JPS61141081A - Interesting area recognizer - Google Patents

Abstract

PURPOSE:To recognize an interesting area at a high speed by generating coordinate values and a moving vector of each pixel and recognizing all pixels in an area enclosed by a locus composed of points moving from a basic point. CONSTITUTION:A vector as a closed curve generated by a closed curve generating means 15 is inputted to the 1st arithmetic means 16 through the 1st vector storing memory 14. Coordinate values of each pixel in a locus composed of moving points from the basis point are calculated, and simultaneously the moving vector of each pixel is produced. After the output of the 1st arithmetic means 16 is re-arranged by the 2nd arithmetic means 18, it is inputted to the 3rd arithmetic means 20. It obtains an intersectional angle between a horizontal line and the moving vector of each pixel, and recognizes all pixels in an area enclosed by the locus of the basic point moving by discriminating it with the aid of said intersectional angle.

Description

[Detailed Description of the Invention] [Technical Field of the Invention] The present invention belongs to the technical field of image processing devices that process image data. Regarding recognition devices.

[Technical background of the invention and its problems] Figure 11 shows a block diagram of a conventional image processing device.For example, the image data DD transmitted from the ICT device is stored in the image memory 1 for one day. The image is displayed on the monitor 3 via the display interface 2. While viewing the image displayed on the monitor 3, the operator operates input means such as the tracker ball 4 to designate the ROI.

That is, for example, it is transmitted from the X-ray CT\MM main body.

The coordinates (xo, yo) of the base point (starting point of the ROI) are moved by the operation of the tracker ball 4, and the movement locus of this base point coordinate is temporarily stored in the R-01 memory 5 as a closed IROI and displayed. It is displayed on the monitor 3 via the interface 2. - On the other hand, in the region of interest recognition device 16, the tracker ball 4
II in the closed curve ROI based on the movement trajectory of the base point coordinates by
I is performed, and the recognition result is output to the statistical value calculation section 7. The statistical value calculation unit 7 that receives the recognition result within the open curve Rot calculates the statistical value within the area corresponding to the closed curve Rot of the image data DD, and the calculation result is displayed on the monitor via the display interface 2. 3.

Next, referring to FIG. 12, the region of interest recognition device!
6 will be explained in detail.

FIG. 12 is a diagram showing details of the region of interest recognition device in FIG. 11.

In the same figure, the ROI creation means 8 includes a tracker ball 4
R according to the movement trajectory of the base point coordinates (Xo, Vo) by
Create an OI closed curve pattern. Created ROI1
1 curve pattern is stored in Rot through R01 memory 9.
1 means 10. The ROI recognition means 10 performs a filling process within the Rot based on the transmitted Rot closed curve pattern, and the processing result is stored in the ROI memory 11.
It is output to the statistical value calculation section 7 via.

By the way, according to the above-described conventional region of interest recognition device 6, W1 recognition within the incline curve Rot is performed using an exploratory method using firmware. This is because a method is adopted in which eight directions are tested for all pixels within the closed curve Rot each time the pixel moves from a specific pixel to the next pixel, and the direction of movement is determined based on the test results.

Therefore, it takes time to recognize the closed curve ROI, and RO[
There is a problem in that it takes a long time from specification to obtaining statistical value calculation results.

[Object of the Invention] The present invention has been made in view of the above-mentioned circumstances, and its purpose is to provide an area of interest that can quickly recognize a region of interest set by an input means such as a tracker ball. An object of the present invention is to provide an area recognition device.

[Summary of the Invention] The outline of the present invention for achieving the above object is as follows: a first calculating means that calculates the coordinate value of each pixel in the locus of movement of the base point, and creates a movement vector for each pixel; A second calculation means rearranges the outputs of the first calculation means, and from the output of the second calculation means, the intersection angle between the movement vector and the horizontal line for each pixel is obtained, and from this intersection angle, the base point movement can be calculated. The device is characterized by comprising a third calculation means that processes all pixels within the region by determining whether it is inside or outside the region surrounded by the locus.1. Region of interest l! ! This is an attempt to increase knowledge and connect people.

[Embodiments of the invention] Hereinafter, the present invention will be specifically explained with reference to Examples.

FIG. 1 is a block diagram showing the configuration of a region of interest 211ml device which is an embodiment of the present invention, and 12 indicates the region of interest recognition device according to the present invention.

