JP2008298706A - Shape determination method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a shape determination method capable of determining bacteria accurately, even when two bacteria are in contact with each other, and when fluorescence-labeled bacteria are bent. <P>SOLUTION: A shape of an inspected object is determined from the thickness average value, thickness variation degree, and length of the inspected object, by extracting a region of the inspected object for determining a shape from an image photographed (S102), computing a contour of the inspected object (S103), calculating the center line of the inspected object (S104), detecting a bent part of the inspected object from a shape of the center line (S107), calculating the thickness of the inspected object in a region except for the bent part from the contour calculated in the contour calculation process (S109), calculating the thickness average value (S111), calculating the thickness variation degree (S114), and calculating the length of the inspected object from the length of the center line (S116). <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a shape determination method, and more particularly to a method for determining bacteria from shapes such as length and thickness of a test object.

  Conventionally, a fluorescence method is generally used as a method for testing acid-fast bacteria. The fluorescence method is a method in which a part of a specimen such as sputum is collected, smeared directly on a slide glass, dried, heat-fixed and fluorescently stained, and an observer searches for the presence of acid-fast bacteria under a microscope. In recent years, in order to maintain the accuracy of the test even if the acid-fast bacteria are not distributed in the cocoon, instead of smearing directly on the slide glass, the centrifuge collection material that equalizes the cocoon with a centrifuge A method of collecting bacteria is mainly used, which is smeared on a slide glass and observed.

  Fluorine staining is typically auramine staining, and staining is performed by staining with auramine, decolorizing with hydrochloric acid alcohol, and then post-staining with methylene blue liquor. By irradiating with ultraviolet rays after dyeing, the acid-fast bacterium emits fluorescence, and an observer observes the state of shining orange using a microscope for inspection. In the fluorescent method, in addition to acid-fast bacteria, dust and the like may be shining orange, so it is necessary for the observer to determine whether or not it is acid-fast bacteria by looking at the shape.

  Also, a method has been proposed in which each field of view is automatically photographed using a photographing means such as a camera instead of being observed by an observer, and acid-fast bacteria are automatically detected from the photographed image (for example, Patent Documents). 1). In this method, whether or not it is an acid-fast bacterium is determined based on the area and aspect ratio of the test object.

However, when processing with a centrifuge is performed by the method of collecting bacteria, which is becoming the mainstream of inspection, bacteria may be bent, and thus it is necessary to determine the shape in consideration of bending. The following method is known as a method for measuring the thickness of a long object with a bend (see, for example, Patent Document 2). In this method, an image of a long target object is taken, the longitudinal direction of the contour of the target and the circumscribed rectangle is calculated, and the distance between the straight line and the contour that equally divides the circumscribed rectangle at one side in the longitudinal direction is The minimum point on the contour is calculated, and the average of the calculated distances is calculated as the thickness.
JP 2004-333151 A JP-A-11-194014

  However, the conventional method has a problem in that it cannot be determined as bacteria because bacteria cannot be recognized when bacteria are in contact with each other or when the bending of bacteria is extremely large. It was.

  The present invention solves the above-mentioned conventional problems, and is a shape for determining the shape of an inspection object so that it can be determined as bacteria even when the bacteria are bent or when the bacteria are in contact with each other. An object is to provide a determination method.

  In order to solve the above-described conventional problems, the shape determination method of the present invention includes a region extraction step of extracting a region of an inspection target for which shape determination is performed from a captured image, and contour calculation for calculating the contour of the inspection target. A center line calculating step of calculating a center line of the inspection object, a bent portion detecting step of detecting a bent portion of the inspection object from the shape of the center line, and the inspection of the region excluding the bent portion A thickness calculating step for calculating the thickness of the object from the contour calculated in the contour calculating step, a thickness average value calculating step for calculating an average value of the thicknesses, and a degree of variation in the thickness. A thickness variation degree calculating step, a length calculating step of calculating a length of the inspection object from the length of the center line, the thickness average value, the thickness variation degree, and the inspection object The length of the test pair It is characterized in that includes determining the shape determination step the shape of the object.

  Further, in the shape determination method, in the shape determination step, when the thickness average value and the thickness variation degree are predetermined values, and the length of the inspection target is a predetermined value, the inspection target is It is characterized by determining that it is bacteria.

