JPH0744707A - Bacterium inspection device and inspection method - Google Patents
Bacterium inspection device and inspection methodInfo
- Publication number
- JPH0744707A JPH0744707A JP5185716A JP18571693A JPH0744707A JP H0744707 A JPH0744707 A JP H0744707A JP 5185716 A JP5185716 A JP 5185716A JP 18571693 A JP18571693 A JP 18571693A JP H0744707 A JPH0744707 A JP H0744707A
- Authority
- JP
- Japan
- Prior art keywords
- image
- bacteria
- picture
- light
- film
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 241000894006 Bacteria Species 0.000 title claims abstract description 91
- 238000000034 method Methods 0.000 title claims description 47
- 238000007689 inspection Methods 0.000 title claims description 15
- 238000012545 processing Methods 0.000 claims abstract description 31
- 238000003825 pressing Methods 0.000 claims abstract description 16
- 239000003153 chemical reaction reagent Substances 0.000 claims abstract description 14
- 238000012935 Averaging Methods 0.000 claims abstract description 11
- 238000004364 calculation method Methods 0.000 claims abstract description 11
- 239000012528 membrane Substances 0.000 claims description 19
- 238000003384 imaging method Methods 0.000 claims description 15
- 239000000470 constituent Substances 0.000 claims description 9
- 238000004020 luminiscence type Methods 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 239000013307 optical fiber Substances 0.000 claims description 5
- 241000233866 Fungi Species 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract description 9
- 230000035945 sensitivity Effects 0.000 abstract description 6
- 238000003860 storage Methods 0.000 abstract description 4
- 230000010354 integration Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 26
- 239000011159 matrix material Substances 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 7
- 239000007788 liquid Substances 0.000 description 6
- 239000005089 Luciferase Substances 0.000 description 4
- 230000001580 bacterial effect Effects 0.000 description 4
- 210000004027 cell Anatomy 0.000 description 4
- 210000000170 cell membrane Anatomy 0.000 description 4
- 244000005700 microbiome Species 0.000 description 4
- 239000000758 substrate Substances 0.000 description 4
- 108090000790 Enzymes Proteins 0.000 description 3
- 102000004190 Enzymes Human genes 0.000 description 3
- 230000001464 adherent effect Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 101150024971 ATP4 gene Proteins 0.000 description 2
- IGXWBGJHJZYPQS-SSDOTTSWSA-N D-Luciferin Chemical compound OC(=O)[C@H]1CSC(C=2SC3=CC=C(O)C=C3N=2)=N1 IGXWBGJHJZYPQS-SSDOTTSWSA-N 0.000 description 2
- CYCGRDQQIOGCKX-UHFFFAOYSA-N Dehydro-luciferin Natural products OC(=O)C1=CSC(C=2SC3=CC(O)=CC=C3N=2)=N1 CYCGRDQQIOGCKX-UHFFFAOYSA-N 0.000 description 2
- BJGNCJDXODQBOB-UHFFFAOYSA-N Fivefly Luciferin Natural products OC(=O)C1CSC(C=2SC3=CC(O)=CC=C3N=2)=N1 BJGNCJDXODQBOB-UHFFFAOYSA-N 0.000 description 2
- 108060001084 Luciferase Proteins 0.000 description 2
- DDWFXDSYGUXRAY-UHFFFAOYSA-N Luciferin Natural products CCc1c(C)c(CC2NC(=O)C(=C2C=C)C)[nH]c1Cc3[nH]c4C(=C5/NC(CC(=O)O)C(C)C5CC(=O)O)CC(=O)c4c3C DDWFXDSYGUXRAY-UHFFFAOYSA-N 0.000 description 2
- 101100436871 Neurospora crassa (strain ATCC 24698 / 74-OR23-1A / CBS 708.71 / DSM 1257 / FGSC 987) atp-3 gene Proteins 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 238000012258 culturing Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000009499 grossing Methods 0.000 description 2
- 238000002796 luminescence method Methods 0.000 description 2
- 239000011259 mixed solution Substances 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 210000001082 somatic cell Anatomy 0.000 description 2
- 229920001817 Agar Polymers 0.000 description 1
- 239000000020 Nitrocellulose Substances 0.000 description 1
- 239000008272 agar Substances 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000014670 detection of bacterium Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000007850 fluorescent dye Substances 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 229920001220 nitrocellulos Polymers 0.000 description 1
- 125000000962 organic group Chemical group 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 239000012488 sample solution Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000010865 sewage Substances 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 239000004094 surface-active agent Substances 0.000 description 1
- -1 that is Proteins 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Landscapes
- Image Processing (AREA)
- Image Analysis (AREA)
- Investigating Or Analysing Materials By The Use Of Chemical Reactions (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
Description
【０００１】[0001]
【産業上の利用分野】本発明は液体中の微生物や体細胞
の数を計測する細菌検査装置と検査方法に関する。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a bacteria inspection device and an inspection method for measuring the number of microorganisms and somatic cells in a liquid.
【０００２】[0002]
【従来の技術】ここでは、細菌を微生物、体細胞なども
含めて、これらの総称として取り扱うが、これら細菌数
を計測することは、食品，醸造，臨床，上下水および半
導体などの各分野における品質管理や環境管理などを行
なう上で極めて重要である。例えば、微生物の菌数また
は微生物活性の計測には、従来、コロニー計数方法が一
般に用いられている。コロニー計数方法は、寒天培地に
試料液の一定量を散布または混合して培養し、生じたコ
ロニーを計数する方法であるが、培養時間に数十時間を
必要とし、操作も煩雑である。2. Description of the Related Art Here, bacteria are collectively referred to as microorganisms and somatic cells, but the number of these bacteria is measured in various fields such as food, brewing, clinical, water and sewage, and semiconductors. It is extremely important for quality control and environmental control. For example, conventionally, a colony counting method has been generally used for measuring the number of microorganisms or the activity of microorganisms. The colony counting method is a method of spraying or mixing a fixed amount of the sample solution on an agar medium and culturing, and counting the generated colonies, but the culturing time requires several tens of hours, and the operation is complicated.
【０００３】その他、ＡＴＰをルシフェリン−ルシフェ
ラーゼ基質−酵素混合液で発光させ、その発光量から菌
数を推定するＡＴＰ測定法、細菌を蛍光色素で染色して
観察する方法などがあるが、いずれも操作が煩雑で迅速
性に欠け、精度も悪い。このような従来の方法の欠点を
克服して、迅速で精度の高い方法が近年開発されつつあ
る。例えば、特開平２−５１０６３号公報、雑誌Ｊ．Ｃ
ｌｉｎ．Ｃｈｅｍ．Ｃｌｉｎ．Ｂｉｏｃｈｅｍ．，Ｖｏ
ｌ．２６，１９８８，ｐｐ１４７−１４８に記載されて
いるように、二次元的に散布された細菌に対して、抗原
−抗体反応を利用して発光酵素を標識し、基質を添加し
たときの発光基点を画像として撮像し計数する方法であ
る。In addition, there are methods such as ATP measuring method in which ATP is caused to emit light by a luciferin-luciferase substrate-enzyme mixed solution, and the number of bacteria is estimated from the amount of emitted light, and a method in which bacteria are stained and observed with a fluorescent dye. The operation is complicated, lacks swiftness, and has poor accuracy. In recent years, rapid and highly accurate methods have been developed to overcome the drawbacks of the conventional methods. For example, JP-A-2-51063, magazine J. C
lin. Chem. Clin. Biochem. , Vo
l. 26, 1988, pp 147-148, a luminescent enzyme is labeled with a luminescent enzyme using an antigen-antibody reaction on a two-dimensionally dispersed bacterium, and a luminescent base point when a substrate is added is determined. This is a method of capturing and counting as an image.