13 shows the output of the input means, for example, the tracker ball 4.
- An interface for importing the X component and Y component in the Y coordinate as vectors, 14 is a first vector storage memory that stores the output of this interface 13, and 15 is stored in this first vector storage memory 14. A closed curve creating means creates a closed curve by connecting the starting point and end point of the curve specified by the tracker ball 4 with a straight line based on the vector, and 16 is a closed curve created by the closed curve creating means 15. The vector is fetched via the first vector storage memory 14, and the coordinates of this fetched vector and the base point (
This is the first calculating means that calculates the coordinate value of each pixel in the trajectory of the base point movement based on the relationship between Xo, yo), and creates a movement and vector for each pixel. Further, 17 is a second vector storage memory for storing the output of the first calculation means 16, and 18 is a memory for arranging the stored contents of the second vector storage memory 17 in the matrix direction using X-Y coordinates. This is a second calculation means for changing (sorting). Furthermore, 19 is a third vector storage memory that stores the output of this second calculation means 18, and 20 is a moving coordinate for each pixel and a horizontal line based on the stored contents of this third vector storage memory 19. (A line parallel to the X-axis in the , a third operator that recognizes all pixels belonging to the region.

Reference numeral 21 denotes a Rot memory that stores the recognition result of the third calculation unit 20, and the stored contents of the Rot memory 21 serve as the output of the device of this embodiment, that is, the region of interest.
For example, statistical value calculation i! in J3 using the image processing device shown in FIG. 17, and subjected to image processing such as statistical value calculation.

Next, the operation of the embodiment apparatus having the above configuration will be explained based on the flowchart shown in FIG.

FIG. 2 is a diagram illustrating the operation of the apparatus of this embodiment. - It is.

The output of the tracker ball 4 is divided into an X component and a Y component in the XY coordinates via the interface 13, and all of these components are stored in the first vector storage memory 14. Here, the first vector storage memory 14
The stored contents are shown in FIG. The arrow belonging to Vy in the same figure means the Y component of the vector, and VxGL:f
The arrow pointing to i means the X component of the vector. Furthermore, movement in the positive direction of the X axis (increasing direction from the origin 0) is "+1".
, movement in the negative direction (direction decreasing from the origin) is "-1"
Also, movement in the positive direction of the Y axis is stored as "-1", movement in the negative direction is stored as "+1", and no movement is stored as "0".

If the ROI set by the operation of the tracker ball 4 does not form a closed curve, that is, the tracker ball 4
If the start point and end point of the curve input by the above do not match, the closed curve creation means 15 creates a closed curve by connecting the start point and end point of the curve with a straight line (step S1).

The created closed curve is as shown in FIG. 3(a), and is stored in the first vector storage memory 14 in the form as shown in FIG. 3(b). Note that st in FIG. 3(a) means the starting point of the curve.

Next, the first calculation means 16 calculates the storage contents of the first vector storage memory 14 and the coordinates of the base point (Xo, yo
), the coordinate value of each pixel in the trajectory of the base point movement is calculated, and a movement vector (front/tail vector) for each pixel is created (step 82).

Here, the coordinate value of each pixel in the trajectory of the base point movement can be obtained by executing the calculation according to the following equation.

X (0) =Xo...
(1)Y(0)=Vo...
・(2 (however, n#0) In the above formula, Xa, Va are the base point coordinates, X(n), Y
(n) is the coordinate of each pixel in the locus of movement of the base point.

In addition, to create a movement vector for each pixel in the trajectory of the base point movement, for example, as shown in Fig. 4(a), the vector (front) f coming out of each pixel in the trajectory of the base point movement and the vector (front) entering each pixel ( tail) t. That is, fx, vr
If y is the front vector, Vfx(n)=Vx(n) ・-[5]Vf
It is expressed as y(n)=Vy(n)・(61. However, O<n<(m-1), m is the total number of pixels in the trajectory of the base point movement.Then, the tail vector t is Since the value is the same as the front vector f of the previous pixel, create the front vector f and shift it by - to make the tail vector t. Therefore, Vfx (n + 1) = Vx (n) ・...(7))V
fy(n+1)=Vy(n) ・(8)
However, Q<n< (m-2), and Vfx(m)
=Vx (0) ・(9)Vfy(m)=Vy
(0) −(Denoted as D.

The movement vector created in this manner is stored in the second vector storage memory 17 in the form shown in FIG. 4(b) together with the coordinate values for each pixel on the locus of movement of the base point.

Note that depending on the shape of the leap curve, there may be vectors that are invalid in the determination by the third calculation means 20, which will be described later. For example, in FIG. 4(a), since the point indicated by ins has no meaning in the processing of the third calculation means 20, which will be described later, invalid points are detected and eliminated by the following procedure. Hereinafter, the procedure for searching for invalid points will be explained based on the flowchart in FIG.

To search for invalid points using the invalid point search algorithm,
The starting point of Wa must be at a corner.

Therefore, first, the pointer is advanced until the starting point reaches the corner (step 510).

Next, it is determined whether the front vector of the position pointed by the pointer is parallel to the X axis (step 51).
1). In this determination, if it is determined as YES, that is, if it is determined that the front vector of the position pointed by the pointer is parallel to the X axis, the current pointer and the point (pixel) pointed by the pointer are It is recognized as a point (step 512), the counter is incremented, and the pointer is advanced (step 513).