  Furthermore, the shape determination method further includes a length average value calculating step of calculating an average value of the length of bacteria, and in the shape determination step, a bent portion is detected in the bent portion detection step, and the thickness average value When the thickness variation degree is a predetermined value and the length of the test object is about twice the length average value calculated in the length average value calculation step, two bacteria are in contact with each other. It is characterized by determining the shape as a thing.

  Further, in the shape determination method, an inspection region extraction step of extracting a region of the inspection target for which shape determination is performed from the captured image, a center line calculation step of calculating a center line of the inspection target, and an outline of the inspection target The contour calculation step for calculating the contact, the contact detection step for detecting the contact of the object from the shape of the center line, and when the contact is detected in the contact detection step, Separation step for separating into regions, thickness calculation step for calculating the thickness of the inspection object from the contour calculated in the contour calculation step, and length calculation for calculating the length of the inspection object from the center line A thickness average value calculating step for calculating an average value of the thickness, a thickness variation degree calculating step for calculating the thickness variation degree, the average value of the thickness, and the thickness Variation degree and the above Shape determination method comprising determining the shape determination step the shape of the test object from the length of 査 object.

  Further, in the shape determination method, in the shape determination step, when the thickness average value and the thickness variation degree are predetermined values, and the length of the inspection target is a predetermined value, the inspection target is It is characterized by determining that it is bacteria.

  Furthermore, in the shape determination method, the thickness variation degree is calculated based on a standard deviation of the thickness in the thickness variation degree calculation step.

  Furthermore, in the shape determination method, the thickness variation degree calculation step calculates the thickness variation degree by a difference between a maximum value and a minimum value of the thickness.

  According to the shape determination method of the present invention, bacteria can be detected by determining the shape of the inspection object even when the inspection objects overlap or are extremely bent.

  Embodiments of the shape determination method of the present invention will be described below in detail with reference to the drawings.

(Embodiment 1)
FIG. 1 is a block diagram of a shape inspection apparatus as a premise of a shape determination method according to Embodiment 1 of the present invention. In FIG. 1, a plate 105 is obtained by smearing an inspection object. The optical means 101 irradiates the plate 105 with excitation light, and the optical means 101 captures the fluorescence emitted when the inspection object on the plate 105 is excited and guides it to the imaging means 102. The imaging unit 102 shoots the area under fluorescence observation, generates an image, and outputs the image to the image processing unit 103. The image processing means 103 detects bacteria from the photographed image and outputs the detection result to the display means 104. The display means 104 displays the detection result.

  First, the plate 105 will be described in detail. The plate 105 uses a slide glass, and is coated with a sample that has been dried, heat-fixed, and fluorescently stained. Examples of the specimen include human sputum and stool. Note that any plate such as a petri dish may be adopted as the plate 105.

  Next, the optical means 101 will be described in detail. An example when a fluorescence microscope is used as the optical means 101 is shown in FIG. The light source 201 is for irradiating the inspection object with excitation light, and uses a mercury lamp or the like to irradiate light including ultraviolet rays. The light source light 202 from the light source 201 passes through the excitation filter 203. The excitation filter 203 transmits light having a wavelength necessary for the bacteria to fluoresce (hereinafter referred to as excitation light 204) and shields unnecessary light. Next, the excitation light 204 is guided to the objective lens 206 by the dichroic mirror 205 and irradiated onto the plate 105 via the objective lens 206. The dichroic mirror 205 is installed at an angle of 45 degrees with respect to the light source light 202 and reflects only a specific wavelength. Bacteria in the specimen are excited by the irradiated excitation light 204 and emit fluorescence 207, which passes through the absorption filter 208 via the objective lens 206 and guides the fluorescence 207 to the imaging means 102. The absorption filter 208 transmits the fluorescence 207 and blocks light 209 other than the fluorescence 207 such as reflected excitation light 204 and external light. Note that any optical means 101 such as a micrometer capable of fluorescence observation may be employed as the optical means 101.