【０００４】図８（ａ）〜（ｃ）は、ルシフェリン−ル
シフェラーゼによるＡＴＰ発光法により、生菌計数を行
なったときの過程を示す模式図である。図８（ａ）〜
（ｃ）におけるＥ（□印）は酵素、即ちここではルシフ
ェラーゼ、Ｓ（○印）は基質、ここではルシフェリンを
表わしている。細菌Ｃが捕捉された膜１の表面１ａ上に
は、あらかじめルシフェリン−ルシフェラーゼ混合液を
浸潤させておくので、光ファイバープレート２の入力面
２ａと膜表面１ａとの間には、酵素−基質を含む液膜層
３が存在する。一方、ＡＴＰ４（・印）は、細胞内部に
細胞膜５によって閉じ込められているために、発光反応
は起こらない［図８（ａ）］。FIGS. 8 (a) to 8 (c) are schematic diagrams showing the process of counting viable cells by the ATP luminescence method using luciferin-luciferase. 8 (a)-
In (c), E (square mark) represents an enzyme, that is, luciferase here, and S (◯ mark) represents a substrate, here luciferin. Since the luciferin-luciferase mixed solution is preliminarily infiltrated on the surface 1a of the membrane 1 on which the bacteria C are captured, an enzyme-substrate is contained between the input surface 2a of the optical fiber plate 2 and the membrane surface 1a. The liquid film layer 3 is present. On the other hand, since ATP4 (• mark) is confined inside the cell by the cell membrane 5, the luminescence reaction does not occur [FIG. 8 (a)].
【０００５】ここで膜裏面１ｂから、矢印で示したＡＴ
Ｐ抽出液（通常は界面活性剤など細胞膜を溶解する試
薬）６を注入すると、膜表面１ａに拡散し、付着してい
た細菌の細胞膜５が溶解して、内部のＡＴＰ４は外部に
放出される［図８（ｂ）］。放出されたＡＴＰ４は、液
膜層３に存在していた発光酵素ルシフェラーゼＥによ
り、基質ルシフェリンＳと反応して発光（太い矢印７）
する［図８（ｃ）］。Here, from the film back surface 1b, the AT indicated by the arrow
When a P extract (usually a reagent such as a surfactant that dissolves a cell membrane) 6 is injected, it diffuses to the membrane surface 1a, the attached bacterial cell membrane 5 is dissolved, and the internal ATP 4 is released to the outside. [FIG.8 (b)]. The released ATP4 reacts with the substrate luciferin S by the luminescent enzyme luciferase E existing in the liquid film layer 3 to emit light (thick arrow 7).
[FIG. 8 (c)].
【０００６】以上のように、幾つかの方法によって、膜
上に付着した細菌を発光させることができる。図９は、
細菌の発光点を検出する装置例として、測定部の要部構
成を示す模式図であり、例えばニトロセルロースなどの
膜１で濾過した付着細菌８（発光基点）の発光画像を、
カメラレンズ９によって高感度撮像手段１０の入力面１
１に結像させ、画像信号をケーブル１２により取り出す
ものである。この方法は、イメージインテンシファイア
ーなどの高感度撮像手段を用いることにより、測定の迅
速性と正確性において優れた特徴を有する。As described above, the bacteria attached on the film can be made to emit light by several methods. Figure 9
FIG. 2 is a schematic diagram showing a configuration of a main part of a measuring unit as an example of a device for detecting a light emitting point of bacteria, and shows, for example, a light emission image of adherent bacteria 8 (light emitting origin) filtered through a membrane 1 such as nitrocellulose.
The input surface 1 of the high-sensitivity imaging means 10 by the camera lens 9
1, and the image signal is taken out by the cable 12. This method has excellent characteristics in measurement speed and accuracy by using a high-sensitivity imaging means such as an image intensifier.
【０００７】さらに、これを改良した装置の測定部の要
部構成を図１０の模式図に示し、図９と共通する部分を
同一符号で表わす。図１０に示すように、高感度撮像手
段１０の光入力部１３を光ファイバープレートとし、こ
の光入力部１３に、膜１の細菌付着面を押し板１４と遮
光蓋１５により押圧し、光入力部１３と膜１の細菌付着
面を密着させて発光反応を生じさせ、光増幅された画像
出力をカメラレンズ１６とＣＣＤカメラ１７によって画
像信号１８に変換して、菌体の発光画像を計測する方式
もある。この方法は、カメラレンズによる膜面撮像方式
に比べて集光効率が向上し、しかも試薬類の自動注入を
容易にすることができる。Further, the construction of the main part of the measuring section of the improved apparatus is shown in the schematic view of FIG. 10, and the portions common to FIG. 9 are designated by the same reference numerals. As shown in FIG. 10, the light input section 13 of the high-sensitivity image pickup means 10 is an optical fiber plate, and the bacteria adhering surface of the film 1 is pressed against the light input section 13 by the pressing plate 14 and the light shielding lid 15. A method for measuring the luminescence image of the bacterial cells by bringing 13 into close contact with the bacteria-adhering surface of the membrane 1 to cause a luminescence reaction, and converting the optically amplified image output into an image signal 18 by the camera lens 16 and the CCD camera 17. There is also. This method improves the light-collecting efficiency as compared with the film surface imaging method using a camera lens, and facilitates automatic injection of reagents.
【０００８】[0008]
【発明が解決しようとする課題】しかしながら、上記の
方法では、高感度撮像手段であるイメージインテンシフ
ァイアーの光電面の感度むらや、カメラレンズの明るさ
のむら、さらに発光試薬類の膜上での背景光のむらなど
があり、視野全体に亘って微弱な発光点を自動的に計数
することが困難である。このような背景光のむらを除去
する方法として、あらかじめ背景画像のみを測定し、後
に測定画像から減算または割り算を行なうのが一般的で
あるが、発光試薬類の背景光のむらのように、背景画像
が測定の都度変化する場合には、この方法を適用するこ
とができない。また、膜上に捕捉された菌同士が近接し
て存在する場合には、複数の菌を１個として数えること
があり、これを分離して計数する方法として、本発明者
らが特開平４−３０７９８号公報で開示したように、発
光輝点の構成画素数を菌体１個当たりの平均画素数で割
り算して計数する方法があるが、菌体による発光輝点の
重なり方を考慮していないため、誤差が大きいことがわ
かった。However, in the above method, the unevenness of the sensitivity of the photocathode of the image intensifier, which is the high-sensitivity image pickup means, the unevenness of the brightness of the camera lens, and the luminescent reagents on the film are not detected. Due to the unevenness of the background light, it is difficult to automatically count weak light emitting points over the entire visual field. As a method of removing such background light unevenness, it is common to measure only the background image in advance and then perform subtraction or division from the measurement image, but like background light unevenness of luminescent reagents, the background image This method cannot be applied when is changed with each measurement. Further, when the bacteria captured on the membrane are present close to each other, a plurality of bacteria may be counted as one. As a method for separating and counting the bacteria, the present inventors have disclosed in Japanese Patent Laid-Open No. As disclosed in JP-A-30798, there is a method of counting the number of constituent pixels of luminescent bright spots by dividing the number of constituent pixels of the luminescent bright spots by the average number of pixels per fungus body. It was found that the error was large because it was not.
【０００９】本発明は、上記の課題を解決するためにな
されたものであり、その目的は、背景光を減少して、背
景に一定でないむらのある画像でも、確実に菌による発
光点を検出し、かつ、菌の重なりによる計数誤差を小さ
くし、正確な菌の計数を自動的に行なうことが可能な細
菌検査装置と検査方法を提供することにある。The present invention has been made in order to solve the above-mentioned problems, and its object is to reliably detect a light-emitting point due to a bacterium by reducing background light and even in an uneven image in the background. In addition, it is an object of the present invention to provide a bacteria inspection device and an inspection method capable of reducing counting errors due to overlapping of bacteria and automatically performing accurate bacteria counting.