Then, it is determined whether the front of point a and the front of the point pointed to by the pointer are in the same direction (step 51
4). In this determination, if the determination is No, that is, if it is determined that they are not in the same direction, it is determined whether the tail vector of point a and the front vector pointed by the pointer are the same in the Y direction. (Step 5
15) If the determination is YES, the process returns to step S13.

If the determination in step S15 is 1, YES, that is, if it is determined that the tail vector of point a and the front vector pointed to by the pointer are the same in the Y direction, then the coordinates of point a are Determine whether it is smaller than the X coordinate of the pointed point (step 816)
. In this determination, if the determination is No, that is, if it is determined that the X coordinate of point a is not smaller than the X coordinate of the point pointed to by the pointer, point a is recognized as an invalid point (step 517); If the determination is YES, the point pointed by the pointer is recognized as an invalid point (step 818).

Then increment the canter and advance the pointer again. However, if the pointer becomes larger than the total number of vector points, the total number of vector points is subtracted from the pointer, and the result is used as the pointer (step 519). Also, if the determination in step S11 is NO, that is, if it is determined that the front vector of the position pointed by the pointer is not parallel to the X axis, and if the determination in step 815 is NO ,
That is, even if it is determined that the tail vector at point a and the front vector pointed to by the pointer are not the same in the Y direction, step 81.9 is executed.

After executing step S19, it is determined whether the count result of the counter is greater than the total number of vector points (step 520). In this determination, if it is determined to be YES, that is, if it is determined that the count result of the counter exceeds the number of vector points, the execution of this algorithm is terminated, and if it is determined to be NO, the step Returning to the determination in S11.

The invalid point a searched for by executing the algorithm described above is shown in FIGS. 6(a) and 6(b), for example.

In the movement vectors shown in (c) and (d), the points are respectively indicated by ins. Various methods can be considered for eliminating these invalid points, but here, the invalid points searched for by the first calculation means 16 are removed from the second is stored as a flag in the vector storage memory 17. In FIG. 4(b), the location where the ■oid flag is "1" means an invalid point, and this invalid point is ignored in the processing of the third calculation means 20, which will be described later.

Next, the second calculation means 18 rearranges (sorting) the contents of the second vector storage memory 17 (
Step S4). That is, the third calculation means 2 described later
The stored contents of the vector storage memory 17 are sorted in the matrix direction using the X and Y coordinates so that the process can be performed sequentially from left to right for each row. The results of the sorting process are stored in the third vector storage memory 19.
is memorized.

Next, the third calculation means 20 obtains the intersection angle between the movement vector and the horizontal line for each pixel based on the stored contents of the third vector storage memory 19, and uses this intersection angle to determine the intersection angle of the base point. By determining whether the area is inside or outside the area surrounded by the locus of movement, m* of all pixels in the area, that is, coloring processing is performed (step 85).

Here, the procedure of the filling process by the third calculation means 20 will be explained based on the flowchart of FIG. 7.

First, the value of the pointer is set to 0 (step 530). It is assumed that when the value of the pointer is O, it points to the beginning (front) of the vector in the table.

Next, it is determined whether the front and tail y-direction vectors of the point pointed to by the pointer are in opposite directions (step 531). N in this judgment.

If it is determined that the y-direction vectors of the front and tail are not opposite to each other, it is determined whether the point indicated by the 'pointer is registered as an invalid point or not (step 532). In this determination, if the determination is No, that is, if the Void flag is determined to be O, it is determined whether the front or tail direction of the point pointed to is upward or downward (step 533). . In this determination, if it is determined that the front or tail direction of the point pointed to by the pointer is downward, 1 is added to the number of times the vector crosses to the left (step 534), and If it is determined that the front or tail direction of the point is upward, 1 is added to the number of points that intersect the vector to the right (step 535). Then, subtract the number of times it crossed to the left from the number of times it crossed to the right, and determine whether the absolute value is greater than O (step 5).
36). Also, if the determination in steps 831 and 832 is YES, the determination in step 836 is performed. In this determination, if YES is determined, that is, if the absolute value of the subtraction result is determined to be greater than 0, the X coordinate of the point before the point pointed to by the pointer is set to x1, and the pointer's Let Y be the Y coordinate of the pointed point (step 537).

For example, in the case of closed curves as shown in Figures 8(a) and 9(a), either the left or right side should be inside the ROI, and the other should be outside the ROI. It is. As shown in FIG. 8(a), when the closed curves intersect, resulting in multiple Rots, the number of times the vector intersects from the left side or the right side is increased, as shown in FIG. 8(b). Said step 834.33
5), if the difference between the right and left is 0, it is outside of Rot, 5!
Understand. However, if the point of intersection is the previously determined invalid point, it is assumed that the point did not intersect, and the number of intersections remains unchanged. Also, at point 89 in FIG. 9(a),
Since the vector is parallel to the horizontal line and does not intersect, ;-
As shown in Figure (b), the previous state will be maintained as it is.

