JP2000231640A - Method and device for deciding boundary of article - Google Patents

Abstract

PROBLEM TO BE SOLVED: To trace the outline of the picture of an article which is image-picked up with a video camera at high speed with a small circuit scale by calculating a direction in which a picture element is connected next with the connected direction of the picture element positioned in the boundary of the article as a reference. SOLUTION: An eight nearby picture element extraction filter 10 outputs eight bit data on a picture element at the boundary of particles. An edge tracing part 12 traces only the picture element positioned at the boundary of the particles. An eight nearby picture element normalizing unit 28 rearranges the bit arrangement, of eight nearby picture element state values stored in an eight nearby picture element memory 11 with the value of an absolute direction register 26 as a reference. A first arithmetic and logic unit 24 executes a prescribed operation and outputs the relative connection direction value of a next boundary. An adder 25 adds the relative connection direction value and an absolute connection direction value stored in the register 26 and outputs a value as the absolute connection direction value of the next boundary. The register 26 outputs a connection code (chain code) 28 which the boundary of the particles shows.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an object boundary determination method and apparatus for tracing the outline of an object in an image, and more particularly, to a method for detecting particles such as blood cells and cells.
The present invention relates to a method and an apparatus for determining a boundary of an object which captures an image with a video camera or the like via a microscope, captures the captured image into an image memory, and determines a boundary of a particle region in the captured image by image processing.

[0002]

2. Description of the Related Art Generally, by knowing the shape of an object,
The characteristics and tendency of the object can be known. For example, it is possible to know the state of the body from the shape of blood cells and cells contained in blood and urine. For this reason, blood cells and cells (usually called “particles”) are imaged with a video camera or the like, and the shapes of the blood cells and cells are analyzed by image processing. In this analysis, features such as the perimeter and area of a particle are calculated by tracking the outline (also called an edge or a boundary) of the particle, and the shape of the particle is numerically determined. I try to figure it out.

[0003] As a method of analyzing by paying attention to the boundary of a certain region in an image, a conventional method and an apparatus for determining a boundary of an object described in Japanese Patent Publication No. 5-71991 or Japanese Patent Publication No. Sho 63-301372 have been known. "Image processing device"
Etc. are known.

In the method described in Japanese Patent Publication No. 5-71991, as shown in FIG. 27, image processing is performed by the following method to track the boundary of an object. Step 1: An image of an object such as a blood cell or a cell is captured, the captured image is A / D converted, and the luminance of each pixel is captured and stored in a frame (image) memory as a multi-valued image (gray scale). This is the first display.

Step 2: A threshold value for distinguishing the object from the background is set, and the multi-valued image is converted into a binary image according to the threshold value and stored in another frame memory. This is the second display.

Step 3: In a binary image, values of a pixel of interest and eight pixels adjacent in eight directions around the pixel of interest are extracted, converted by a look-up table, and stored in a separately prepared frame memory. This is the third display. As a result, only the pixels at the transposed part of the object have a non- “0” value, and the pixels inside and outside the object have a value of “0”.

Step 4: The third display image is raster-scanned to search for non-zero pixel values. Once a pixel with a non-zero value is found, the direction of the next pixel to be moved is determined by referring to the look-up table using the value and the direction of travel to reach that pixel as parameters.
Each time a pixel at the boundary is tracked, a third pixel corresponding to that pixel is tracked.
Clears the contents of the display memory to zero. While the contents of the next connected pixel in the memory of the third display are non-zero, the pixels at the boundary are tracked, and if the contents of the next connected pixel are zero, all the pixels at the boundary are tracked. Is deemed to have been tracked and the wake of the boundary is terminated. In this way, the boundaries of the object are tracked, and finally a chain code is obtained.

In the method described in Japanese Patent Application Laid-Open No. 63-301372, image processing is performed by the following method to track the boundaries of objects. The above steps 1 to 3 are almost the same as the method described in Japanese Patent Publication No. 5-71991, and when the direction of the previous pixel is k with respect to the pixel value of the third display obtained from step 3, k + 2 The chain direction is searched in the direction in which k increases from the eye digit (k is an odd number) or the digit of the (k + 3) th judgment (k is an even number). I try to track.

Conventionally, image processing is performed by such a method to track a boundary.

[0010]

However, the edge tracing method described in Japanese Patent Publication No. 5-71991 uses a lot of look-up tables, and the logic circuit is relatively large in scale. Since the PROM used for the table is relatively slow as a logic element, there has been a problem that it is difficult to increase the speed and cost of the boundary point tracking circuit.

The edge tracing method described in Japanese Patent Application Laid-Open No. 63-301372 has a problem in that several steps are required for searching for a tracing direction, and it is difficult to speed up the processing.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and is intended to enable high-speed, small-scale circuit tracking of the outline of an image of an object captured by a video camera via a microscope or the like. The present invention provides a method and apparatus for determining a boundary of an object.

[0013]

According to a method for determining a boundary of an object according to the present invention, the density information of each pixel of an image obtained by imaging the object is represented by 2%.
With respect to the binary image obtained by converting the value into a value signal and extracting the object region, each pixel located in the object region
In addition to converting to a neighboring pixel state value having a value corresponding to the value signal, the coordinates of the pixel located at the vertex of the object area are obtained, the pixel located at the coordinates is set as a starting point, and the above-described neighboring pixel state value is referred to. While calculating the relative connection direction value based on the connected direction of the pixels located at the boundary of the object, the absolute connection direction value of the next connected direction is calculated, and this is calculated for each pixel positioned at the boundary of the object. The feature is that the boundary of the object is tracked by repeating.

