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BACKGROUND OF THE INVENTION
1. Field of Invention
This invention relates to a method of identifying a contour line of an
object to be detected by using an image pick-up device, for example, a
television camera.
2. Description of the Prior Art
Among prior art, methods of calculating the values of characteristic
parameters of an object from a television picture image (a multivalue
picture image) may be mentioned a region method and a contour line
detection method.
According to the region method, the picture image is divided into a
plurality of partial image regions each having substantially the same
brightness and then the object is identified by judging the continuity of
the regions on the assumption that respective surfaces of the object has
similar brightness.
Although this method is effective for an object constituted by planes, when
curved surfaces present, the processing thereof is difficult. Moreover,
since all picture image data are processed, the amount of data becomes
excessive, thus making it difficult a high speed processing.
On the other hand, the contour line extraction method utilizes the edges of
respective surfaces of the object and according to this method, the points
of the picture image at which the brightness changes rapidly are extracted
as the edges, and the edges are connected together to convert them into a
line picture. This method contemplates detection of lines in the picture
image so that when compared with the region method which detects the
surfaces, the number of detection stops and the quantity of informations
for investigating their continuity are small so that high speed processing
can be made.
The steps of identifying a circular body with the contour line extraction
method will be described with reference to FIGS. 1a through 1d. At first,
an original picture image (shown in FIG. 1a) photographed with a
television camera is differentiated along respective scanning lines to
extract a contour candidate point at which the brightness changes rapidly.
Then, picture elements near this point are similarly differentiated and a
picture elements having the maximum differentiated value is taken as a
point continuous to the contour candidate point. This processing is
repeated many times to obtain continuous contour points (contour line
candidate)(see FIG. 1c) and when these contour points are closed (see FIG.
1d) they are deemed as an object.
According to this prior art contour extraction method, tracing of the
contour candidate points are rendered difficult by the following factors.
(1) blooming caused by metal luster (see FIG. 2a),
(2) overlapping of object (see FIG. 2b),
(3) vague or not clear image caused by rust, spoil, etc. of the object
surfaces,
(4) distortion of the picture image caused by electrical noise.
As a consequence, there is a defect that an actually presenting object
would not be detected. Furthermore, identifying algorithm for solving
these problems becomes complicated so that real time processing is almost
impossible.
SUMMARY OF THE INVENTION
It is the principal object of this invention to provide a novel method of
accurately identifying the contour line of a circle or an object having a
configuration similar to a circle or a portion thereof by using a simple
electric circuit and simple processing steps.
According to this invention, there is provided a method of identifying a
contour line comprising the steps of presuming picture image data
indicative of contour candidate points of an object to be detected based
on picture image data representing the brightness of one picture in which
the object presents, and scanning the picture image data in a
predetermined region containing the picture image data so as to identify
the contour line of the object.
According to a modified embodiment of this invention, there is provided a
method of identifying a contour line comprising the steps of presuming
picture image data indicative of a contour candidate point of an object to
be detected based on picture image data representing the brightness of one
picture in which the object presents, extracting, from the positions of
the picture image data, picture image data of a plurality of picture
elements including the contour candidate point, picture image data of a
plurality of picture elements on the outside of the contour candidate
point, and picture image data of a plurality of picture elements on the
inside of the contour candidate point, determining average values of the
brightness of the three picture image data; determining the differences
between the mean values regarding adjacent contour candidate points, and
identifying that the adjacent contour candidate points are continuous when
one of the differences lies in a predetermined range.
BRIEF DESCRIPTION OF THE DRAWINGS
Further objects and advantages can be more fully understood from the
following detailed description taken in conjunction with the accompanying
drawings, in which
FIGS. 1a-1d are diagrammatic representations showing the steps of
identifying an object according to a prior art method of contour
extraction;
FIGS. 2a and 2b are diagrammatic representations showing one example of
prior art factors that render difficulty to trace a contour line;
FIG. 3 is a block diagram showing one example of the apparatus utilized to
carry out the method of identifying a substantially circular contour line
according to this invention;
FIG. 4 shows the degree of brightness of a picture image data stored in the
RAM array shown in FIG. 3;
FIGS. 5a and 5b are flow charts showing one example of the steps of
processing executed by the central processing unit shown in FIG. 3;
FIGS. 6a-6e are diagrams for explaining the steps of the flow charts shown
in FIGS. 5a and 5b;
FIG. 7 is a flow chart showing successive steps of the processings executed
by the central processing unit for identifying the continuity of the
contour line;
FIGS. 8a-8e are diagrams useful to explain the chart shown in FIG. 7;
FIGS. 9a-9c respectively show one examples of several picture elements
including a contour candidate point, several picture elements on the
outside of the contour candidate point, and several picture elements on
the inner side of the contour candidate point;
FIG. 10 is a graph showing one example of a mean value of the brightness
along the entire periphery of the contour line, and
FIG. 11 shows another example of the contour candidate point.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
A preferred embodiment of this invention will now be described with
reference to the accompanying drawings.