【００１０】[0010]
【課題を解決するための手段】上記の課題を解決するた
めに、本発明の細菌検査装置は、結像面に光ファイバー
プレートを備えた高感度撮像手段の入力面に細菌付着面
が接するように載置した膜の裏面から、表面に艶消しの
黒色処理を施した押し板によりこの膜を押圧する手段を
有する測定部、およびおよび撮像して得られた菌に対応
する複数の点状の高輝度画素群を含む積算画像を所定の
サンプル数で移動平均化する平均化処理手段と、２種類
の画面の減算を行なう画面間演算処理手段と、画像の所
定の領域を所定のしきい値で２値化する画像２値化手段
と、２値化された画像の高輝度画素群を群毎に計数する
手段とを有する画像処理部を備え、この装置を用いた細
菌検査方法は、撮像により得られた菌に対応する複数の
点状の高輝度画素群を含む積算画像（Ａ）を、高輝度画
素群より少ないサンプル数で移動平均化して画像（Ｂ）
を得てこれを記憶し、高輝度画素群より多いサンプル数
で移動平均化して画像（Ｃ）を得、画像（Ｂ）から画像
（Ｃ）を対応する各画素毎に減算して画像（Ｄ）を得、
画像（Ｄ）の所定の領域を所定のしきい値で２値化し、
２値化された画像の高輝度画素群を群毎に計数するもの
であり、計数方法は、高輝度画素群ｉに関する２値化前
の群の最高輝度値をＩmax ，２値化後の群の構成画素数
をＳi，菌単体当たりの平均輝度値をＩS ，菌単体当た
りの平均画素数をＳS とし、関数ｆを小数点以下四捨五
入するものとし、画素群ｉについての重みＷi を式
（１）で計算し、 Ｗi ＝ｆ（Ｓi ／ＳS ）＋ｆ（Ｉmax ／ＩS ）−１ （１） 画像中高輝度群総数をｎとして、式（２）から総菌数Ｎ
を計算する。In order to solve the above-mentioned problems, in the bacteria inspection apparatus of the present invention, the bacteria adhering surface is in contact with the input surface of the high-sensitivity image pickup means having an optical fiber plate on the image forming surface. From the back side of the placed film, the measurement part having a means to press the film with a pressing plate with matt black treatment on the surface, and a plurality of dot-shaped heights corresponding to the bacteria obtained by imaging. Averaging processing means for moving and averaging the integrated image including the luminance pixel group with a predetermined number of samples, inter-screen calculation processing means for subtracting two types of screens, and a predetermined area of the image with a predetermined threshold value. An image processing unit having an image binarizing unit for binarizing and a unit for counting the high-luminance pixel group of the binarized image for each group is provided. Multiple point-like high-intensity pixels corresponding to the obtained fungus The accumulated image comprising (A), moving averages with less number of samples than the high luminance pixel group image (B)
The image (C) is obtained by storing and averaging it with a larger number of samples than the high brightness pixel group, and the image (C) is subtracted from the image (B) for each corresponding pixel to obtain the image (D). ),
Binarize a predetermined area of the image (D) with a predetermined threshold,
The high-brightness pixel group of the binarized image is counted for each group, and the counting method is the maximum brightness value of the group before the binarization regarding the high-brightness pixel group i is I max , the number of constituent pixels S i of the group, the average luminance value I S per bacteria alone, the average number of pixels per cell alone and S S, the function f is assumed to round decimal, the weight W i for the pixel groups i Is calculated by the formula (1), and W i = f (S i / S S ) + f (I max / I S ) −1 (1) The total number of bacteria is calculated from the formula (2), where n is the total number of high-intensity groups in the image. N
To calculate.
【００１１】 [0011]
【００１２】[0012]
【作用】以上の装置構成により、撮像入力面に膜を密着
させる押し板を、艶消し黒色処理を施したために、膜上
に放射される背景光を吸収し、背景光反射光を小さく
し、従来の鏡面仕上げの押し板に比べて背景光を２／３
〜１／２にすることができ、また、上記のような計数を
行なうことにより、測定の都度異なる背景の中から、微
小かつ微弱な発光点を検出することができる。With the above device configuration, since the press plate for adhering the film to the image pickup input surface is subjected to the matte black treatment, the background light emitted on the film is absorbed, and the background light reflected light is reduced, 2/3 the background light compared to the conventional mirror-finished push plate
It is possible to halve, and by performing the above counting, it is possible to detect a minute and weak light emitting point from the background that is different each time measurement is performed.
【００１３】さらに、上述の式（１），（２）を用い
て、発光基点の菌数の重みを計算することが可能であ
り、簡単な計算によって、細菌１個からの微弱な発光基
点を正確に検出することができる。Furthermore, it is possible to calculate the weight of the number of bacteria at the luminescent starting point by using the above equations (1) and (2), and the weak luminescent starting point from one bacterium can be calculated by a simple calculation. Can be accurately detected.
【００１４】[0014]
【実施例】以下、本発明を実施例に基づき説明する。図
１は本発明の細菌検査装置の構成について、それぞれ点
線で囲った測定部１９の構成を示す一部断面図と、測定
部１９からの画像信号を画像処理して菌数を計数するた
めの画像処理部２０のブロック図を含む模式図であり、
図１０と共通する部分に同一符号を用いている。EXAMPLES The present invention will be described below based on examples. FIG. 1 is a partial cross-sectional view showing a configuration of a measuring unit 19 surrounded by a dotted line, and a configuration of a bacteria inspection apparatus of the present invention, and image processing of an image signal from the measuring unit 19 for counting the number of bacteria. FIG. 3 is a schematic diagram including a block diagram of an image processing unit 20 ,
The same parts as those in FIG. 10 are designated by the same reference numerals.
【００１５】図１において、測定部１９では、あらかじ
め一定量の試料を濾過して細菌を付着させ、所定の前処
理を施した膜１を細菌付着面を下にして、高感度撮像手
段１０の光入力部１３に設置する。膜１上面から発光開
始のための試薬を滴下し、膜１に付着する面（上面）
に、艶消し黒色処理面２１を持つ押し板１４ａおよび遮
光蓋１５を被せ、膜１を押圧する。高感度撮像手段１０
には、イメージインテンシファイアーを組み込んだ２次
元光子計数管を用い、また、艶消し黒色処理面２１は、
押し板１４ａにアルミニウムを用い、黒色アルマイト処
理を施したものである。高感度撮像手段１０の出力部２
２のフォトン画像を、カメラレンズ１６を備えたＣＣＤ
カメラ１７で撮像して、ビデオ信号２３として出力す
る。In FIG. 1, in the measuring unit 19 , a predetermined amount of sample is filtered in advance to attach bacteria, and the membrane 1 which has been subjected to a predetermined pretreatment is placed with the bacteria-adhering surface facing down, so that the high-sensitivity imaging means 10 can be operated. It is installed in the optical input unit 13. A surface (upper surface) on which a reagent for starting light emission is dropped from the upper surface of the film 1 and adheres to the film 1.
Then, the pressing plate 14a having the matt black treated surface 21 and the light shielding lid 15 are covered, and the film 1 is pressed. High-sensitivity imaging means 10
Is a two-dimensional photon counter incorporating an image intensifier, and the matte black treated surface 21 is
The pressing plate 14a is made of aluminum and is black alumite treated. Output unit 2 of high-sensitivity imaging means 10
2 photon images, CCD with camera lens 16
The image is taken by the camera 17 and output as a video signal 23.
【００１６】画像処理部２０では、このビデオ信号２３
が、コンピュータ２４によりコントロールされた画像積
算手段２５に入力され、デジタル化された後、あらかじ
め設定されたフレーム数が画像積算される。この積算画
像は、画像処理手段２６，コンピュータ２４および画像
記憶手段２７により、移動平均化，画面間演算，２値
化，画像計算の各処理を行なう。ＣＲＴ２８は計算結果
の表示、ビデオモニター２９は測定中の画像の監視、ビ
デオプリンター３０は画像の記録を行なうものである。In the image processor 20 , the video signal 23
Is inputted to the image integrating means 25 controlled by the computer 24, digitized, and then the image is integrated by a preset number of frames. The integrated image is processed by the image processing means 26, the computer 24, and the image storage means 27 to perform moving averaging, inter-screen calculation, binarization, and image calculation. The CRT 28 displays the calculation result, the video monitor 29 monitors the image being measured, and the video printer 30 records the image.