According to the present invention, when tracking the boundary of an object, the relative connection direction value based on the direction in which the pixels located at the vertex of the object area are connected to the starting point of the pixel located at the boundary of the object is used as a reference. By calculating the absolute connecting direction value of the next connecting direction, the tracking of the boundary of the image of the object can be performed faster and with a smaller circuit scale (compared to the conventional method using a lookup table). High integration).

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In an object boundary determination method according to the present invention, an image to be processed is obtained by imaging an object with a camera or the like. Any camera can be used as long as it can convert an image of a captured object into an electric signal and output the electric signal, and an ordinary video camera using a CCD (charge coupled device) can be applied.

As described above, when a normal video camera is applied as a camera, a captured image is obtained as an analog video signal obtained by scanning a plurality of pixels. Therefore,
The conversion of an analog video signal to a digital signal represented by a gray scale (multi-valued image), the conversion of a digital signal to a binary signal, the conversion of a binary signal to a neighboring pixel state value, and the calculation of a connection direction value CPU, ROM, RAM, I / O
The processing can be performed by an image processing device (image processor) including a microcomputer including a port.

In the above configuration, the absolute connecting direction value of the next connecting direction can be calculated by adding the relative connecting direction value to the absolute connecting direction value of the previously connected direction.

Further, the object boundary determining apparatus of the present invention comprises:
A binarization unit for converting density information of each pixel of the image of the object into a binary signal to extract an object region; and for the obtained binary image, the pixels located in the object region are surrounded by A pixel extracting unit that converts the pixel value into a neighboring pixel state value having a value corresponding to the binary signal, a coordinate extracting unit that obtains coordinates of a pixel located at a vertex of the object area, and coordinates obtained by the coordinate extracting unit. With the pixel located at the starting point as a starting point, the relative connected direction value based on the connected direction of the pixels located at the boundary of the object is determined by referring to the neighboring pixel state value converted by the pixel extracting unit, An edge tracing unit is provided which calculates an absolute connection direction value of the connection direction and repeats the calculation for each pixel located at the boundary to track the boundary of the object.

Hereinafter, the present invention will be described in detail based on an embodiment shown in the drawings. Note that the present invention is not limited to this.

FIG. 1 is a block diagram showing the configuration of an object boundary determining apparatus directly used for implementing the object boundary determining method of the present invention.

The apparatus for determining a boundary of an object includes a video camera 2 for imaging an object 1 to be measured, an image processor (image processing apparatus) 3, a microcomputer 4,
It comprises an RT display device 5 and an external storage device 6.

The image processor 3 includes a digitizer 7
, A comparator 8, a binary image holding memory 9, a pixel extraction unit (here, an 8-neighbor pixel extraction filter 10 and an 8-neighbor pixel memory 11), an edge trace unit 12, and a feature amount extraction unit 13. ing.

The object 1 to be measured is, for example, particles such as blood cells flowing through an imaging flow cytometer or cells mixed with urine. An imaging flow cytometer guides a sample solution (also called sample solution) diluted with blood or urine into a transparent tube called a flow cell to form a sample flow (also called sample flow). By irradiating pulsed light such as strobe light or pulsed laser light, the video camera captures particles (sometimes referred to as test particles) such as blood cells mixed with blood or cells mixed with urine. Although not shown in the present embodiment,
When an image of the object 1 is captured by the video camera 2, it is possible to capture an image by such a method.

The video camera 2 is a commercially available video camera, and captures an image of an object 1 such as blood cells and cells flowing through an imaging flow cytometer through a microscope. Such a video camera 2 has a large number of CCs corresponding to the number of pixels.
D is used as a photoelectric conversion element, and the video camera 2 photoelectrically converts the image of the object 1 by the CCD and outputs an analog video signal conforming to EIA.

The digitizer 7 A / D converts an analog video signal from the video camera 2. That is, the analog video signal is converted from the luminance (light intensity) of each pixel to, for example, 0 to 25.
The image data is converted into a multi-valued image (gray scale) represented by a digital 8-bit signal of 256 steps up to 5, and this is sequentially output in a raster scan (line sequential scan) manner. The values of the multi-valued image will be described later in detail.

The information output from the digitizer 7 in this manner can be said to be density information of each pixel of the target image, and this information is converted into a binarizing unit, an image extracting unit, a coordinate extracting unit, The boundary of the object is tracked by being processed by the edge tracing unit.

The binarizing section comprises, for example, a comparator 8 and a binary image holding memory 9. Comparator 8
Converts the grayscale digital signal for each pixel
The particles are sorted into binary levels with “1” and the background as “0”, and the binary signals are sequentially output in a raster scan format. That is, a luminance histogram of a target image such as a particle converted into a gray scale is analyzed in advance, and a threshold value at which the background and the particle are appropriately separated is obtained. Then, this threshold value is set in the comparator 8, and the particles are sorted into two values in which the particle is "1" and the background is "0". This sorting may be such that the particle is “0” and the background is “1”.

The binary image holding memory 9 is a memory for holding a binarized image of particles and a background, and stores binary information of a pixel of interest and eight pixels surrounding the pixel of interest (1 or 0). Information) is sequentially output in a raster scan format. 2
The storage contents of the value image holding memory 9 will be described later in detail.

The pixel extraction section is composed of, for example, an eight-neighbor pixel extraction filter 10 and an eight-neighbor pixel memory 11. 8
The neighboring pixel extraction filter 10 sequentially sets all pixels of the binary image as a pixel of interest, performs a logical operation on the binary values of eight neighboring pixels around the pixel of interest, and sets “0” for pixels inside and outside the particle. 8-bit data (1 byte, that is, 1 word data) having a value and a non-zero value for a pixel at the boundary of a particle is sequentially output in a raster scan format.