  Next, the imaging unit 102 will be described in detail. The imaging unit 102 uses a monochrome CCD camera, and is joined to a fluorescence microscope as the optical unit 101 by a C mount. The fluorescence 207 from the specimen guided by the optical means 101 is photographed by a CCD camera, and the photographed image is output to the image processing means 103. Note that any imaging unit 102 such as a color CCD camera may be employed as the imaging unit 102.

  Next, the configuration of the image processing means 103 will be described in detail with reference to FIGS. FIG. 3 is a flowchart showing each step in the shape determination method performed by the image processing means 103.

  First, in step S101, the captured image is binarized. In the photographed image, since the inspection object emits fluorescence, the luminance value of the inspection object is higher than the luminance value of the pixels in the background portion. Therefore, binarization is performed by setting 1 if the luminance value of the pixel of interest is higher than the threshold value and setting it to 0 otherwise. As a method of determining the threshold value, for example, an average value of luminance values of an area that is previously determined by the observer as bacteria is calculated, and an average value of luminance values of the background is also measured, and an intermediate value thereof is set as the threshold value. Also good. FIG. 5 is a diagram obtained by binarizing a photographed image. The hatched area is an area that is set to 1 by binarization, and the other areas are 0 areas.

  Next, step S102 is an inspection region extraction step, and an inspection region is extracted using the binarized image calculated in the binarization step of step S101. The inspection area is extracted by labeling areas determined to be 1 for all pixels of the binarized image. Labeling is an operation in which if the value of the pixel of interest is 1, if there is a value of 1 in the vicinity of the surrounding 8, that pixel is identified as the same region as the region of the pixel of interest, and the same region is numbered. This operation is performed until all the pixels in the inspection area are labeled. FIG. 6 shows the result of labeling, and the same area is numbered from 601 to 606.

  Next, step S103 is a contour extraction step, in which a contour is extracted for the inspection region calculated in step S102. FIG. 7 shows the contour extraction result of the inspection region 601 in FIG. 6 calculated in step S102, and the contour 701 is extracted. Although there are various methods for calculating the contour, the contour 701 can be extracted by using a known contour extraction filter such as a Laplacian filter.

  Next, step S104 is a center line calculation step, and a center line is calculated for the examination region calculated in step S102. There are various methods for calculating the center line. For example, the center line can be calculated by using a well-known thinning method such as the Holditch method. In the thinning process, a process for narrowing the inspection area to line width 1 is performed, and a center line passing through the center of the inspection area 601 can be calculated as indicated by reference numeral 801 in FIG.

  Next, step S105 is a thickness calculation point selection step, and a location for calculating the thickness is selected as a thickness calculation point from a point on the center line 801. The thickness of the inspection object at the thickness calculation point is calculated in a subsequent process. In FIG. 8, 802, 803, and 804 are thickness calculation points. The thickness calculation point is determined by sequentially selecting points from end to end on the center line 801. However, as will be described later, since a bending amount calculation point is provided before and after the thickness calculation point, as in 802 A point that is a certain distance away from the end of the center line is selected as a thickness calculation point, and points on the center line to a point 804 that is a certain distance away from the end of the center line 801 are selected while sequentially moving the thickness calculation points.

  Next, step S106 is a bending amount calculation point setting step, and two bending amount calculation points for calculating the bending amount are set. FIG. 8 shows an example of a bending amount calculation point. In FIG. 8, 802 a and 802 b are bending amount calculation points for calculating the bending amount at the thickness calculation point 802, and are positioned on opposite sides of each other at equal distances around the thickness calculation point 802 on the center line 801. It is set to be. Similarly, bending amount calculation points 803a and 803b are set around the thickness calculation point 803. In this case, the distance from the bending amount calculation point 803a to the other bending amount calculation point 803b is preferably about the thickness of the inspection object. For example, when detecting acid-fast bacteria, the thickness of the acid-fast bacteria is 0.3 μm to 0.6 μm as the distance from the bending amount calculation point to the other bending amount calculation point.

  Next, step S107 is a bending amount calculation step, and the bending amount of the inspection object at the thickness calculation point selected in the thickness calculation point selection step of step S105 is calculated. The bending amount is calculated by an angle formed by the bending amount calculation point set in the bending amount calculation point setting step in step S106 and the thickness calculation point. Specifically, when a straight line is drawn from two bending amount calculation points to a thickness calculation point, the angle formed by the two straight lines on the thickness calculation point is defined as the bending amount. For example, in FIG. 8, the bending amount at the thickness calculation point 802 is an angle θ1 formed by the thickness calculation point 802 and the bending amount calculation points 802a and 802b, and the bending amount at the thickness calculation point 803 is the thickness calculation. It is represented by an angle θ2 formed by the point 803 and the bending amount calculation points 803a and 803b.