【００１７】ここで、移動平均とは、５１５×５１２の
画素と、各画素の１６ピットの輝度データからなる画像
データについて、各画素を中心に、すべての画素につい
て要素１からなるｍ×ｍ（但し、ｍは奇数）の正方マト
リックスを乗じ、総和をとり、マトリックス数即ちｍ2
で割り算し、中心画素の輝度データとすることを意味す
る。この操作は、一般にｍ×ｍ単純平滑化と呼ばれるも
のであり、ｍ×ｍより小さい輝度の振幅を減少させる効
果がある。Here, the moving average is m × m (consisting of element 1 for all pixels, centering on each pixel, of image data consisting of 515 × 512 pixels and luminance data of 16 pits of each pixel. However, m is an odd number) and the sum is calculated by multiplying by a square matrix, that is, m 2
It means that the luminance data of the central pixel is obtained by dividing by. This operation is generally called m × m simple smoothing, and has the effect of reducing the amplitude of luminance smaller than m × m.
【００１８】画面間演算とは、二つの画像同士の算術演
算を行なうことを意味し、本発明では特に減算を用い
る。２値化は、所定の値以上の各画素の輝度データを最
高輝度値（Ｈｉｇｈ）に変換し、それより小さい輝度デ
ータの各画素の輝度データを最小輝度値（Ｌｏｗ）に変
換する操作である。本実施例では、最高輝度データはＦ
ＦＦＦ（１６進）即ち６５５３５（１０進）、最小輝度
データは０である。Inter-screen operation means performing an arithmetic operation between two images, and in the present invention, subtraction is particularly used. The binarization is an operation of converting the brightness data of each pixel having a predetermined value or more into the maximum brightness value (High) and converting the brightness data of each pixel having the smaller brightness data into the minimum brightness value (Low). . In this embodiment, the highest brightness data is F
FFF (hexadecimal), that is, 65535 (decimal), the minimum luminance data is 0.
【００１９】画像計算とは、上述のような２値化された
画像データについて、各画素の属性（ＨｉｇｈまたはＬ
ｏｗ）の隣接関係に着目して空間的に分類した後、それ
らの群についての幾何学的らパラメータを求め、または
それらを統計処理することを意味し、本発明では、後述
するように、各群の構成画素数と対応する２値化前の画
像の輝度データによる重み付け計数を行なう。Image calculation means the attribute (High or L) of each pixel in the binarized image data as described above.
ow) is spatially classified by focusing on the adjacency relation, and then geometrical parameters for these groups are obtained or statistically processed. In the present invention, as will be described later, Weighting counting is performed by the luminance data of the image before binarization corresponding to the number of pixels constituting the group.
【００２０】図２は、上述した構成の装置を用いて、細
菌の発光画像を処理する手順の流れ図を示したものであ
り、図１のコンピュータ２４のプログラムとして実現す
ることができる。以下に図１を併用参照して説明する。
まず、図１のビデオ信号２３は、画像積算手段２５によ
ってデジタル化されて、所定のフレーム数が連続して積
算され、画像積算手段２５の内部に設けられた図示して
ない画像記憶用フレームメモリーに記憶される。この画
像データＡは、マトリックスサイズの異なる２種類の移
動平均化が施される。即ち、細菌による発光基点より小
さいマトリックスサイズで移動平均化を行ない、ノイズ
を除去した画像をＢとし、細菌による発光基点より大き
いマトリックスサイズで移動平均化して、細菌による発
光基点を除去した背景画像をＣとし、別々に画像記憶手
段２７に記憶する。このとき、これら２種類のマトリッ
クスサイズは、図１に示した測定部の光学的な倍率や、
解像度によって異なる。したがって、あらかじめ細菌に
よる発光基点を同定し、画像上での大きさを画像解析す
る必要がある。FIG. 2 shows a flow chart of a procedure for processing a luminescent image of bacteria using the apparatus having the above-mentioned configuration, which can be realized as a program of the computer 24 in FIG. A description will be given below with reference to FIG.
First, the video signal 23 shown in FIG. 1 is digitized by the image accumulating means 25 and a predetermined number of frames are successively accumulated, and a frame memory (not shown) for image storage provided inside the image accumulating means 25 is provided. Memorized in. The image data A is subjected to two types of moving averages having different matrix sizes. That is, moving average is performed with a matrix size smaller than the luminescent origin of bacteria, noise-removed image is B, and moving average is performed with a matrix size larger than luminescent origin of bacteria to remove background image of luminescent origin of bacteria. C and separately stored in the image storage means 27. At this time, these two types of matrix sizes are the optical magnification of the measurement unit shown in FIG.
Depends on the resolution. Therefore, it is necessary to identify the luminescent base point of bacteria in advance and perform image analysis of the size on the image.
【００２１】次に、これら二つの画像Ｂ，Ｃについて画
面間減算（Ｂ−Ｃ）を行なう。結果として得られる最終
処理画像Ｄは、あらかじめ設定された輝度しきい値によ
って２値化され、２値画像Ｅを得ることができる。図示
は省略したが、２値画像Ｅにおいて隣り合うＨｉｇｈレ
ベルの画素同士を、一つの群として登録する手順を施し
た後、上述のノイズ除去のための移動平均化で除去しき
れなかったノイズ、即ち、細菌による発光基点とは考え
られないような小さい画素数の群を、ノイズて無視また
は除去する。Next, inter-screen subtraction (B-C) is performed on these two images B and C. The final processed image D obtained as a result is binarized by a preset brightness threshold value, and a binary image E can be obtained. Although illustration is omitted, after performing a procedure of registering high level pixels adjacent to each other in the binary image E as one group, noise that cannot be completely removed by the moving average for noise removal described above, That is, a group having a small number of pixels, which is not considered to be a light emission origin of bacteria, is ignored as noise and is removed.
【００２２】残った群について、ラベルを与えた後、各
群の重み、即ち、各群に含まれる細菌数を後述する方法
によって見積もり、合計細菌数を計算する。図３（ａ）
〜（ｄ）は、前述の移動平均処理によって背景光が除去
される過程を、画像の１次元輝度波形により示した線図
であり、それぞれ図３（ａ）は原画像の１次元輝度波
形、図３（ｂ）はノイズ除去波形、図３（ｃ）は背景む
ら波形、図３（ｄ）は最終処理波形を表わしている。After giving labels to the remaining groups, the weight of each group, that is, the number of bacteria contained in each group is estimated by the method described later to calculate the total number of bacteria. Figure 3 (a)
3D are diagrams showing the process of removing the background light by the moving average processing described above by a one-dimensional luminance waveform of the image, and FIG. 3A is a one-dimensional luminance waveform of the original image, 3B shows a noise removal waveform, FIG. 3C shows a background uneven waveform, and FIG. 3D shows a final processed waveform.