It is assumed that an object to be detected is a circular body 1 shown in
FIG. 3. An industrial television (ITV) camera 2 photographs the circular
body or object in a predetermined field of view to send a video composite
signal containing the brightness signal of the input picture image to a
synchronous isolating circuit 3 and an A/D converter 4. The synchronous
isolating circuit 3 operates to separate a synchronizing signal from the
video composite signal. The synchronizing signal thus separated is used to
designate an address of a random access memory array (RAM array) 5, while
the A/D converter 4 converts the inputted video composite signal into a
picture image data having 16 tones of brightness for writing the picture
image data in the designated address. In this manner, picture image data
corresponding to one picture and representing the brightness of the
original picture shown in FIG. 4. Any desired picture image data can be
read out by designating X and Y addresses of the RAM array 5.
Memory means 6 stores the main program or the like for carrying out the
method of this invention, and a central processing unit (CPU) 7 executes
the processing of the picture image data stored in the RAM array in
accordance with the content of the main program.
The steps of processing executed by the CPU 7 will be described as follows
with reference to the flow charts shown in FIGS. 5a and 5b and the
diagrams shown in FIGS. 6a-6e.
At step 100 shown in FIG. 5a, the threshold value D of the differentiated
value, the diameter L of the circular body, the number of scannings Ns in
the radial direction, and the present number No of the contour candidate
point are set. The threshold value D is used to judge the contour
candidate point at which the brightness of the picture image data varies
rapidly. In this embodiment, the number of scanning is selected to be 8
and the number of presets No is selected to be 6.
After the initial setting has been completed, the present picture image
data (see FIG. 6a) in the RAM array 5 is searched for finding out the
center position candidate point of the circular body. The search of the
center position candidate point is made by differentiating in the X
direction. The picture image data stored in the RAM array 5, and based on
the positions of respective contour candidate points when the spacing
between two contour candidate points at which the brightness changes
rapidly approaches the set diameter L.
More particularly, at step 101, the number n of the contour candidate
points is set to zero, at step 102, the present picture image is scanned
in the X direction, and at step 103, the differentiated value D' of the
picture image data is calculated. At step 104, a judgment is made as to
whether the differentiated value D' has exceeded the threshold value D or
not. When the differentiated value D' has exceeded the threshold value D,
the coordinate position of D' is stored at step 105, and at step 106 n is
incremented by one. At step 107, a judgement is made as to whether n is
equal to or larger than 2. When the result of this judgement is YES, at
step 108 the distance L' (see FIG. 6b) between any two stored points is
calculated. Then at step 109, a judgment is made as to whether the
distance L' is close to the initially set diameter L or not. When the
result of this judgment is YES, at step 110, the center position candidate
point C (X,Y) (see FIG. 6c) is calculated by utilizing the coordinate
positions of the two points. It should be understood that the method of
searching the center positions candidate point is not limited to the
illustrated embodiment. For example, a method can be used wherein more
than three contour candidate points are determined so as to calculate the
center position candidate point based on a circle passing through these
three points.
Thereafter, the contour candidate point of the circular body is searched
based on the center position candidate point of the circular body so as to
check presence or absence of the contour line, that is, the circular body.
Referring now to FIG. 5b, at step 111, the number n of the contour
candidate points is set to zero for scanning in a preset radial direction
from the center position candidate point. Since the radius R (=L/2) of the
circular body has been given the region to be scanned is limited to a
doughnut shaped region bounded by a circle having a permissible minimum
radius (R-.DELTA.R), and a circle having a permissible maximum radius
(R+.DELTA.R). The preset scanning directions are 8, that is 0 (+X
direction), .pi./4, .pi./2, 3.pi./4, .pi., 5.pi./4, 3.pi./2 and 7.pi./4 by
taking the center position candidate point as the reference point (see
FIG. 6d).
At the time of scanning in respective radial directions, the maximum
differentiated value D.sub.max is set to zero at step 112. After that, at
step 113, the scanning is made in either of the eight radial directions
and at step 114, the differentiated value D' of the picture image data is
calculated. At step 115, a judgment is made as to whether the
differentiated value D' is larger than the maximum differentiated value
D.sub.max or not. When the result is YES, at step 116, the differentiated
value D' is changed for the maximum differentiated value D.sub.max so that
in the scanning range, all maximum differentiated values are changed to
the maximum differentiated values. At step 117, a judgment is made whether
the scanning in the range has completed or not. When the scanning has
completed, at step 118, a judgment is made as to whether the maximum
differentiated value D.sub.max has exceeded the threshold value D or not.