  Next, step S108 is a step of determining whether or not the portion is a bent portion. If the angle calculated in step S107 is smaller than a predetermined value, it is determined that the portion is a bent portion of the inspection object. For example, in FIG. 8, the amount of bending at the thickness calculation point 802 is about 180 degrees, and it is determined that the portion is not a bent portion. Further, the amount of bending at the thickness calculation point 803 is about 60 degrees, and it is determined that it is a bent portion. For example, if the angle is smaller than 120 degrees, it is determined that the portion is a bent portion. If it is determined that it is a bent portion, the process proceeds to step S110, and the thickness is not measured at the thickness calculation point. As shown in FIG. 14, in the bent portion, when the thickness calculation point is not at the bend corner of the center line 801 but at a place close to the bend corner, the thickness calculation point 1401 and the bend amount calculation points 1401a and 1401b are formed. Since the angle θ3 is about 100 degrees and is smaller than 120 degrees, it is determined to be a bent portion. As described above, since the angle becomes small in the vicinity of the corner, it is determined that the portion is a corner.

  If it is determined that the portion is not a bent portion, the process proceeds to the thickness calculation step in step S109, and the thickness is measured at the thickness calculation point. In FIG. 8, the thickness is measured at the thickness calculation point 802, and the thickness is not measured at the thickness calculation point 803. As a result, thickness measurement is not performed at the bent portion in FIG. 8, so that erroneous thickness measurement can be prevented.

  Next, step S109 is a thickness calculating step. When it is determined in step S108 that the portion is not a bent portion, the thickness of the place is calculated. A method for calculating the thickness will be described with reference to FIG. In FIG. 9, a thickness calculation point 802 on the center line 801 is a point determined not to be a bent portion, and the thickness at this point is calculated. For this purpose, the line 901 having the minimum length of the line segment cut by the contour 701 among the straight lines passing through the thickness calculation point 802 is set as the thickness 901 of the inspection object.

  Each step from the thickness calculation point selection step in step S105 to the thickness calculation step in step S109 is performed while sequentially selecting the thickness calculation points on the center line, and the process proceeds to step S110 until there are no selection points for the thickness calculation points. And repeat.

  Next, step S111 is a thickness average value calculation step, and the average value of the thicknesses calculated in the thickness calculation step of step S109 is calculated.

  Next, step S112 is a step of determining whether or not the average thickness value is within a predetermined value range. As the predetermined value for determination, a range of 0.3 μm to 0.6 μm which is the thickness of the acid-fast bacterium is set as the predetermined value. If the average thickness is not a predetermined value, the process proceeds to step S113, where it is determined that the sample is not a bacterium. When the average value of the thickness is a predetermined value, the process proceeds to the variation calculating step in step S114.

  Next, step S114 is a variation calculation step, and the variation in the thickness of the inspection object calculated in the thickness calculation step in step S109 is calculated. For thickness variation, for example, the standard deviation is calculated to calculate the variation. By using the average value of the thickness calculated in the thickness average value calculating step of step S111, the standard deviation is calculated by calculating the root mean square of the difference between the thickness at the thickness calculation point that is not a bent portion and the average value. Can be calculated.

  Next, step S115 is a step of determining whether or not the variation is within a predetermined value range, and it is determined whether or not the value calculated in the variation calculation step of step S114 is a predetermined value. The acid-fast bacterium is a long and thin bacterium having a uniform thickness. The variation in thickness can be calculated, and the bacterium can be determined based on whether the test object has a uniform thickness. For the thickness variation, the standard deviation value calculated in the variation calculation step in step S114 is used. In step S115, determination is made based on whether or not the standard deviation value is a predetermined value. For the predetermined value, the standard deviation value of the thickness of the inspection object that has been previously determined as a bacterium by the person and the inspection object that has been determined as not being a bacterium Calculate the standard deviation value of the thickness, calculate the average value of each, and calculate the intermediate value between the standard deviation value of the thickness when judged as bacteria and the standard deviation value of the thickness when judged as non-bacteria If the standard deviation value of the thickness of the test object is larger than the predetermined value, it is determined that the sample is not a bacterium and the process proceeds to step S113. If the standard deviation value is smaller than the predetermined value, the process proceeds to the length calculation process in step S116.