The 8-neighbor pixel memory 11 has two operation modes, an operation at the time of inputting an image and an operation at the time of edge tracing. Or the value of “8-bit data”) is sequentially input in a raster scan format. That is, the 8 neighboring pixel extraction filters 10 to 8 of the previous stage
Since the neighboring pixel state values are sequentially output in a raster scan format, the eight neighboring pixel state values are held in response to this. At the time of edge tracing, the next-stage edge tracing unit 12 outputs the 8-neighbor pixel state value held at the address specified along the boundary of the particle.

The edge tracing unit 12 traces (traces) the edge of a particle (also referred to as a boundary or an outline) in pixel units while referring to the contents of the 8-neighbor pixel memory 11, and generates a concatenated code (chain code) indicated by the particle boundary ) Is output. The tracing method will be described later in detail.

The characteristic amount extracting unit 13 obtains and outputs characteristic amounts such as the perimeter and area of the particle from the chain code represented by the boundary of the particle output from the edge trace unit 12 of the previous stage.

The microcomputer 4 controls each element of the image processor 3 appropriately. Further, feature amounts such as a perimeter and an area are temporarily stored for each particle, subjected to statistical processing, and output to the CRT display device 5. The CRT display device 5 displays the result of the statistical processing. A control program for determining a boundary of an object is executed on the main memory of the microcomputer 4.

In the present invention, an external storage device 6 may be provided. The external storage device 6 can store a program for controlling the microcomputer 4, that is, a program for controlling the object boundary determining device of the present invention by the microcomputer 4. Also,
The feature amount of the particles obtained by the image processor 3 and the result of the statistical processing can be stored.

The external storage device 6 may be a hard disk device for writing and reading data to and from a hard disk, a floppy disk device for writing and reading data to and from a floppy (registered trademark) disk, or may be connected through a line. The storage device may be a storage device shared with another device such as a file server. After the control program for determining the boundary of the object is loaded from the external storage device 6, it may be executed on the main memory of the microcomputer 4.

Next, the processing of the above-described 8-neighbor pixel extraction filter 10 will be described in detail. In the process of the 8-neighbor pixel extraction filter 10, the following logical operation is performed during the scanning time of one raster scan.

As shown in FIG. 2, the eight neighboring pixels n0, n1, and n are positioned counterclockwise from the three o'clock direction with respect to the center pixel of interest n8.
2, n3, n4, n5, n6, n7 are defined, and 8 neighboring pixel memories 1
The operation result a of the following logical expression is stored as 8-bit data at a position corresponding to one target pixel n8.

A = n8 & (n0♯n1♯n2 # n3 # n4 # n5 # n6 # n7) & nj (where # is a logical sum, & is a logical product,! Is negation, and nj is a binary display of “n7n6n5n4n3n2n1n0” Represent)

Specifically, n8 and (n0♯n1 # n2 # n3 # n4
♯n5♯n6 # n7) and nj's AND (logical product), and has the following meaning. The first term on the right-hand side indicates whether or not the pixel of interest is in the particle area, that is, the boundary or inside of the particle. The second term indicates whether or not there is a pixel that becomes “1” around the pixel of interest. The third term indicates the state of eight pixels around the target pixel.

That is, if the arrival pixel is "0", this is regarded as the background and a is set to "0" regardless of the value of the eight neighboring pixels.
And Even if the pixel of interest is “1”, if all eight neighboring pixels are “0”, this is regarded as dust instead of particles, and a is set to “0”.

After all, a pixel which does not become "0" under the above-described logical conditions is regarded as a pixel located at and inside the boundary of the particle. Therefore, only the background pixel has a value of “0”, and the pixels located at and inside the boundary of the particle have a =
It has a value of nj, that is, a non- "0" value. As described above, when the target pixel is located at the boundary or inside of the particle, the eight neighboring pixel state values (1 or 0) around the arrival pixel are set.
Is stored as 8-bit data at a position corresponding to the pixel of interest in the 8-neighbor pixel memory 11.

For example, eight neighboring pixels nj that combine the pixel of interest n8
(J = 0 to 7) If the binary state is as shown in FIG.
Becomes “n7n6n5n4n3n2n1n0”, that is, “11111000”,
The value of (11111000) B, that is, the value of 0x “F8” is stored in the 8-neighbor pixel memory 11 at the position corresponding to the target pixel n8. However, “() B” is a symbol indicating a binary number (binary code), and “0x” or “() H” is a symbol indicating a hexadecimal number (hex code).

In this way, the particles that fit into the image are extracted from the binarized image by the above-described method, and the state of the boundary between the particles and the surroundings of the pixels located inside are extracted by the eight neighboring pixels. By holding the state value, edge tracing is realized with a smaller circuit scale as described later.

In the above logical expression, the right side!
The term (n0 & n2 & n4 & n6) may be added to extract only the pixels located at the boundaries of the particles. That is, the logical expression is expressed as a = n8 & (n0♯n1♯n2 # n3 # n4♯n5♯n6♯n7) &! (N0
& N2 & n4 & n6) & nj, and n8, (n0♯n1 # n2♯n3♯n4 # n5 # n6♯n7),
! (N0 & n2 & n4 & n6) and nj (logical product) may be taken.

In this case,! (N0 & n2 & n4
& N6) condition can be added. That is, even if the pixel of interest is “1” and one of the eight neighboring pixels is “1”, the neighboring pixels in the clockwise direction of the three o'clock, twelve o'clock, nine o'clock, and six o'clock of the eight neighboring pixels are If the pixel is “1”, this can be regarded as inside the particle and a can be set to “0”.

Therefore, in this case, pixels that are not at the boundaries of the particles, that is, pixels inside and outside the particles have a value of “0”, and only the boundary pixels of the particles have the value of a = nj, that is, non- “0”. Will have the value of Thereby, only when the target pixel is located at the boundary of the particle, the eight neighboring pixel state values (binary 1 or 0) around the target pixel are set to the positions corresponding to the target pixel in the eight neighboring pixel memory 11. It will be held as 8-bit data.