【００２３】図３（ａ）の曲線３１は原画像の１次元輝
度波形を示し、前述の積算画像Ａにおいて、二つの細菌
による発光基点の中心を通る直線上の輝度データをグラ
フ化したものである。波形３１は、二つの発光基点によ
るピーク３１ａ．３１ｂと、発光試薬のむらによる比較
的大きなゆらぎと、細かいノイズを含んでおり、図１に
示した測定部１９の光学系によって生ずる感度むら波形
３２に従って、全体が湾曲した形状を呈している。した
がって、この段階で、一定レベルのしきい値で２値化す
るのが困難であることは明らかである。そこで、まず、
細菌による発光基点のピーク幅ｓより小さいマトリック
スで移動平均化すると、図３（ｂ）のノイズ除去波形３
３に示すように、細かいノイズが除去された滑らかな波
形が得られる。また、波形３１より大きなマトリックス
で移動平均化すると、図３（ｃ）に示す如く、細菌によ
る発光基点が消え、比較的大きなうねりが抽出された背
景むら波形３４を得ることができる。これら二つの波形
３３，３４を減算したものが図３（ｄ）に示す最終処理
波形３５であり、先に述べた細かいノイズ成分、発光試
薬のむらによるゆらぎ、および感度むらが解消されて、
細菌による発光基点が一定レベルの信号として抽出され
ることがわかる。[0023] Curve 31 in FIG. 3 (a) shows a one-dimensional luminance waveform of an original image, which in the integrated image A above, was graphed luminance data on the straight line passing through the center of the light-emitting base by two bacteria Is. The waveform 31 is the peak 31a. 31b, a relatively large fluctuation due to the unevenness of the luminescent reagent, and a fine noise are included, and the entire shape is curved according to the sensitivity unevenness waveform 32 generated by the optical system of the measurement unit 19 shown in FIG. Therefore, at this stage, it is obvious that it is difficult to perform binarization with a constant level threshold value. So first,
When moving averaging is performed using a matrix smaller than the peak width s of the light emission origin of bacteria, the noise removal waveform 3 in FIG.
As shown in FIG. 3, a smooth waveform with fine noise removed is obtained. Also, when moving average is performed using a matrix larger than the waveform 31, as shown in FIG. 3C, a background unevenness waveform 34 in which a luminescent origin of bacteria disappears and a relatively large undulation is extracted can be obtained. The final processed waveform 35 shown in FIG. 3D is obtained by subtracting these two waveforms 33 and 34, and the fine noise component, the fluctuation due to the unevenness of the luminescent reagent, and the unevenness in sensitivity described above are eliminated.
It can be seen that the luminescent origin of bacteria is extracted as a signal of a certain level.
【００２４】このように、本発明の方法は、比較的一般
的な画像処理手順を組み合わせることにより、有効な背
景画像処理補正を行なうことができるという点に大きな
特徴を有する。このような要素となる画像処理手順は、
高速化されたハードウェアーやアルゴリズムが普及して
おり、これを利用することによって、全体の処理速度の
高速化が容易であるという利点を持っている。As described above, the method of the present invention is characterized in that effective background image processing correction can be performed by combining relatively common image processing procedures. The image processing procedure that becomes such an element is
High-speed hardware and algorithms have become widespread, and the use of these has the advantage that it is easy to increase the overall processing speed.
【００２５】以上、背景光の画像処理上の除去方法につ
いて説明したが、本来、背景光は、測定部において低減
した方がよいことは明らかである。以下では、光学的な
背景光の除去方法について、従来との比較において、図
４（ａ）〜（ｃ）の模式断面図を参照して説明するが、
それぞれ図４（ａ）は押し板を用いない場合、図４
（ｂ）は、図１０に示した従来の押し板１４を用いた場
合、図４（ｃ）は、図１に示した本発明における艶消し
黒色処理面１８を有する押し板１４ａを適用した場合の
膜内発光状態を表わす。また、各図とも光は矢印で示し
てある。Although the method of removing the background light in the image processing has been described above, it is obvious that the background light should be reduced in the measuring section. Hereinafter, an optical background light removal method will be described with reference to the schematic cross-sectional views of FIGS. 4A to 4C in comparison with a conventional method.
FIG. 4 (a) shows the case of FIG.
FIG. 4 (b) is a case where the conventional pressing plate 14 shown in FIG. 10 is used, and FIG. 4 (c) is a case where the pressing plate 14a having the matte black treated surface 18 of the present invention shown in FIG. 1 is applied. Represents the light emission state in the film. In addition, light is indicated by an arrow in each drawing.
【００２６】図４（ａ）は、付着細菌３６の付着面３７
を下にして発光させた膜１の模式断面図であり、付着細
菌３６からの光は、膜内散乱光３８と膜外散乱光３９が
あり、膜外散乱光３９が図１の高感度撮像手段１０の光
入力部１３に到達することになる。また、膜１内に含浸
した発光試薬の自家発光、即ち背景光４０は、膜１の上
面、下面とも等しく放出され、その発光量は、膜１内の
発光試薬の含浸量に比例する。したがって、背景光４０
を弱くし、付着細菌３６からの発光量を相対的に大きく
する必要がある。そこで、従来は図４（ｂ）に示すよう
に、押し板１４を用いて膜１の上面から押圧することに
より、膜１内もしくは膜１と光入力部１３の間の発光試
薬の液量を少なくし、背景光４０を低減化していた。し
かし、このような方法では、押し板１４の表面は従来鏡
面仕上げになっており、図４（ｂ）に示すように、背景
光反射光４１が膜１内部を透過して入力部１３に到達
し、背景光４０を増大させ、しかも発光試薬の膜１内の
含浸量のむらを大きく反映させている。FIG. 4A shows an attachment surface 37 of the attachment bacteria 36.
FIG. 2 is a schematic cross-sectional view of the film 1 which is made to emit light with the downward direction. Light from the adhering bacteria 36 includes intra-membrane scattered light 38 and extra-membrane scattered light 39, and the extra-membrane scattered light 39 is highly sensitive imaging in FIG. It will reach the optical input 13 of the means 10. Further, the self-luminous light of the luminescent reagent impregnated in the film 1, that is, the background light 40 is emitted equally to the upper surface and the lower surface of the film 1, and the amount of luminescence is proportional to the impregnated amount of the luminescent reagent in the film 1. Therefore, the background light 40
Is required to be weakened, and the amount of light emitted from the adherent bacteria 36 needs to be relatively increased. Therefore, conventionally, as shown in FIG. 4B, by pressing from the upper surface of the membrane 1 using a pressing plate 14, the liquid amount of the luminescent reagent in the membrane 1 or between the membrane 1 and the light input section 13 is reduced. The background light 40 was reduced. However, in such a method, the surface of the push plate 14 is conventionally mirror-finished, and as shown in FIG. 4B, the background light reflected light 41 passes through the inside of the film 1 and reaches the input unit 13. However, the background light 40 is increased, and the unevenness of the impregnated amount of the luminescent reagent in the film 1 is largely reflected.
【００２７】これに対して、本発明では図４（ｃ）に示
すように、図１の艶消し黒色処理面１８を有する押し板
１４ａを用いて、この黒色処理面１８が膜１の上面と接
するようにし、膜１面上に放射される背景光４０を吸収
することにより、背景光反射光４１を小さくし、背景光
４０のレベルを鏡面の押し板１４に比べて、約２／３〜
１／２にすることができた。On the other hand, in the present invention, as shown in FIG. 4 (c), the pressing plate 14a having the matte black processed surface 18 of FIG. 1 is used, and this black processed surface 18 is the upper surface of the film 1. By making them contact with each other and absorbing the background light 40 radiated on the surface of the film 1, the background light reflected light 41 is reduced, and the level of the background light 40 is about 2/3 of that of the push plate 14 having a mirror surface.
I was able to halve it.
