JPH0649195B2 - Microorganism detection device - Google Patents

Description

Description: FIELD OF THE INVENTION The present invention relates to a microorganism detecting device for detecting the type and amount of appearance of microflora using image processing technology.

[Background of the Invention]

As a typical example of utilizing a large amount of microorganisms, a biological sewage treatment method is known. The activated sludge method is one of biological sewage treatment methods, and is a method of treating organic substances in sewage by utilizing the oxidative decomposition action of aerobic microorganisms. The process consists of an aeration tank maintained in an aerobic condition and a settling basin for gravity settling of microorganisms. Due to the operational management of this process,
What is particularly important is to grow microorganisms having a good sedimentation property. This is because when microorganisms having poor sedimentation properties appear, not only do they flow out of the sedimentation pond and the quality of the treated water deteriorates, but also the total amount of microorganisms in the process system decreases and the treatment becomes impossible.

By the way, generally, it is said that there are about 50 kinds of microorganisms in which the activated sludge method often appears. The activated sludge, which is a general term for these microorganism groups, can be roughly classified into two types. One is the cohesive zoo glare (Zoogloe
It is a) type microorganism and has excellent sedimentation property for forming good flocs. The other is a filamentous microorganism, which impedes the mutual access of flocs and is inferior in sedimentation and compaction. If this filamentous microorganism grows abnormally, it causes a bulking state (sludge expansion), solid-liquid separation is not possible in the sedimentation tank, and activated sludge flows out.

The growth of zooglare microorganisms and filamentous microorganisms differs depending on the organic matter load (the amount of organic matter per unit activated sludge weight) in the aeration tank and the aeration conditions. Therefore, it is important to maintain and manage the microbial flora that forms stable flocs in sewage treatment plants where the inflow conditions change drastically on a daily basis or in seasons. For that purpose, it is necessary to understand the state of activated sludge.

An optical microscope is usually used to grasp the state of activated sludge. The microscopic image contains a lot of information, and the state of activated sludge can be known by observing the type and number of emerging microorganisms. Conventionally, in order to measure the type and number of microorganisms, a method of visually observing a microscopic image itself, or taking a photograph and visually observing the photographing result has been adopted. However, reading this information requires skill, and even a skilled operator who is familiar with microorganisms spends a lot of time and makes frequent observation difficult. In particular, the number of appearance of filamentous microorganisms is difficult to obtain by calculating the total length by manually analyzing the individual length from the imaging result. Therefore, it is the actual situation that the analysis of the microflora by microscopic images requires a long time even for an expert operator who has specialized knowledge and cannot be frequently observed, and effective information is not sufficiently utilized.

On the other hand, in other microbial culturing processes to which the invention is applied, filamentous microorganisms that produce antibiotics such as penicillin are cultivated or fermented using filamentous microorganisms. In these processes, the purpose is to grow filamentous microorganisms and obtain antibiotics that are metabolized from filamentous microorganisms, but since the amount of antibiotics cannot be measured in a short time,
It is necessary to monitor the growth of filamentous microorganisms.

Conventionally, filamentous microorganisms are sampled and dried,
I try to weigh this. However, since this measuring method is a manual operation by an observer as in the case of the sewage treatment process, even if a skilled observer makes a measurement, it takes several hours for one measurement.

On the other hand, recently, as described in Japanese Patent Laid-Open No. 60-31889, a method of capturing microbes as image information with an industrial television camera (ITV) as an imaging device and detecting the microbes in a flow rate by image processing technology. Are also considered. But,
When the difference between the brightness of the microorganisms and the brightness of the background is small, the background brightness of the optical system cannot be perfectly uniform, and light unevenness occurs, and it is difficult to detect only the microorganisms.

[Object of the Invention]

It is an object of the present invention to provide a microorganism detecting apparatus capable of performing image processing on a microscopic image of a microorganism, analyzing the amount of the microorganism in a short time, and automatically detecting the amount.

[Outline of Invention]

The feature of the present invention is that when a microscope image is converted into luminance information and the background luminance information before the microbial sample is subtracted from the luminance information after the sample, the luminance information of only the microorganism is obtained,
By setting an arbitrary brightness level in the brightness information, the number of pixels corresponding to the target microorganism is extracted and the state of the microflora can be automatically detected.

Example of Invention

 FIG. 1 shows an embodiment of the present invention.