  In step S114 and step S115, the variation is calculated using the standard deviation and the degree of variation is determined. However, the variation in thickness is simply quantified by the difference between the maximum value and the minimum value, and the degree of variation is determined. May be. Since the processing is simple, the degree of variation can be calculated at high speed.

  Next, step S116 is a length calculation step, in which the length of the inspection object is calculated. The length is calculated from the length of the center line 801. If the center line 801 is not in contact with the contour 701 when calculating the length, both ends of the center line 801 are extended to the contour 701 as shown in FIG. Is calculated as the length of the inspection object.

  Next, step S117 is a step of determining whether or not the length is a predetermined value, and it is determined whether or not the length of the inspection object calculated in the length calculation step of step S116 is a predetermined value. As the predetermined value for determination, since the length of the acid-fast bacterium is in the range of 1 μm to 4 μm, this range is set as the predetermined value. If the length of the inspection object is not a predetermined value, the process proceeds to step S113, where it is determined that the sample is not bacteria. If the length is a predetermined value, the process proceeds to step S118 and is determined to be bacteria.

  Up to this point, the processing for one inspection region has been described in detail for the sake of simplicity, but from step S103 to step S118, the processing is simultaneously performed for all the inspection regions extracted in step S102.

  Next, step S119 is a bacteria count process, and the number of bacteria determined in step S118 is counted.

  By performing the processes from step S101 to step S119 as described above, it is possible to determine whether the inspection target is a bacterium or a non-bacteria.

  Next, the display means 104 in FIG. 1 will be described. For example, a liquid crystal monitor is used as the display unit 104. The display unit 104 displays the detection result output from the image processing unit 103. As the detection result, the number of bacteria counted in step S119 may be displayed, or a description symbol for each number of bacteria may be displayed based on the examination guidelines issued by the Japanese Tuberculosis Society. In addition, an image or the like determined as bacteria may be displayed.

  As described above, in the first embodiment, even when the bacteria are bent, it is possible to detect the bent portion and calculate the thickness of a place other than the bent portion. Bacteria can be accurately determined from variation and length.

  In the present embodiment, the acid-fast bacterium has been described as an example. However, the determination can be similarly performed for other koji molds, and is not limited to the acid-fast bacterium.

  In the present embodiment, the average value of the length of the bacteria in the same specimen is calculated, the length of the test object is about twice the average value of the length of the bacteria in the same specimen, and the curve is bent. When there is a portion, it may be determined that two bacteria are in contact with each other. A flowchart in this case is shown in FIG.

  When the test object has a shape as shown in FIG. 7, the bacteria may be bent as described above, but the tip of two bacteria may be in contact. Bacteria can be determined. When the tip of two bacteria are in contact with each other, the length of the test object is about two, so calculate the length of the test subject's bacteria, It is necessary to determine whether the length is about twice the length of the bacteria.

  Therefore, first, in step S122, an average length value is calculated for a measurement target that is a normal gonococcal length bacteria. Since the lengths of the bacteria in the same specimen are substantially equal, the length of the bacteria can be determined by calculating the average length. Then, the average value of the calculated length is fed back to the step S117, and the bacteria determination process is performed again on the measurement object that has not been determined as bacteria by the normal length determination.

  If it is determined in step S117 that the length of the inspection object is not a predetermined value, it is determined in step S120 whether the length of the inspection object is about twice the average value. If the length is about twice, the process proceeds to step S121. If not, the process proceeds to step S113 and it is determined that it is not a bacterium.

  Next, step S121 is a step of determining whether or not a bent portion exists in the inspection object. If there is a bent portion, the process proceeds to step S118, where it is determined as a bacterium, and if not, step S121 is performed. It transfers to S113 and it determines with other than bacteria.