In the next stage edge tracing unit 12,
Since only the pixel located at the boundary of the particle is traced, it does not matter whether the pixel inside the particle has an 8-neighbor pixel state value or is “0”, but the inside of the particle is “0”.
By giving the 8-neighbor pixel state value only to the pixels located at the boundaries of the particles, it is possible to prevent an error in the direction of connection at the time of edge tracing.

FIG. 4 is a block diagram showing a detailed configuration of the edge trace unit 12. As shown in FIG. As shown in the figure, the edge trace unit 12 includes an X address counter 21, a Y address counter 22, an 8-neighbor pixel normalizer 23, a first logical operator 24, an adder 25, an absolute direction register 26
And a second logical operation unit 27, and outputs a chain code 28 from the absolute direction register 26.

The X-address counter 21 and the Y-address counter 22 are up-down counters for designating which position data is to be read when reading data from the 8-neighbor pixel memory 11, and specify the coordinate value of the pixel to be read. Things. The X address counter 21 specifies a value in the X direction corresponding to the horizontal direction, and the Y address counter 22 specifies a value in the Y direction corresponding to the vertical direction. When tracing the boundary of a particle, an instruction is given from the X address counter 21 and the Y address counter 22, and the 8 neighboring pixel state value at the address of the next connected boundary pixel is read from the 8 neighboring pixel memory 11.

As described above, the eight-neighbor pixel memory 11 stores the output result of the eight-neighbor pixel extraction filter 10 corresponding to the previous stage in a raster scan manner at the time of image input, as described above.
It is stored as dimensional image data. After that, at the time of edge tracing, the 8-neighbor pixel state value of the address specified by the X address counter 21 and the Y address counter 22 is output.

The eight-neighbor pixel normalizer 23 rearranges the bit arrangement “n7n6n5n4n3n2n1n0” of the eight-neighbor pixel state value stored in the eight-neighbor pixel memory 11 with reference to the value of the absolute direction register 26. Output as a value. This sorting (normalization) method will be described later.

The first logical operation unit 24 converts the normalized neighboring pixel values output from the 8-neighbor pixel normalizer 23 into n0, n1, n2,
Assuming n3, n6, and n7, the following calculation is performed.

D2 = (! N0 &! N1 &! N2 &! N3) # n6 # n7; d1 = (! N0 &! N1 & n2) # (! N0 &! N1 & n3) # n6 # n
7; d0 = (! N0 &! N1 &! N6) # (! N0 &! N2 & n3 &! N6) ♯
(However, # indicates logical sum, & indicates logical product, and! Indicates negation.)

The value (d2d1d0) B of d2, d1, d0 obtained by this operation indicates the relative connection direction of the next boundary, and the first logical operator 24 calculates the values of d2, d1, d0. Output as relative connection direction value. Here, n4 and n5 are not combined on the right side of d2, d1, and d0, indicating that n4 and n5 are unnecessary data for calculating the relative connection direction value.

FIG. 5 shows (d2d1d)
0) The direction indicated by the binary number of B and the direction converted to a decimal number are shown. Since the directions connected from the pixel of interest are eight directions, the direction is indicated by a numerical value of 0 to 7 in the counterclockwise direction, with the direction of 3 o'clock of the clock being “0”. A numerical value indicating such a direction is called a connection code.

For example, if (d2d1d0) B is (011) B, the connecting direction is the direction of "3" and (d2d1d0) B is (0)
10) If B, the connection direction is the direction of “2”. However, the value output from the first logical operation unit 24 is a relative connection direction value based on the value of the absolute direction register 26.

The adder 25 adds the relative connection direction value output from the l-th logical operation unit 24 and the absolute connection direction value stored in the absolute direction register 26, and adds the absolute connection direction value at the next boundary. Output as direction value. The adder 25 is a 3-bit adder and takes only eight values from 000 to 111.

For example, (01
1) B = 3 is stored and obtained by the above logical expression (d
If (2d1d0) B is (010) B = 2, the output of the adder 25 is (011) B + (010) B = (101) B, and
The absolute connection direction value of the next boundary is the direction of “5”.

For example, if (101) B = 5 is stored in the absolute direction register 26 and (d2d1d0) B obtained by the above logical expression is (111) B = 7, the adder 2
Since the output of 5 is only 3 bits, (101) B +
(111) B = (100) B, and the absolute connection direction value of the next boundary is the direction of "4". Absolute direction register 26
Holds the absolute connection direction value of the next boundary output from the adder 25.

The chain code 28 is a data sequence output from the absolute direction register 26. Such a data sequence of the absolute connection direction value at the boundary is used as a chain code at the boundary of the particle, and the characteristic amount of the particle is determined in the next stage. calculate.

The second logical operation unit 27 instructs the X address counter 21 and the Y address counter 22 to increase or decrease as shown in FIG. 6 based on the absolute connection direction value at the next boundary. That is, if the absolute connection direction value is “0”, (X, Y) = (+ 1, 0) as the coordinate value, and if it is “1”, (+1,
+1) is (0, +1) for "2", (-1, +1) for "3", and (-1, 0) for "4".
, "5" indicates (-1, -1), "6" indicates (0, -1), and "7" indicates (+1, -1) as an increase / decrease value. I do.

Next, the processing of the 8-neighbor pixel normalizer 23 will be described in detail. That is, the process of rearranging the bit arrangement of the 8-neighbor pixel state value stored in the 8-neighbor pixel memory 11 with the direction of the previous concatenation as a starting point, normalizing the bit arrangement, and converting it into the next concatenated gorge will be specifically described.