【００２８】以上述べてきた如く、本発明では、不均一
な背景光に含まれる細菌による発光点を画像的に抽出す
るために、新しい簡便な画像処理方法と光学的に有利な
測定部の構造を発明するに至ったものである。次に、確
実に検出されるようになった細菌による発光点を、画像
計算により正確に算出するには、菌の重なりを考慮し
て、一つの発光基点に含まれる細菌の数を推定しなけれ
ばならない。図５（ａ），（ｂ）は、菌が重なって検出
された２値画像の例を示す模式図であり、図５（ａ）は
２値化画面の一部を示す模式図、図５（ｂ）は２値化前
の輝度波形図である。図５（ａ）のように、発光基点４
２はその広がりからみれば、２個と考えられるが、直線
Ｐ上の２値化前の輝度波形４３からは、図５（ｂ）のよ
うに３個であることがわかる。このように、本来発光基
点に含まれる菌数は、基点に含まれる２値化前の輝度デ
ータを２次元的に積分し、菌１個当たりの輝度積分値で
除算すればよいことが容易に推測される。As described above, in the present invention, a new simple image processing method and an optically advantageous structure of the measuring unit are used in order to image-wise extract the light emission points of bacteria contained in the non-uniform background light. Was invented. Next, in order to accurately calculate the luminescent points due to bacteria that have been reliably detected by image calculation, the number of bacteria included in one luminescent base point must be estimated in consideration of the overlapping of bacteria. I have to. 5 (a) and 5 (b) are schematic diagrams showing an example of a binary image in which bacteria are overlapped and detected, and FIG. 5 (a) is a schematic diagram showing a part of the binarized screen, FIG. (B) is a luminance waveform diagram before binarization. As shown in FIG. 5A, the light emission starting point 4
Although 2 is considered to be 2 in view of its spread, it can be seen from the luminance waveform 43 before binarization on the straight line P that there are 3 as shown in FIG. 5B. As described above, the number of bacteria originally included in the luminescent base point can be easily obtained by two-dimensionally integrating the brightness data before binarization included in the base point and dividing by the brightness integrated value per one bacterium. Guessed.
【００２９】しかし、この方法では、基点の全てに亘っ
て積分操作を要するために、処理に時間がかかる。そこ
で、本発明では、細菌１個の発光基点の輝度波形のピー
ク値がほぼ一定していること、この波形がほぼ完全に一
致して重ならない限り、ピーク値は２倍にならないこと
に着眼し、次のような方法により、１個の発光基点に含
まれる細菌数を計算することにした。即ち、高輝度画素
群ｉに関する２値化前の群の最高輝度値をＩmax ，２値
化後の群の構成画素数をＳi ，菌単体当たりの最高輝度
値をＩS ，菌単体当たりの平均画素数をＳS とし、関数
ｆを小数点以下四捨五入するものとし、画素群ｉについ
ての重みＷi を式（１）で計算し、 Ｗi ＝ｆ（Ｓi ／ＳS ）＋ｆ（Ｉmax ／ＩS ）−１ （１） 画像中高輝度群総数をｎとして、式（２）から総菌数Ｎ
を計算することにより、 発光基点の輝度レベルと、構成画素数の二つの変数から
補正することにした。ここで、重み計算式（１）で、画
素数と輝度値の除算結果を四捨五入するのは、菌１個当
たりの構成画素数，最高輝度値のばらつきを考慮したか
らである。However, this method requires a long processing time because the integration operation is required over all the base points. Therefore, in the present invention, it is focused on that the peak value of the luminance waveform at the luminescent origin of one bacterium is substantially constant, and that the peak value does not double unless the waveforms almost completely coincide and overlap. It was decided to calculate the number of bacteria contained in one luminescent origin by the following method. That is, the maximum brightness value of the group before binarization regarding the high brightness pixel group i is I max , the number of constituent pixels of the group after binarization is S i , the maximum brightness value per bacterium alone is I S , and per bacterium alone Let S S be the average number of pixels, and the function f be rounded off after the decimal point. The weight W i for the pixel group i is calculated by equation (1), and W i = f (S i / S S ) + f (I max / I S ) -1 (1) From the formula (2), the total number of bacteria N
By calculating It was decided to correct from two variables, the brightness level of the light emission base point and the number of constituent pixels. In the weight calculation formula (1), the division result of the number of pixels and the luminance value is rounded off because the number of constituent pixels per one bacterium and the variation in the maximum luminance value are taken into consideration.
【００３０】これを具体的に幾つかの代表的な二つの菌
の重なり方について、図６，図７を参照して説明する。
図６（ａ）は、発光基点の重なり方が小さい場合を示す
模式図であり、図６（ｂ）は、このときの輝度波形図で
ある。図７（ａ）は、発光基点の重なり方が大きい場合
を示す模式図であり、図７（ｂ）は、このときの輝度波
形図である。図７（ｂ）では各基点の波形を点線で、実
測波形を実線で表わしてある。This will be specifically described with reference to FIGS. 6 and 7 as to how some representative two bacteria overlap.
FIG. 6A is a schematic diagram showing a case where the light emitting base points overlap little, and FIG. 6B is a luminance waveform diagram at this time. FIG. 7A is a schematic diagram showing a case where the light emission base points overlap with each other, and FIG. 7B is a luminance waveform diagram at this time. In FIG. 7B, the waveform at each base point is represented by a dotted line, and the measured waveform is represented by a solid line.
【００３１】従来の構成画素数のみの判定は、図６では
式（１）の右辺第１項は、ｆ（Ｓi／ＳS ）＝２であ
り、図７では同様にして式（１）の右辺第１項は、ｆ
（Ｓi ／ＳS ）＝１である。しかし、画素の大きさおよ
びこれらの変数の自由度を考慮した式（１）で計算され
る重みＷi は、図６，図７のいずれの場合も２であり、
実際の菌数と一致する。例えば、仮に図６，図７の場合
に、さらに１個の菌が上記の二つの重なり方で重なった
としても、同様の結果が得られることは明らかである。In the conventional determination of only the number of constituent pixels, in FIG. 6, the first term on the right side of the equation (1) is f (S i / S S ) = 2, and in FIG. The first term on the right side of is f
(S i / S S ) = 1. However, the weight W i calculated by the equation (1) considering the pixel size and the degrees of freedom of these variables is 2 in both cases of FIGS. 6 and 7,
It matches the actual number of bacteria. For example, in the case of FIGS. 6 and 7, it is apparent that the same result can be obtained even if one bacterium is overlapped by the above-mentioned two overlapping manners.
【００３２】このように、本発明の方法によれば、発光
基点の２値化前の最高輝度値と、２値化後構成画素数か
ら、簡単な演算によって発光基点に含まれる菌数を正確
に計算することができる。As described above, according to the method of the present invention, the number of bacteria contained in the light-emitting base point can be accurately calculated by a simple calculation from the maximum luminance value of the light-emitting base point before binarization and the number of constituent pixels after binarization. Can be calculated to
【００３３】[0033]
【発明の効果】従来、微小でかつ微弱な発光基点をむら
のある背景画像から自動的に抽出するためには、一定の
背景画像を必要とするか、移動２値化など特殊用途向け
で一般には使用することができないアルゴリズムを用い
る必要があったが、本発明の装置と方法によれば、測定
の都度異なる背景の中から、微小でかつ微弱な発光基点
を検出することが、移動平均化（単純平滑化），画面間
減算，２値化など画像処理としては、汎用的な方法を組
み合わせて行なうことが可能であり、市販の汎用画像処
理システムで容易に実現することができ、しかも処理が
高速である。したがって、この画像処理方法は、細菌検
査装置だけでなく、広く種々の画像処理に利用すること
ができる。EFFECTS OF THE INVENTION Conventionally, in order to automatically extract a minute and weak emission base point from a background image having unevenness, a constant background image is required or is generally used for special purposes such as moving binarization. However, according to the apparatus and method of the present invention, it is possible to detect a minute and weak emission base point from different backgrounds each time measurement is performed by moving averaging. Image processing such as (simple smoothing), inter-screen subtraction, and binarization can be performed by combining general-purpose methods, which can be easily realized by a commercially-available general-purpose image processing system. Is fast. Therefore, this image processing method can be used not only for the bacteria inspection device but also for various image processing.