When the result of judgment is YES, at step 119, the number n of the
contour candidate point is incremented by one. After that, at step 120, a
judgement is made as to whether the contour candidate point presents or
not in the eight scanning directions. When the total number n of the
contour candidate points is larger than the preset number No (in this
example 6) of the contour candidate points, it is judged that the contour
line of the circular body presents in the doughnut shaped region. On the
other hand, when the total number n of the contour candidate points is
less than the preset number No, the search of the center position
candidate point of the circular body is performed again at step 121.
Finally, when the presence of the contour line of the circular body is
recognized, at step 122, an approximate circle is determined from n
contour candidate points, and at step 123, the coordinates of the center
of the circle and, if desired, its diameter are calculated (see FIG. 6e),
thus finishing the processing of the picture image.
When photographing a circular body with the ITV camera 2, where the center
of the circular body is displaced from the ITV camera the resulting
contour line is not a true circle but an ellipse. The method of this
invention is also applicable to such a case. Furthermore, the invention is
also applicable to a substantially circular body (an ellipse close to a
circle or a polygon).
The number Ns of scannings in the radial direction, the direction of
scanning, and the preset number No establishing the threshold value are
not limited to those described above.
After the presence of the contour line of a circular body has been
recognized, the continuity of the contour line is identified by the
following method.
FIG. 7 shows a flow chart indicative of the successive steps of the CPU 7
for identifying the continuity of the contour line. At step 200,
characterizing points of an object to be detected are extracted from the
present picture image data (see FIG. 8a) stored in the RAM array 5. In
this example, since the object to be detected is assumed to be a circular
body, as its characteristic point is detected--the center position Po (Xo,
Yo) of the circle (see FIG. 8b). The method of detecting the
characteristic point is not limited to that described above and the
characteristic point can be detected by differentiating in the X direction
the picture image data stored in the RAM array 5 so as to detect
characteristic point based on the two contour candidate positions the
spacing therebetween becoming the maximum and the brightness changes
abruptly, or by determining more than three contour candidate points and
then calculating the center position of a circle passing the three points.
Then at step 201, X contour candidate points are presumed from the
characteristic point Po and the radius of the circle. For the sake of
convenience, raspective contour candidate points are represented by Pi
(i-1-n) (see FIG. 8c). Then at step 202, i is set to 1, and at step 203
several picture elements Ci including the contour candidate point Pi,
several picture elements Oi on the outside of the contour candidate point
Pi, and several picture elements Ii on the inner side of the contour
candidate point Pi are extracted (see FIGS. 8c, 8d and 8e).
The extraction should be made such that the three types of the picture
image data would be arranged in substantially normal direction with
respect to the loci of the contour candidate points. The direction of
.psi. of the normal is calculated by the following equation in accordance
with the relative position between the characteristic point Po (Xo, Yo)
and the contour candidate point Pi (Xi, Yi).
##EQU1##
The picture elements are extracted based on this direction .psi.. FIGS.
9a, 9b and 9c respectively show three picture elements Ci containing
contour candidate point Pi, three picture elements Oi on the outside of
the contour candidate point Pi and three picture elements Ii on the inside
of the contour candidate point Pi.
At step 204, the mean values Ci, Oi and Ii of the brightness of the three
types of the picture image data Ci, Oi and Ii are determined. After that
at step 205, a judgment is made as to whether i is equal to one or not and
when the result of judgment is YES, at step 206, i is made to be 2 to
execute again the foregoing steps. When the result of judgment of step 205
is NO, the program sequence is advanced to stop 207 where the differences
Sc, So and S.sub.I between the mean values Ci, Oi and Ii and Ci-1, Oi-1
and Ii-1 which are obtained at adjacent contour candidate points are
calculated according to the following equations.
Sc=C.sub.i -C.sub.i-1
So=O.sub.i -O.sub.i-1
S.sub.I =I.sub.i -I.sub.i-1 (2)
Then at step 208, a check is made as to whether the differences Sc, So and
S.sub.I thus calculated are included in the permissible range (from the
lower limit T.sub.L to the upper limit T.sub.H) preset as shown in FIG.
10. When these differences are on the outside of the permissible range, it
is judged that adjacent contour candidate points are discontinuous at step
211. However, when either one of the three differences lies in the
permissible range, at step 208, it is judged that adjacent contour
candidate points are continuous. More particularly, as shown in FIG. 8,
between C and D, there is a point at which the difference goes out of the
permissible range, but where either one of the other differences lies in
the permissible range, it is judged that adjacent contour candidate points
are continuous. Then, at step 209, i is incremented by one for the purpose
of checking whether the next adjacent contour candidate points are
continuous or discontinuous, thus executing again above described steps.
When the continuity of all contour candidate points is confirmed at step
210, the processing is terminated. In other word, it is now judged that
the contour line is continuous to identify the object.
The object to be detected is not limited to a circular body. The method of
this invention is applicable to judge whether a portion of the contour
line is continuous or not as shown in FIG. 11, provided that the contour
candidate points are presumed by certain experiments.
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Description |
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