As shown in FIGS. 7A to 7H, the relationship between eight neighboring pixels adjacent to the target pixel in eight directions around the target pixel is often symmetric four times, and in some cases, eight times. Become symmetric. For example, if the bit arrangement of the 8-neighbor pixel state value in FIG. 7A is shifted by one in the counterclockwise direction, the bit arrangement shown in FIG. 7B is obtained. Similarly, if FIG. 7B is shifted by one, FIG. 7C is shifted, FIG. 7C is shifted by one, FIG. 7D is shifted, and FIG. 7D is shifted by one. FIG.
7E is shifted by one to FIG. 7E, and FIG.
7 (f) is shifted by one, and FIG. 7 (g) is shifted, and FIG. 7 (g) is shifted by one, as shown in FIG. 7 (h).

As described above, in the examples of FIGS. 7A to 7H, the relationship between the eight neighboring pixels adjacent to the pixel of interest is eight-fold symmetrical. , It is possible to reduce the scale of the logic circuit necessary for calculating the next connection direction when performing edge tracing to 1/4 to 1/8 (the integration of 4 to 8 times is possible. is there).

In order to reduce the scale of such a logic circuit,
The 8-neighbor pixel normalizer 23 shifts the bit arrangement of the 8-neighbor pixel state value as follows. For example, assuming that the bit arrangement of the 8-neighboring pixel state value is the arrangement shown in FIG. 8, the direction in which the central blank portion is connected to the target pixel in the direction of “0”, that is, the previous connection code is “0” ", As shown in FIG. 9A, the bit arrangement of the 8-neighbor pixel state values is not shifted and is left as it is.

If the preceding connection code is "1", n0 to n are rotated counterclockwise from the direction of "1" with respect to the target pixel.
The bit value of 7 is extracted (see FIG. 9B). Similarly,
If the previous connection code is "2", the bit values of n0 to n7 are extracted counterclockwise from the direction of "2" with respect to the arrival pixel (see FIG. 9C), and the previous connection code is "3". ”, N0 from the direction of“ 3 ”counterclockwise with respect to the target pixel.
The bit values of n0 to n7 are extracted (see FIG. 9D). If the preceding concatenated code is "4", the bit values of n0 to n7 are extracted counterclockwise from the direction of "4" for the pixel of interest. (FIG. 9
(See (e)), if the previous connection code is "5", bit values n0 to n7 are extracted counterclockwise from the direction of "5" with respect to the pixel of interest (see FIG. 9 (f)). If the concatenation code is "6", the bit values of n0 to n7 are extracted counterclockwise from the direction of "6" with respect to the target pixel (see FIG. 9 (g)). If there is, the bit values of n0 to n7 are extracted counterclockwise from the direction of "7" with respect to the pixel of interest (see FIG. 9H).

For example, when the eight neighboring pixels of the destination pixel are binary as shown in FIG. 10, the eight neighboring pixel state values of the target pixel before normalization are as follows. That is,
Since n0, n1,..., N7 are applied in order in the counterclockwise direction from the 3 o'clock direction, (n7, n6, n5, n4, n3, n2, n1, n0) = (1, 1, 1, 0,
0,0,0,0).

In this 8-neighbor pixel state value, if the direction connected to the target pixel, that is, the previous connection direction is the direction of “3” (indicated by an arrow R in the drawing), the normal As shown in FIG. 11, the binarized neighborhood pixel value is based on the direction of “3” as viewed from the target pixel, and from there, n0, n1,... , (N7, n6, n5, n4, n3, n2, n1, n0) = (0, 0, 0, 1,
1, 1, 0, 0).

Similarly, when the eight neighboring pixels of the target pixel are binary as shown in FIG. 12, the eight neighboring pixel state values of the target pixel before normalization are as follows.

(N7, n6, n5, n4, n3, n2, n1, n0) = (1, 1, 0, 0,
0, 0, 0, 1) In this 8-neighbor pixel state value, if the previous connection direction is the direction of “4” (indicated by an arrow R in the drawing), the direction 4
As shown in FIG. 13, the normalized neighboring pixel values normalized as shown in FIG. 13 are (n7, n6, n5, n4, n3, n2, n1, n0) = (0, 0, 0, 1,.
1, 1, 0, 0).

As described above, by normalizing the connected directions, the eight neighboring pixel state values shown in FIG. 10 and the eight neighboring pixel state values shown in FIG. Although the two states differ, they have the same value, which indicates that the eight neighboring pixels are actually arranged in the same manner when viewed relatively. Therefore, by adopting the relative connecting direction in this way, the pattern of the connecting direction can be significantly reduced,
The size of the logic circuit of the first logic operation unit 24 in the next stage can be greatly reduced.

Next, the processing in the l-th logical operation unit 24 when data is received from the 8-neighbor pixel normalizer 23 will be described in detail.

FIG. 14 is an explanatory diagram showing the truth value of the logical operation in the first logical operation unit 24. The normalized adjacent pixel value output from the 8-neighbor pixel normalizer 23 and the The relationship with the output relative connection direction value is shown.

For example, the normalized neighboring pixel values output from the first logical operation unit 24 are (n7, n6, n5, n4,
If (n3, n2, n1, n0) = (0, 0, 0, 1, 1, 1, 0, 0), this is 0 × 1C, and the relative connection direction value is “2”.
(0, l, 0), which means that the connecting direction of the boundary turns 90 ° counterclockwise from the destination pixel.

As described above, the first logical operation unit 24 calculates the normalized neighboring pixel value n output from the 8-neighbor pixel normalizing unit 23.
The relative connection direction values d2, d1, and d0 are obtained from 0, n1, n2, n3, n6, and n7 by the above-described logical operation. However, since eight neighboring pixels are normalized, as shown in FIG. , The normalized neighboring pixel values are aggregated into 19 types of patterns, and the relative connection direction values are set in seven directions of 0, 1, 2, 3, 4, 6, and 7, which is a very simple logical crossing process.