Next, set Xl and Y in step 837 to ROI
1 on the bit plane of memory 21 Step 8
38), set X1+1 to Xl again (step 539)
. □ Then, it is determined whether the X coordinate of the point pointed to by the pointer is greater than x1 (step 540). If this determination is NO, that is, if the X coordinate of the point pointed to by the pointer is smaller than x1, and if the determination in step 836 is NO, the pointer X, Y coordinates of the point you are pointing to
(step 841), (
X.

Y) is set to 1 (step 542).

Then, it is determined whether or not the total number of points has been repeated (step 843), and if YES is determined in this determination, that is, if it is determined that the total number of points has been repeated, the execution of this algorithm is terminated, and , if the determination is NO, the process returns to step S31.

The filling process is performed by executing the above algorithm, and a flag 1 is set in the Rot memory 21 for all pixels within the area surrounded by the locus of movement of the base point.

In addition, in this algorithm, the movement vector parallel to the horizontal line is the same as the state of its left end, so the trajectory of the base point movement may or may not be filled in, but this is due to the third The problem is solved by performing the coloring process once in the calculation means 20 and then filling the screen again.

Furthermore, by ignoring the invalid points searched by the first calculation means 16 in the filling process of the third calculation means 20, irregular ROIs as shown in FIGS. 10(a) and 10(b), for example, can be created. Even if it is, only the part not shown by diagonal lines can be filled in, and the area shown by 0LIT will not be filled in.

In this way, the device of this embodiment calculates the coordinate value of each pixel in the trajectory of the base point movement, creates a movement vector for each pixel, rearranges this, and then The system recognizes the area surrounded by the trajectory of the base point movement based on the angle of intersection with each movement vector, and does not recognize the area of interest in an exploratory manner in eight directions, unlike conventional devices. Therefore, the number of times of determining whether the region of interest is inside or outside the region of interest is greatly reduced, and the determination itself is simpler than the conventional force type, so that the region of interest can be recognized at high speed. For example, if the trajectory of the base point movement is a circle, according to the conventional method, it is 8xπr2x2, but in the case of the device of this embodiment, it is 2πr, resulting in a speed difference of 8r to 1. , in proportion to the radius r!
The am speed difference will widen.

Although one embodiment of the present invention has been described above, it goes without saying that the present invention is not limited to the above-mentioned embodiment, and can be modified as appropriate within the scope of the gist of the present invention.

[Effects of the Invention] As described in detail above, according to the present invention, it is possible to provide a region of interest recognition device that can quickly identify a region of interest set by an input means such as a tracker ball.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of a region of interest recognition device according to an embodiment of the present invention, FIG. 2 is a flowchart for explaining the operation of the embodiment device shown in FIG. 1, and FIGS. 3(a) and (b) 4(a) and 4(b) are explanatory diagrams showing examples of the storage contents of the first and second vector storage memories in FIG. 1, respectively, and FIG. 5 is an explanatory diagram showing an example of the storage contents of the first and second vector storage memories in FIG. Flowchart for explaining the action of FIG. 6(a),(b)
), (c), and (d) are explanatory diagrams showing invalid points, FIG. 7 is a noro chart for explaining the action of the third calculation means in FIG. ) and Figure 9(a)
,(b) and FIG. 10(a). (b) is an explanatory diagram for explaining the operation of the third calculation means, FIG. 11 is a block diagram showing an example of an image processing device, and FIG. 12 is a conventional example of the region of interest Wjtm@M in FIG. 11. FIG. 4-1-Racker ball (input means), 16--first calculation means, 18--second calculation means, 20--third calculation means. CG 'j (b) (d) Figure 8 (b) (b)

Claims (2)

[Claims] (1) In a region of interest recognition device that recognizes as a region of interest the area surrounded by the trajectory of the base point movement by operating the input means and performs image processing, the coordinate value of each pixel in the trajectory of the base point movement is calculated, and , a first calculation means for creating a movement vector for each pixel, a second calculation means for rearranging the outputs of the first calculation means, and a second calculation means for rearranging the outputs of the first calculation means.
The intersection angle between the movement vector and the horizontal line for each pixel is obtained from the output of the calculation means, and from this intersection angle, it is determined whether the area is inside or outside the area surrounded by the locus of the base point movement. A region of interest recognition device comprising: third calculation means for recognizing pixels. (2) The region of interest recognition device according to claim 1, wherein the first calculation means eliminates in advance movement vectors that are invalid in the determination made by the third calculation means.