【００３４】また、撮像入力面に膜を密着させる細菌検
査装置で、その膜面の押し板を艶消し黒色処理を施すこ
とにより、背景光が従来の鏡面仕上げの押し板に比べ
て、２／３〜１／２と著しく低減される。さらに、従
来、菌が凝集し、または菌が膜上で画像分解能以下の近
接した位置に付着すると、実数値に比べ計数値が小さく
なるという欠点があったが、本発明の方法によれば、簡
単に発光基点の菌数の重みを計算することが可能であ
り、このように、画像処理的にかつ光学的に、背景光を
低減することができ、発光基点に含まれる菌数を、簡単
に計算することができるようになったため、細菌１個か
らの微弱な発光基点を正確に自動的に検出することが可
能となった。In addition, in a bacteria inspection device in which a film is brought into close contact with the image pickup input surface, the background light is 2 / thick as compared with a conventional mirror-finished pressing plate by applying a matte black treatment to the film pressing surface. It is significantly reduced to 3 to 1/2. Further, conventionally, when the bacteria are aggregated, or the bacteria are attached to the film at a position close to or below the image resolution, there is a drawback that the count value becomes smaller than the real value, but according to the method of the present invention, It is possible to easily calculate the weight of the number of bacteria at the luminescent origin, and in this way, the background light can be reduced optically and optically, and the number of bacteria contained in the luminescent origin can be easily calculated. Since it has become possible to calculate, it has become possible to accurately and automatically detect a weak luminescent base point from one bacterium.
【００３５】これらのことから、本発明の装置と方法を
適用することにより、従来、細菌検査装置で一般的に用
いられているコロニー計数法に代わって、数分〜数十分
の時間で正確な検査が可能となり、細菌検出から製造ラ
インへのフィードバックが迅速となり、製品の歩留り
や、安全性の向上を格段に飛躍させることができる。From the above, by applying the apparatus and method of the present invention, the colony counting method, which has been generally used in the conventional bacterial inspection apparatus, can be replaced with an accurate time of several minutes to several tens of minutes. Various tests can be performed, and the feedback from the detection of bacteria to the production line is speeded up, which can dramatically improve the yield and safety of products.
【図１】本発明の細菌検査装置の構成を示す模式図FIG. 1 is a schematic diagram showing the configuration of a bacteria inspection device of the present invention.
【図２】本発明の細菌検査装置を用いて細菌の発光画像
を処理する手順の流れ図FIG. 2 is a flow chart of a procedure for processing a luminescence image of bacteria using the bacteria inspection apparatus of the present invention.
【図３】移動平均処理によって背景光が除去される過程
を示し、それぞれ（ａ）は原画像の１次元輝度波形図，
（ｂ）はノイズ除去波形図，（ｃ）は背景むら波形図，
（ｄ）は最終処理波形図FIG. 3 shows a process in which background light is removed by moving average processing, and (a) is a one-dimensional luminance waveform diagram of an original image,
(B) is a noise elimination waveform diagram, (c) is a background uneven waveform diagram,
(D) is the final processed waveform diagram
【図４】光学的な背景光の除去方法を従来との比較にお
いて示し、（ａ）は膜のまま、（ｂ）は従来の押し板を
用いた場合、（ｃ）は、本発明における艶消し黒色処理
面を有する押し板を適用した場合のそれぞれ膜内発光状
態を表わす模式断面図FIG. 4 shows an optical background light removal method in comparison with a conventional one, in which (a) is a film as it is, (b) is a conventional pressing plate, and (c) is a gloss in the present invention. Schematic cross-sectional views showing the light emission state in the film when a pressing plate having an erased black treated surface is applied.
【図５】菌が重なって検出された場合を示し、（ａ）は
２値化画面の一部を示す模式図、（ｂ）は２値化前の輝
度波形図5A and 5B show a case where bacteria are detected in an overlapping manner, FIG. 5A is a schematic diagram showing a part of a binarized screen, and FIG. 5B is a luminance waveform diagram before binarization.
【図６】発光基点の重なり方を示し、（ａ）は重なり方
の小さい場合を示す模式図、（ｂ）はそのときの輝度波
形図6A and 6B are schematic diagrams showing how the light emission base points are overlapped, where FIG. 6A is a schematic diagram showing a case where the overlap is small, and FIG.
【図７】発光基点の重なり方を示し、（ａ）は重なり方
の大きい場合を示す模式図、（ｂ）はそのときの輝度波
形図7A and 7B are schematic diagrams showing how the light emission base points overlap, where FIG. 7A is a schematic diagram showing a case where the light emission base points are large, and FIG.
【図８】ＡＴＰ発光法による生菌計数の過程を示し、
（ａ）は発光反応前の状態、（ｂ）は試薬を注入した状
態、（ｃ）は発光状態を説明するための各模式図FIG. 8 shows the process of counting viable bacteria by ATP luminescence method,
(A) is a state before a luminescence reaction, (b) is a state in which a reagent is injected, (c) is a schematic diagram for explaining a luminescence state
【図９】細菌の発光点を検出する装置の測定部の要部構
成を示す模式図FIG. 9 is a schematic diagram showing a configuration of a main part of a measuring unit of a device for detecting a light emitting point of bacteria.
【図１０】図９の装置を改良した測定部の要部構成を示
す模式図FIG. 10 is a schematic diagram showing a configuration of a main part of a measuring section obtained by improving the apparatus shown in FIG.
１ 膜 １ａ 膜表面 １ｂ 膜裏面 ２ 光ファイバープレート ２ａ 入力面 ３ 液膜層 ４ ＡＴＰ ５ 細胞膜 ６ ＡＴＰ抽出液 ７ 発光 ８ 付着細菌 ９ カメラレンズ １０ 高感度撮像手段 １１ 入力面 １２ ケーブル １３ 光入力部 １４ 押し板 １４ａ 押し板 １５ 遮光蓋 １６ カメラレンズ １７ ＣＣＤカメラ １８ 画像信号１９ 測定部２０ 画像処理部 ２１ 艶消し黒色処理面 ２２ 出力部 ２３ ビデオ信号 ２４ コンピュータ ２５ 画像積算手段 ２６ 画像処理手段 ２７ 画像記憶手段 ２８ ＣＲＴ波形曲線 ２９ ビデオモニター ３０ ビデオプリンター ３１ 原画像の１次元輝度波形 ３１ａ ピーク ３１ｂ ピーク ３２ 感度むら波形 ３３ ノイズ除去波形 ３４ 背景むら波形 ３５ 最終処理波形 ３６ 付着細菌 ３７ 細菌付着面 ３８ 膜内散乱光 ３９ 膜外散乱光 ４０ 背景光 ４１ 背景光反射光 ４２ 発光基点 ４３ ２値化前の輝度波形1 Membrane 1a Membrane Surface 1b Membrane Backside 2 Optical Fiber Plate 2a Input Surface 3 Liquid Membrane Layer 4 ATP 5 Cell Membrane 6 ATP Extraction Liquid 7 Emission 8 Adherent Bacteria 9 Camera Lens 10 High Sensitivity Imaging Means 11 Input Surface 12 Cable 13 Optical Input Section 14 Push Plate 14a Push plate 15 Light-shielding lid 16 Camera lens 17 CCD camera 18 Image signal 19 Measuring section 20 Image processing section 21 Matte black processing surface 22 Output section 23 Video signal 24 Computer 25 Image accumulating means 26 Image processing means 27 Image storing means 28 CRT waveform curve 29 Video monitor 30 Video printer 31 One-dimensional luminance waveform of original image 31a Peak 31b Peak 32 Sensitivity uneven waveform 33 Noise removal waveform 34 Background uneven waveform 35 Final processing waveform 36 Adhering bacteria 37 Bacterial adhering surface 38 Intramembrane scattering light 39 Extra-membrane scattered light 40 background light 41 background light reflected light 42 emission base point 43 luminance waveform before binarization
───────────────────────────────────────────────────── フロントページの続き (51)Int.Cl.6 識別記号 庁内整理番号 ＦＩ 技術表示箇所 Ｇ０１Ｎ 21/78 Ｄ 9408−2Ｊ 33/569 Ｂ 9015−2Ｊ (72)発明者 豊島 英文 神奈川県川崎市川崎区田辺新田１番１号 富士電機株式会社内 (72)発明者 佐々木 正一 埼玉県戸田市川岸１丁目４番９号 オルガ ノ株式会社総合研究所内─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. 6 Identification code Internal reference number FI Technical indication location G01N 21/78 D 9408-2J 33/569 B 9015-2J (72) Inventor Hidefumi Toyoshima Kawasaki, Kanagawa Prefecture 1-1 Tanabe Nitta, Kawasaki-ku, Ichi Fuji Electric Co., Ltd. (72) Inventor, Shoichi Sasaki 1-4-9 Kawagishi, Toda City, Saitama Organo Research Institute