The meaning of the relative connection direction values of 0 to 7 means the direction in which the boundaries are connected. That is, the direction 0 means turning in the same direction as the front connection direction, the direction 1 means turning in a direction of 45 ° counter to the front connection direction, and the direction 2 means the front connection direction. The direction 3 means turning in the direction of 90 ° in a counterclockwise direction, the direction 3 means turning in the direction of 135 ° in a counterclockwise direction with respect to the front connection direction, and the direction 4 means the front connection. 180 counterclockwise to the direction. The direction 6 means turning in a direction of 270 ° counterclockwise with respect to the front connecting direction, and the direction 7 means turning 315 ° in the counterclockwise direction with respect to the front connecting direction. Means to turn in the direction of.

For reference, the relative connection direction value
The output of d2, d1, and d0 does not have a value of “5”. This means that, as shown in FIGS. 15A and 16A, the vehicle makes a 225 ° turn with respect to the front connecting direction of the boundary.
When tracing the boundary of the object counterclockwise, FIG.
As shown in FIG. 16B and FIG. 16B, it is not possible to make a 225 ° turn, and therefore, the output of the relative connection direction value includes:
The value “5” does not exist.

The "3" direction, which is symmetrical to the "5" direction, means a 135 ° turn with respect to the boundary trace direction as shown in FIGS. 17 (a) and 17 (b). However, this transfer is possible.

For the transfer in the direction of “4”, 180
° direction, so it will return to the original direction,
If the particles are linear or rod-shaped, they can be shifted in this direction.

With the above-described logical operation, the edge trace unit 12 searches for the next pixel to be brought in next, and as long as the eight neighboring pixel state values of the searched pixel are valid (non-zero), the pixel is searched. Track and continue tracking the boundary until it matches the starting coordinates.

That is, the edge tracing unit 12 sets the starting point to the connection direction immediately before the pixel of interest as described above.
The neighboring pixel state values are rearranged and normalized, and the direction of the next connection is output not as an absolute angle but as a relative angle with respect to the previous transportation direction. The boundary can be tracked with a small logic scale, and therefore a logic circuit therefor can be easily integrated with a gate array or the like.

The operation of the object boundary determining apparatus having such a configuration will be described with reference to the flowchart shown in FIG. First, the microcomputer 4 captures, using the video camera 2, particles such as blood cells to be combined with blood and cells to be combined with urine. An analog video signal of the imaged particles is input to the image processor 3.

In the image processor 3, the digitizer 7
A / D-converts the analog video signal. FIG. 19 is an explanatory diagram showing an example of a grayscale image.
It shows the converted gray scale image of 65 levels from 0 to 64. The digitizer 7 sequentially outputs the data in a raster scan format.

Next, the grayscale image is sorted into binary levels by the comparator 8 and stored in the binary image holding memory 9. FIG. 20 is an explanatory diagram showing an example of the contents stored in the binary image holding memory 9, in which a grayscale image is binarized with a threshold value of "25".

Next, the 8-neighbor pixel extraction filter 10 performs a logical operation on the binary values of the eight neighbor pixels surrounding the pixel of interest to calculate an 8-neighbor pixel state value. I do.

FIG. 21 is an explanatory diagram showing an example of the storage contents of the 8-neighbor pixel memory 11 in which the background is "0" and the boundaries and inside of the particles are non- "0". Up to this point, the operation is performed at the time of image input, and thereafter, the operation is performed at the time of edge tracing.

At the time of edge tracing, the edge tracing unit 12 traces the edges of the particles in pixel units while referring to the contents of the 8-neighbor pixel memory 11, and outputs a concatenated code. Next, the characteristic amount extraction unit 13 obtains characteristic amounts such as the perimeter and area of the particle from the connection code.

Here, the processing operation at the time of edge tracing will be described in detail with reference to the flowchart of FIG. First,
It is necessary to determine the starting point of the edge trace. For this reason, the microcomputer 4 first accesses the 8-neighbor pixel memory 11 having the two-dimensional data in the order of the upper left to lower right direction raster scan as shown by the arrow T in FIG. A point (pixel) is searched for (step Sl). In FIG. 22, a point A having a value of (E0) H is searched.

Next, the coordinates of the point A having the value of (E0) H first found by the raster scan, that is, the X and Y addresses are set as the start address (Sx, Sy), and the values are set in the start address register and the X address. , Y address counters 21 and 22 (step S2). The start address register is an X, Y address counter 21,
22 is provided in advance.

Next, the X and Y address counters 21 and 22
The state of the eight neighboring pixels of the pixel of interest is read from the eight neighboring pixel memory 11 in accordance with the address shown in (1), and the concatenation code before the pixel of interest is predicted from the state of the eight neighboring pixels and set in the absolute direction register 26 (step S3). Note that the prediction of the previous concatenated code for the first pixel of interest is
Perform in the conventional manner.

In this conventional method, for example, the connection direction and the connection code are defined as shown in FIG. 5, and the state of the eight neighboring pixels of the pixel of interest obtained from the eight neighboring pixel memory 11 is (E
0) If H = (1,1,1,0,0,0,0,0) B, the state of the pixel in the vicinity of the target pixel is as shown in FIG. 23. As indicated by the arrow, the previous connection direction is predicted as the direction of “3”, and this value “3” is set in the absolute direction register 26.

Next, the 8-neighbor pixel normalizer 23 rearranges and normalizes the 8-neighbor pixels of the pixel of interest read from the 8-neighbor pixel memory 11 with reference to the value of the absolute direction register 26 (step S4). ).