A test liquid such as activated sludge is collected through a sampling tube 101 and is guided to a slide glass 1 by a pump 103.
After the test liquid is observed, it is discharged from the drain pipe 102. An image magnifying optical device 2 such as an optical microscope is arranged on the slide glass 1 with a slight gap. The slide glass 1 is preferably thin so that the optical microscope can be focused on it. It is also possible to quantitatively collect the test liquid in a preparation according to a standard method of an optical microscope and perform a microscopic examination. By enlarging the microbiota of the collected test liquid with the optical microscope 2, an original image with contrast can be produced. When the optical microscope is in the bright field, the object to be examined is dark and the background is bright.

The original image has a dark microbial fauna in the liquid fauna that is the light background. The original image is converted into luminance information by an imaging device 3 such as an industrial television camera (hereinafter referred to as ITV). The brightness information obtained by the ITV 3 is processed by the information processing device 4 and displayed on the monitor 5. ITV in Figure 3
The example of the image of the activated sludge converted into the luminance information from 3 is shown. Z represents, for example, a zooglare microbial mass having excellent flocculation and sedimentation properties among the activated sludge flocs, and F represents a filamentous fungus having poor sedimentation properties. B is the background liquid phase part. It should be noted that the hatched portion of the microbial mass Z looks black. Here, N is noise due to dirt or scratches attached to the optical system or the slide glass, for example.

Details of the information processing device 4 are shown in FIG.

In FIG. 2, the brightness information from the ITV 3 is converted into a digital signal by the A / D converter 40 and stored in the image memory 41. When using fresh water with no microorganisms as the test solution,
The captured image by ITV3 is only the background as shown in FIG. The background consists of a liquid phase portion B and noise N. The background image information is A / D converted and stored as background luminance information in the auxiliary image memory 42 via the image memory 41. The auxiliary memory 41 stores the states of the slide glass 1 and the microscope 2 as a pretreatment of the microorganism detection treatment in the activated sludge.

FIG. 5 shows the luminance distribution on the line AA 'in FIG. MAX represents the maximum value of emotions. The liquid phase portion B has a high luminance, and the flock portion Z has a low luminance. The brightness of the filamentous fungus F is intermediate between the two.

In order to extract the filamentous fungus F using the luminance information, it is necessary to determine the luminance levels of the liquid phase portion B and the flot portion Z in advance.

As shown in FIG. 6, the brightness of the liquid phase portion B is non-uniform due to light unevenness, and the brightness level of the filamentous fungus F shown in FIG. 5 is also non-uniform. Further, since the luminance S _{N of the} noise N is similar to that of the filamentous fungus, there is a high possibility that it will be extracted as the filamentous fungus.

The luminance signals of the pixels in the i-th row and the j-th column are S _ij and W _{ij in} each of FIGS. 3 and 4. In FIG. 2, S _ij corresponds to the pixel memory 41, and W _ij corresponds to the auxiliary pixel memory 42. The brightness correction circuit 43 has a maximum brightness value M.
Using AX, the corrected luminance information C _{ij from} which the influence of the background luminance shown in the equation (1) is removed is calculated.

C _ij = S _ij + (MAX + W _ij ) ... (1) FIG. 7 shows an image represented by the corrected luminance information C _ij , and FIG. 8 shows the luminance distribution on the line AA ′ of the image of FIG. Show. In the corrected luminance distribution, the background luminance is MAX and uniform, and the noise N is also removed.

The brightness level determination circuit 44 is a circuit for extracting the maximum value S _B and the minimum value S _Z of the brightness level from the brightness distribution of FIG. The maximum value S _B is the background brightness and is expressed by the formula (2) S _B = MAX (2), and the minimum value S _x is the average value of the block portion Z.

Threshold value setting circuit 45 sets a brightness level lower S _h than the background luminance S _B at a higher luminance than the lower luminance level S _l and fungal F than a high brightness and filamentous fungi F than Furotsuku portion Z. The range of the set levels S _l and S _h is shown by the equation (3).

S _B > S _l > S _h > S _X (3) The binarization circuit 46 extracts the filamentous fungus F from the corrected luminance information. That is, the luminance information C _ij of the pixel in the i-th row and the J-th column is binarized by the expressions (4) and (5), and only the pixel corresponding to the filamentous fungus F is extracted.

When S _l ≦ C _ij ≦ S _h , f _ij = 1 (4) When C _ij <S ₁ or C _ij > S _h , f _ij = 0 (5) where f _ij is a pixel corresponding to a filamentous fungus Represents Only the pixel corresponding to the filamentous fungus F has a signal "1" by the binarization circuit 46.
Level. FIG. 9 shows an example of binarizing and extracting the filamentous fungus F of FIG. 8 and FIG. 10 shows an example of the filamentous fungus F extracted from the microflora of FIG. 7. The filamentous fungus F extracted as shown in FIG. 10 is subjected to a thinning process by the integrating circuit 47 to be processed into a line having a width of 1 pixel. After performing the above processing, f _{ij of} which the pixel signal is “1” level is repeatedly added in each of the i-th row and the j-th column to obtain the length f of the filamentous fungus F in the entire screen.
ask for _v The addition of the pixels f _ij is obtained by the addition circuit 48 according to the equation (6).

