
software.
As the output of this software is dxf formatted not including
topology, the further study about the topological product should be
progressed. From this, we can use the cadastral map efficiently and
can construct the integrated land information system based on it. Only
if this process accomplished, we can use the cadastral map efficiently
as the base map on GIS.
ACKNOWLEDGEMENT
This research is performed by the project of "Development of
Expert System that contains Expansion-Shrinkage Correction, Map
Matching Correction and Quality Examinations for Computerization of
cadastral map", sponsored by Ministry of Science & Technology
of Korea.
REFERENCES
1. Ministry of Science & Technology of Korea , 1998,
Development of Expert System that contains Expansion-Shrinkage
Correction, Map Matching Correction and Quality Examinations for
Computerization of cadastral map , pp. 79-81.
2. Korea Cadastral Survey Corporation, 1987, A Study on the
Cadastral Map Revise, p. 46.
3. Baek Seung-Chul, 1994, A Study on the Cadastral Map
Re-production by Scanning, Master's Thesis, Chongju University.
4. Research Institute of Computer, Information & Communication,
Busan National University , 1998, Development of a Vectoring Software
for Printed Maps,
5. Seoul Development Institute, 1993, The Study of Seoul City
Implementing City-wide GISs, Seoul Development Institute, 93-R-25.
6. Han Nak-hee, Rhee Phil-Kyu, 1996, Parallel Thinning Algorithm
using Weighted-Value, Korea Journal of Cognitive Science, Vol.7, No.1,
pp. 5-35.
CONTACT
Byoungjun Seo
Ph. D. Course, Researcher
Department of Civil, Urban & Geo-Systems Engineering
Seoul National University
Shillim Dong
Gwanak Gu
Seoul
KOREA
Tel. + 82 2 880 7371
Fax + 82 2 889 0032
E-mail: cttrap@chollian.net
Jaejoon Jeong
Ph. D. Course, Researcher
Department of Civil, Urban & Geo-Systems Engineering
Seoul National University
Shillim Dong
Gwanak Gu
Seoul
KOREA
Fax + 82 2 889 0032
E-mail: hayoon@chollian.net
Jaebin Lee
Graduate Course
Department of Civil, Urban & Geo-Systems Engineering
Seoul National University
Shillim Dong
Gwanak Gu
Seoul
KOREA
Fax + 82 2 889 0032
E-mail: damanegi77@hotmail.com
Assoc. Prof. Yongil Kim
Department of Civil, Urban & Geo-Systems Engineering
Seoul National University
Shillim Dong
Gwanak Gu
Seoul
KOREA
Fax + 82 2 889 0032
E-mail: yik@snu.ac.kr
12 April 2001
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