For example, as shown in FIG. 24, when the state of the eight neighboring pixels is (E0) H = (1,1,1,0,0,0,0,0) B, the absolute direction register 26 When rearranged starting from the direction of the value “3” of (3), (0,0,0,1,1,1,0,0) B
Becomes Note that this rearrangement process can be easily realized by providing a conventionally known multiplexer.

Next, the normalized neighboring pixel value output from the 8-neighbor pixel normalizer 23 is input to the first logical operator 24 to obtain a relative connection direction value as shown in FIG. 14 (step S5). ).

For example, (n7, n6, n5, n4. N3, n2, n1, n
0) as (0,0,0,1,1,1,0,0) B, ie 0x1C
Is input, the output (d2, d1, d0) becomes (0, 1, 0). In other words, the relative connection direction value of the next connected boundary is the direction of “2” (10 decimal).

Next, the value of the absolute direction register 26 and the relative connection direction value output from the first logical operation unit 24 are added to the adder 2.
5, and the value is stored in the absolute direction register 26 as the absolute connecting direction value of the next boundary (step S).
6). Since the adder 25 is a 3-bit adder, when the concatenated code is "8" or more in decimal, the remainder of 8 becomes the absolute concatenated direction value.

For example, if the value of the absolute direction register 26 is "3" and the relative connection direction value output from the adder 25 is "2", then 3 + 2 = 5, and the absolute connection direction value of the next boundary is obtained. Becomes “5”. This value is set in the absolute direction register 26 at the next clock.

As described above, the absolute connection code at the next boundary is the difference (relative value) between the absolute connection code at the previous boundary and the absolute connection code at the next boundary.
Is added.

Next, the absolute connection direction value stored in the absolute direction register 26 is converted by the second logic circuit 27 into an increase / decrease value as shown in FIG. 22 (step S7).

For example, if the value of the absolute direction register 26 is "5" as described above, the increase and decrease values of X and Y are (-
1, -1), and this value is stored in the X, Y address counter 2
Instruct 1 and 22. Thus, the tracking of the boundary is performed as shown in FIG.
As shown by the arrow 5, since the vehicle moves in the direction of the relative connection direction value "2", the next boundary pixel is a point B having a value of (E3) H.

Next, the start address (Sx, Sy) at which the tracking of the boundaries of the particles is started, which is stored in the start address register, and Y address counters 21 and 22
(Step S8).

Here, the X, Y address counter 21.2
If the address indicated by 2 is different from the start address (Sx, Sy), the process returns to step S4, and steps S4 to S8 are repeated by the number of boundary pixels.

Here, the X, Y address counter 2
The addresses indicated by 1 and 22 are the start addresses (Sx, Sx
If y) coincides with each other, as shown in FIG. 26, it means that the particle has made one round, and the edge tracing is stopped. The data sequence of the value of the absolute direction register 26 from the start to the end of the edge trace indicates a chain code representing the boundary of the particle.

As described above, focusing on the symmetry based on the boundary tracking direction in the eight neighboring pixel state values and rearranging the eight neighboring pixel state values on the basis of the immediately preceding chain code, a minimum The next chain direction can be calculated by the parameter (6 bits), and as a result, a chain code can be generated only by a simple logical operation and an adder. In addition, since the boundary can be tracked only by such a simple logical operation and a random logic, a high degree of integration of the image processor (more than four times integration), Significant speed-up of image processing (boundary tracking capability of 5 million pixels / second or more) is possible. These were realized by a relatively small capacity (several thousand gates) FPGA (field programmable gate array).

By the way, in the present invention, as shown in FIG. 2, a coordinate extracting unit (here, represented by a vertex coordinate detecting unit 14 and a vertex coordinate holding memory 15) is provided so that the start point of the edge trace is detected. Is preferred. This will be described below. In the coordinate extraction unit, for example, a pixel on the boundary of a particle has a value of “1”,
If 1-bit data having a value of "0" can be obtained for other pixels, the coordinates of the pixel when the value is "1" can be known. This coordinate information is referred to at the time of edge tracing by the edge tracing unit 12, and is effectively used as a starting point of the edge tracing, which contributes to further speeding up of processing and integration of circuits.

When the 8-neighbor pixel extraction filter 10 performs a logical operation on the eight neighboring pixels around each pixel of interest, the vertex coordinate detection unit 14 performs another logical operation on the pixel of interest. That is, the following particle edge detection flag TIP is calculated for each pixel of interest n8. n0, n1, n2, n3, n4, n
5, n6, n7, and n8 are assumed to be in accordance with FIG. n8 is a pixel of interest. TIP = n8 &! n1 &! n2 &! n3 &! n4 & (n0♯n5♯n6 # n
7)

The value of the flag TIP is such that n8 is "1", n1, n2, n3, and n4 are all "0" and n0, n5, n
When either of 6 and n7 is “1”, it becomes “1”,
At this time, the target pixel n8 is located at the upper right, upper,
Do not connect to the upper left or left side pixel, lower left, lower,
The pixel is connected to either the lower right pixel or the right pixel. That is, the pixel is located at the upper left corner of the particle area. In the case of the binary image in FIG. 20, the flag TIP is “1” for the third pixel from the top and the seventh pixel from the left (this is point A in FIG. 22), and “0” for the other pixels. ".

In this way, the vertex coordinate detecting section 14 detects the coordinates (Sx, Sy) of the pixel of interest when the flag TIP becomes "1". These coordinates are stored in the vertex coordinate holding memory 15.

