misrecognized polygons is easy to carry out. After
the process of extracting the vertexes of the recog-
nized polygons, the hatched polygons in vector
form can be used in geographic information sys-
tems.
At last, a process of deleting the recognized
hatched polygons from the original image I (i,j)
should be performed. It is very helpful to recognize
other kinds of map information. ;
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Fig. 13 The result of recognized polygons
8. EXPERIMENTS AND CONCLUSIONS
In order to verify the feasibility and the efficiency
of the method proposed in this paper, we arbitrari-
ly select a 1 : 50000 topographical map as experi-
mental data. The scanning resolutions in both hor-
izontal and vertical directions are 250dpi. This
piece of map includes 834 hatched polygons as well
as many other kinds of graphics. Among the
hatched polygons on this map, 829 hatched poly-
gons are correctly recognized and extracted with
the proposed method. The ramained 5 hatched
polygons are rejected because they are wrongly
drown with unclosed borders on original map. Be-
sides the recognized hatched polygons, 26 polygons
standing for parts of Chinese characters are misrec-
ognized as hatched polygons. The final ratio of
correct recognition of hatched polygons is 96%.
Experiments show that the automatic recognition
method for hatched polygons put forward in this
paper is effective and feasible. It can reach a high
ratio of correct recognition as about 96%. The
misrecognized ones are exclusively parts of chinese
characters. This means that a even higher recogni-
tion ratio of hatched polygons may be reached if
342
this method is performed to maps of western coun-
tries since the western texts on maps are more dif-
firent from hatched polygons. The method has a
strong capability of anti — interference. The
hatched polygons linking to other graphics in origi-
nal scanning image can be correctly recognized and
extracted. According to the recoginition strategy
of layer by layer, it is important to remove the
recoginized map symbols from the original map im-
ages because it will be helpful to extract other lay-
ers of map information afterwards.
References
Capson, D. W. 1984. An improved algorithm for
sequential extraction of boundary from a reaster
scan. Computer Vision, Graphics, and Image Pro-
cessing, 28(109).
Fulford, M. C. 1981. The FASTRAK automatic
digitizing system. Pattern Recognition, 14(1).
Wahl, F. M. etal. 1982. Block Segmentation and
text extraction in mixed text/image documents,
Computer Graphics and Image Processing, 2 (6)
pp375— 390.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996
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