  As described above, in the present embodiment, even when the tips of two bacteria are in contact with each other, it can be determined whether the bacteria are bacteria, and the accuracy of the bacteria determination can be improved.

(Embodiment 2)
FIG. 11 is a flowchart showing a shape determination method according to Embodiment 2 of the present invention. The difference from Embodiment 1 is that the presence or absence of a contact portion is detected from the intersection of the center lines, and when the contact portion is detected, the inspection object is separated into two regions and the shape is determined in each region. is there. FIG. 12 shows an example when two inspection objects are in contact with each other. In such a case, when photographing with a CCD camera, halation is caused by the fluorescence emitted from the inspection object, the boundary disappears, and it is often recognized as one area.

  First, as described in the first embodiment, the process from step S101 to step S104 is performed on the inspection object, and the center line is calculated.

  Next, step S201 is a step of determining whether or not there is an intersection on the center line. If there is no intersection on the center line, the process proceeds to the thickness calculation point selection step of step S105. If there is an intersection on the center line, it is determined that there is a contact portion, and the process proceeds to the inspection object separation step. The intersection can be calculated by investigating the branching state of the center line 801, and 1201 is the intersection in FIG.

  Next, step S202 is a contour inflection point calculation step, in which the inflection point of the contour 701 extracted in step S103 is calculated. In the case of FIG. 12, 1202 and 1203 are inflection points. The inflection point can be calculated from the positional relationship between the attention point on the contour 701 and the preceding and following inflection point calculation points. For example, when the attention point is 1202, 1202 and the preceding and following inflection point calculation points 1202a and 1202b. The angle is checked, and if it is smaller than a predetermined angle, it is calculated as an inflection point. For example, all the points on the contour line are selected as the attention point, and the search is performed. For the inflection point calculation points before and after, for example, a point that is 5 pixels away from the attention point is selected. Each time an attention point is searched, an inflection point calculation point is selected and moved by a point 5 pixels away from the attention point. As a predetermined angle for calculating whether the point is an inflection point, for example, if the angle is smaller than 120 degrees, the inflection point is calculated. When there are a plurality of inflection points in succession, the attention point having the smallest angle between the attention point and the inflection point calculation point is calculated as the inflection point.

  Next, step S203 is a region separation line calculation step, in which a separation line that separates the inspection region into two is calculated. The region separation line can be calculated from a straight line connecting the contour points calculated in the contour inflection point calculation step in step S202. In FIG. 13, a straight line 1204 connecting the inflection point 1202 and the inflection point 1203 is the region separation line. Become.

  Next, step S204 is an inspection region separation step, and the inspection region is separated by the region separation line 1204 calculated in the separation line calculation step of step S203. In FIG. 13, the region 1205 and the region 1206 are separated by a separation line 1204. As for the center line, the center line from the intersection 1201 to the region separation line 1204 is deleted, and the center line is also separated. After the regions are separated by the inspection region dividing step in step S204, the steps after step S105 are performed in each of the separated regions.

  Next, step S105 is a thickness calculation point selection step, and when there is no intersection on the center line, a thickness calculation point on the center line of the inspection region extracted in the inspection region extraction step of step S102 is selected, and the center line If there is an intersection, a thickness calculation point on the center line of each inspection region separated in the inspection region separation step in step S204 is selected.

  Next, step S109 is a thickness calculation step, in which the thickness at the thickness calculation point is calculated. Steps S105 and S109 are repeated in step S110 until there are no thickness calculation points.

  When the calculation of the thickness at the thickness calculation point is completed, the average value of thickness, the variation in thickness, and the length are calculated as in the first embodiment, and whether each value is a predetermined value or not is a bacterium. Judge whether it is other than bacteria.

  As described above, in the second embodiment, since the overlapping of bacteria is detected and the overlapping area is separated and each bacteria is detected, it is possible to accurately determine whether or not the bacteria are in contact with each other. Can be done.

  The shape determination method according to the present invention has a function of determining bacteria even when the bacteria are bent or in contact with the bacteria, and is useful as a bacteria testing apparatus or the like.