The processing operation at the time of edge tracing will be described with reference to FIG. In the previous embodiment, the coordinates of the non-zero value are found by accessing the 8-neighbor pixel memory in a raster scan manner and searching for a point having a non-zero value (step S1). The vertex coordinates (Sx, Sy) output from the vertex coordinate holding memory 15 are set in the start address register and the X, Y address counters 21 and 22 without performing the processing, so that the edge tracing is performed. Simplifies and speeds up the processing. The processing performed thereafter, that is, the 8-neighbor pixel memory 1
The process of tracing (tracing) the edge of a particle (also referred to as a boundary or contour) in pixel units while referring to the contents of 1 and outputting a concatenated code (chain code) represented by the boundary of the particle is the same.

[0110]

According to the present invention, when tracking the boundary of an object imaged by a video camera or the like, a pixel located at the vertex of the object area is set as a starting point, and a direction in which the pixels located at the boundary of the object are connected is used as a reference. The absolute connecting direction value of the next connecting direction is calculated by calculating the relative connecting direction value, which makes it possible to reduce the regulation of the logic circuit compared to the conventional one and easily integrate it in a gate array etc. It is possible to do. This also allows for rapid border tracking.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of an object boundary determination device according to the present invention.

FIG. 2 is an explanatory diagram showing the definition of eight neighboring pixels for a pixel of interest.

FIG. 3 is an explanatory diagram showing an example of a binary state of eight neighboring pixels including a target pixel.

FIG. 4 is a block diagram illustrating a detailed configuration of an edge trace unit.

FIG. 5 is an explanatory diagram showing connection directions.

FIG. 6 is an explanatory diagram showing a relationship between a connection direction and an increase / decrease value of an X, Y address counter.

FIG. 7 is an explanatory diagram showing the symmetry of eight neighboring pixels with respect to a target pixel.

FIG. 8 is an explanatory diagram showing a bit arrangement of an 8-neighbor pixel state value.

FIG. 9 is an explanatory diagram showing a state in which an 8-neighbor pixel state value is shifted.

FIG. 10 is an explanatory diagram showing an example of 8-neighbor pixel state values before normalization.

FIG. 11 is an explanatory diagram showing an example of an 8-neighbor pixel state value before normalization.

FIG. 12 is an explanatory diagram showing an example of 8-neighbor pixel state values before normalization.

FIG. 13 is an explanatory diagram showing an example of 8-neighbor pixel state values before normalization.

FIG. 14 is an explanatory diagram showing truth values of a logical operation in a first logical operation unit.

FIG. 15 is an explanatory diagram showing an example in which the vehicle makes a 225 ° turn with respect to the front connection direction of the boundary.

FIG. 16 is an explanatory diagram showing an example in which the vehicle makes a 225 ° turn with respect to the front connecting direction of the boundary.

FIG. 17 is an explanatory diagram showing an example in which the vehicle makes a 135 ° turn with respect to the front connection direction of the boundary.

FIG. 18 is a flowchart showing a processing operation at the time of edge tracing.

FIG. 19 is an explanatory diagram illustrating an example of a grayscale image.

FIG. 20 is an explanatory diagram illustrating an example of storage contents of a binary image holding memory.

FIG. 21 is an explanatory diagram showing an example of the storage contents of an 8-neighbor pixel memory.

FIG. 22 is an explanatory diagram showing a state of a raster scan of an 8-neighbor pixel memory.

FIG. 23 is an explanatory diagram showing eight neighboring pixel state values where the pixel of interest is (E0) H.

FIG. 24 is an explanatory diagram showing a bit arrangement in a case where the pixel of interest rearranges eight neighboring pixel state values of (E0) H.

FIG. 25 is an explanatory diagram showing a tracking state of a boundary in the 8-neighbor pixel memory.

FIG. 26 is an explanatory diagram showing a state in which edge tracing is completed after making a round around the boundary of a particle.

FIG. 27 is a block diagram illustrating a conventional method of tracking the boundary of an object.

[Description of sign]

 DESCRIPTION OF SYMBOLS 1 Object 2 Video camera 4 Microcomputer 5 CRT display device 6 External storage device 7 Digitizer 8 Comparator 9 Binary image holding memory 10 8 Neighboring pixel extraction filter 11 8 Neighboring pixel memory 12 Edge trace part 13 Feature extraction part 14 Vertex coordinate detection Unit 15 vertex coordinate holding memory 21 X address counter 22 Y address counter 23 8 neighborhood pixel normalizer 24 first logical operator 25 adder 26 absolute direction register 27 second logical operator 28 chain code

Claims (2)

[Claims] 1. A binary image obtained by converting density information of each pixel of an image obtained by capturing an object into a binary signal and extracting an object region, for each pixel located in the object region, each of the pixels is located in a surrounding binary signal. In addition to converting to a neighboring pixel state value having a value corresponding to, the coordinates of the pixel located at the vertex of the object area are obtained, the pixel located at that coordinate is set as the starting point, and the object is referred to with reference to the neighboring pixel state value. Calculate the absolute connection direction value of the next connected direction by calculating the relative connection direction value based on the connected direction of the pixels located at the boundary of, and repeat this for each pixel located at the boundary of the object A method for determining the boundary of an object by tracking the boundary of the object. 2. A binarizing unit for converting density information of each pixel of an image of an object into a binary signal to extract an object region, and for a pixel located in the object region with respect to the obtained binary image. A pixel extracting unit for converting each pixel into a neighboring pixel state value having a value corresponding to a surrounding binary signal, a coordinate extracting unit for obtaining coordinates of a pixel located at a vertex of the object area, Starting from the pixel located at the coordinates obtained in
The absolute connecting direction value of the next connecting direction is obtained by calculating the relative connecting direction value based on the connecting direction of the pixels located at the boundary of the object while referring to the neighboring pixel state value converted by the pixel extracting unit. And an edge tracing unit that tracks the boundary of the object by repeating this for each pixel located at the boundary.