Since only the filamentous fungal length f _{v on} one screen causes variations, the filamentous fungal length f _v is calculated for a plurality of screens,
The average value is used for evaluation. The adder circuit 49 calculates the average value ▲ ▼ of N screens according to the equation (7).

The filamentous fungus length average value ▲ ▼ represents the number of pixels per screen of the filamentous fungus. Since each pixel formed by equal division of the screen has a fixed length, the filamentous fungus length L of the sample can be obtained by using the number of pixels obtained by the equation (7).

L = l∇ (8) where l is the pixel length adding circuit 414, which determines the total length of the filamentous fungus.

On the other hand, the binarization extraction of the pixel Z _{ij in which} the block, that is, the Zugrea microorganism is present, is obtained by the binarization circuit 410 according to the following equation.

When C _ij ≦ S _l Z _ij = 1 (8) When C _ij > S _l Z _ij = 0 (9) In the adder circuit 411, the pixel whose Z _ij is “1” level is i row, j
The area Z _v of the floating portion is obtained according to the equation (10) by repeating the process for each of the columns and adding for the entire one screen.

Further, the average value ▲ ▼ of the number of pixels in the floating portion of the N screen is calculated by the adding circuit 412 according to the equation (11).

The integrating circuit 413 is a circuit that integrates the pixel area with the number of pixels obtained by the equation (11), and by doing so, the area A of the Suglerous microorganism of the sample can be obtained.

A = a ..... (12) where a is the pixel area.

The display control circuit 415 uses the original image, f _ij , f _v , ▲.
This is a circuit that selects only the necessary signal from the signals ▼, L, Z _ij , Z _v , ▲ ▼, and A. The image selected by the display control circuit 415 is converted into an analog signal by the D / A converter 416 and sent to the monitor 15 for display.

As described above, the present invention converts a microbial image into luminance information, and when detecting a microorganism from the luminance information, the background luminance information in which no microorganism is present is subtracted from the microorganism luminance information, so processing is performed. It is possible to remove various obstacles such as light unevenness, dirt, and scratches that occur in the detection part such as a magnifying optical device and a slide glass, and it becomes possible for the filamentous fungus to measure the amount of zooglare microorganisms with high accuracy.

〔The invention's effect〕

According to the present invention, the microflora magnified by an image magnifying optical device such as a microscope can be automatically analyzed by a simple process,
It is particularly effective for detecting highly transparent filamentous fungi and zookerea microorganisms. The reliability is higher than that of the image processing method used conventionally, and the number of maintenance such as cleaning of the microorganism detecting portion can be greatly reduced.

In addition, although the above-mentioned example explained the example applied to the sewage treatment process, it goes without saying that the present invention can be applied to the measurement of the concentration of filamentous microorganisms in other bioprocesses for culturing filamentous microorganisms.

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of the present invention, FIG. 2 is a detailed view of the embodiment, FIG. 3 is an example view of a microorganism image, FIG. 4 is an example view of a background image, and FIG. Luminance distribution map of microorganism image,
FIG. 6 is a luminance distribution diagram of a background image, FIG. 7 is an example diagram of a microorganism image, FIG. 8 is a microorganism image luminance distribution diagram, FIG. 9 is a binary example of filamentous fungi, and FIG. 10 is a filamentous fungus image. 1 …… Slide glass, 2 …… Image magnifying optical device, 3 ……
Imaging device, 4 ... Information processing device, 5 ... Monitor, 103
……pump.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Mikio Yoda 5-2-1 Omika-cho, Hitachi City, Ibaraki Prefecture Hitachi Ltd. Omika Plant, Hitachi Ltd. (72) Naoki Hara 5-chome, Omika-cho, Hitachi City, Ibaraki Prefecture No. 1 Inside the Omika Plant of Hitachi, Ltd. (56) References JP-A-60-31889 (JP, A) JP-A-61-33296 (JP, A) JP-A-61-35798 (JP, A) Special Kai 60-30675 (JP, A)

Claims (1)

[Claims] 1. An image pickup device for converting a microbial image into luminance information, a first storage means for storing the microbial luminance information converted into the luminance information by the image pickup device, and background luminance information in which no microorganism exists. And a second detecting means, a calculating means for subtracting the background luminance information from the microorganism luminance information, and a microorganism detecting means for detecting the amount of microorganisms from the microorganism luminance information from which the background luminance information is subtracted. .