Claims (3)
した細菌を所定の試薬を用いて発光反応させ、その発光
画像を高感度撮像手段により撮像して細菌数を測定する
細菌検査装置であって、 結像面に光ファイバープレートを備えた高感度撮像手段
の入力面に細菌付着面が接するように載置した膜の裏面
から、表面に艶消しの黒色処理を施した押し板によりこ
の膜を押圧する手段を有する測定部、および撮像して得
られた菌に対応する複数の点状の高輝度画素群を含む積
算画像を所定のサンプル数で移動平均化する平均化処理
手段と、２種類の画面の減算を行なう画面間演算処理手
段と、画像の所定の領域を所定のしきい値で２値化する
画像２値化手段と、２値化された画像の高輝度画素群を
群毎に計数する手段とを有する画像処理部を備えること
を特徴とする細菌検査装置1. A bacteria inspection apparatus for measuring the number of bacteria by allowing a predetermined amount of a sample to be filtered through a membrane to cause bacteria to undergo a luminescence reaction using a predetermined reagent and imaging the luminescence image by a highly sensitive imaging means. Then, from the back side of the film placed so that the bacteria adhering surface is in contact with the input surface of the high-sensitivity imaging means equipped with an optical fiber plate on the imaging surface, this film is applied by a push plate with a matt black treatment on the surface. A measuring unit having a means for pressing, and an averaging processing means for moving and averaging an integrated image including a plurality of dot-shaped high-brightness pixel groups corresponding to the bacteria obtained by imaging with a predetermined number of samples; Inter-screen calculation processing means for performing subtraction of different types of screens, image binarization means for binarizing a predetermined area of an image with a predetermined threshold value, and a group of high-luminance pixels of the binarized image Equipped with an image processing unit having means for counting for each Bacteria inspection device characterized by
なう方法において、撮像により得られた菌に対応する複
数の点状の高輝度画素群を含む積算画像（Ａ）を、高輝
度画素群より少ないサンプル数で移動平均化して画像
（Ｂ）を得てこれを記憶し、高輝度画素群より多いサン
プル数で移動平均化して画像（Ｃ）を得、画像（Ｂ）か
ら画像（Ｃ）を対応する各画素毎に減算して画像（Ｄ）
を得、画像（Ｄ）の所定の領域を所定のしきい値で２値
化し、２値化された画像の高輝度画素群を群毎に計数す
ることを特徴とする細菌検査方法。2. A method for conducting a bacteria test using the apparatus according to claim 1, wherein an integrated image (A) including a plurality of dot-like high-intensity pixel groups corresponding to a bacterium obtained by imaging is made into a high-intensity image. An image (B) is obtained by moving and averaging with a smaller number of samples than the pixel group, and this is stored, and an image (C) is obtained by moving and averaging with a larger number of samples than the high-brightness pixel group. Image (D) by subtracting C) for each corresponding pixel
And binarizing a predetermined region of the image (D) with a predetermined threshold value, and counting the high-intensity pixel groups of the binarized image for each group.
ｉに関する２値化前の群の最高輝度値をＩmax ，２値化
後の群の構成画素数をＳi ，菌単体当たりの平均輝度値
をＩS ，菌単体当たりの平均画素数をＳS とし、関数ｆ
を小数点以下四捨五入するものとし、画素群ｉについて
の重みＷi を式（１）で計算し、 Ｗi ＝ｆ（Ｓi ／ＳS ）＋ｆ（Ｉmax ／ＩS ）−１ （１） 画像中高輝度群総数をｎとして、式（２）から総菌数Ｎ
を計算することを特徴とする細菌検査方法。 3. The counting method according to claim 2, wherein the maximum brightness value of the high brightness pixel group i before binarization is I max , the number of constituent pixels of the binarized group is S i , and the fungus alone. The average luminance value per unit is I S , the average number of pixels per unit of bacteria is S S , and the function f
Was assumed to round decimal calculates the weight W i for the pixel groups i in the formula (1), W i = f (S i / S S) + f (I max / I S) -1 (1) Image From the formula (2), the total number of bacteria N
A method for examining bacteria, which comprises calculating
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP5185716A JP3029760B2 (en) | 1993-07-28 | 1993-07-28 | Bacterial test equipment and test method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP5185716A JP3029760B2 (en) | 1993-07-28 | 1993-07-28 | Bacterial test equipment and test method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH0744707A true JPH0744707A (en) | 1995-02-14 |
| JP3029760B2 JP3029760B2 (en) | 2000-04-04 |
Family
ID=16175606
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP5185716A Expired - Fee Related JP3029760B2 (en) | 1993-07-28 | 1993-07-28 | Bacterial test equipment and test method |
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| Country | Link |
|---|---|
| JP (1) | JP3029760B2 (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08136546A (en) * | 1994-11-15 | 1996-05-31 | Bio Sensor Kenkyusho:Kk | Method for analyzing substance |
| EP1067199A1 (en) * | 1998-12-28 | 2001-01-10 | Sapporo Breweries Ltd. | Method of counting microorganisms and device for accomplishing the counting |
| US6729448B2 (en) | 2000-10-18 | 2004-05-04 | Tok Bearing Co., Ltd. | Rotary damper |
| USRE38863E1 (en) | 1995-02-03 | 2005-11-01 | Ruy Tchao | Chemotaxis assay procedure |
| JP2010161955A (en) * | 2009-01-13 | 2010-07-29 | Future Univ-Hakodate | Microbiological test system |
| JP2011036188A (en) * | 2009-08-12 | 2011-02-24 | Ihi Corp | Microorganism-detecting device |
| WO2016175269A1 (en) * | 2015-04-28 | 2016-11-03 | デンカ生研株式会社 | Method for collecting microbial antigen |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015093518A1 (en) * | 2013-12-18 | 2015-06-25 | コニカミノルタ株式会社 | Image processing device, pathological diagnosis support system, image processing program, and image processing method |
-
1993
- 1993-07-28 JP JP5185716A patent/JP3029760B2/en not_active Expired - Fee Related
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08136546A (en) * | 1994-11-15 | 1996-05-31 | Bio Sensor Kenkyusho:Kk | Method for analyzing substance |
| USRE38863E1 (en) | 1995-02-03 | 2005-11-01 | Ruy Tchao | Chemotaxis assay procedure |
| USRE40747E1 (en) | 1995-02-03 | 2009-06-16 | Ruy Tchao | Chemotaxis assay procedure |
| EP1067199A1 (en) * | 1998-12-28 | 2001-01-10 | Sapporo Breweries Ltd. | Method of counting microorganisms and device for accomplishing the counting |
| EP1067199A4 (en) * | 1998-12-28 | 2006-09-27 | Sapporo Breweries | Method of counting microorganisms and device for accomplishing the counting |
| US6729448B2 (en) | 2000-10-18 | 2004-05-04 | Tok Bearing Co., Ltd. | Rotary damper |
| JP2010161955A (en) * | 2009-01-13 | 2010-07-29 | Future Univ-Hakodate | Microbiological test system |
| JP2011036188A (en) * | 2009-08-12 | 2011-02-24 | Ihi Corp | Microorganism-detecting device |
| WO2016175269A1 (en) * | 2015-04-28 | 2016-11-03 | デンカ生研株式会社 | Method for collecting microbial antigen |
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| Publication number | Publication date |
|---|---|
| JP3029760B2 (en) | 2000-04-04 |
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