The block diagram of the shape inspection apparatus in Embodiment 1 and Embodiment 2 of this invention Explanatory drawing of the fluorescence microscope in Embodiment 1 and Embodiment 2 of this invention The flowchart of the shape determination method in Embodiment 1 of this invention Flowchart of another form determining method according to Embodiment 1 of the present invention Binarization explanatory drawing in Embodiment 1 of this invention Explanatory drawing of the labeling process in Embodiment 1 of this invention Outline extraction result diagram according to Embodiment 1 of the present invention Explanatory drawing for calculation of the amount of bending in Embodiment 1 of the present invention Explanatory drawing for thickness calculation of a test subject in Embodiment 1 of the present invention Explanatory drawing for length calculation of the inspection subject in Embodiment 1 of the present invention Flowchart of shape determination method in Embodiment 2 of the present invention Explanatory drawing of a test subject when there is a contact part in Embodiment 2 of the present invention Explanatory drawing of isolation | separation of the inspection area | region in Embodiment 2 of this invention Explanatory drawing for calculation of the amount of bending in Embodiment 1 of the present invention

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Optical means 102 Imaging means 103 Image processing means 104 Display means 105 Plate 201 Light source 202 Light source light 203 Excitation filter 204 Excitation light 205 Dichroic mirror 206 Objective lens 207 Fluorescence 208 Absorption filter 209 Lights other than fluorescence 601, 602, 603, 604 605, 606 Inspection area 701 Outline 801 Center line 802, 803, 804 Thickness calculation point 802a, 802b, 803a, 803b Bending amount calculation point 901 Thickness of inspection object 1201 Intersection 1202, 1203 Inflection point 1202a, 1202b Inflection Point calculation point 1204 Area separation line 1205, 1206 Divided area 1401 Thickness calculation point 1401a, 1401b Bending amount calculation point

Claims (7)

A region extraction step of extracting a region of the inspection object for which shape determination is performed from the captured image;
A contour calculating step for calculating a contour of the inspection object;
A center line calculating step for calculating a center line of the inspection object;
A bent portion detecting step of detecting a bent portion of the inspection object from the shape of the center line;
A thickness calculating step of calculating the thickness of the inspection object in the region excluding the bent portion from the contour calculated in the contour calculating step;
A thickness average value calculating step of calculating an average value of the thickness;
A thickness variation degree calculating step of calculating the thickness variation degree;
A length calculating step of calculating the length of the inspection object from the length of the center line;
A shape determination method including a shape determination step of determining a shape of the inspection object from the average thickness value, the thickness variation degree, and the length of the inspection object. In the shape determination step, when the thickness average value and the thickness variation degree are predetermined values, and the length of the inspection object is a predetermined value, the inspection object is determined to be bacteria. The shape determination method according to claim 1.   A length average value calculating step for calculating an average value of the length of bacteria is further provided. In the shape determining step, a bent portion is detected in the bent portion detecting step, and the thickness average value and the thickness variation degree are detected. Is a predetermined value, and when the length of the test object is about twice the length average value calculated in the length average value calculation step, the shape is determined to be in contact with two bacteria. The shape determination method according to claim 1. An inspection area extraction step for extracting an area of an inspection object for which shape determination is performed from the captured image;
A center line calculating step for calculating a center line of the inspection object;
A contour calculating step for calculating a contour of the inspection object;
A contact detection step of detecting contact of the object from the shape of the center line;
A separation step of separating an inspection object into two regions from the shape of the contour when contact is detected in the contact detection step;
A thickness calculating step of calculating the thickness of the inspection object from the contour calculated in the contour calculating step;
A length calculating step of calculating the length of the inspection object from the center line;
A thickness average value calculating step of calculating an average value of the thickness;
A thickness variation degree calculating step for calculating the thickness variation degree;
A shape determination method including a shape determination step of determining the shape of the inspection object from the average value of the thickness, the variation degree of the thickness, and the length of the inspection object. In the shape determination step, when the thickness average value and the thickness variation degree are predetermined values, and the length of the inspection object is a predetermined value, the inspection object is determined to be bacteria. The shape determination method according to claim 4. The shape determination method according to claim 1, wherein in the thickness variation degree calculation step, the thickness variation degree is calculated based on a standard deviation of the thickness. The shape determination method according to claim 1, wherein, in the thickness variation degree calculation step, the thickness variation degree is calculated based on a difference between a maximum value and a minimum value of the thickness.

Images