JP2823564B2 - Organism detection device - Google Patents
Organism detection deviceInfo
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- JP2823564B2 JP2823564B2 JP63128521A JP12852188A JP2823564B2 JP 2823564 B2 JP2823564 B2 JP 2823564B2 JP 63128521 A JP63128521 A JP 63128521A JP 12852188 A JP12852188 A JP 12852188A JP 2823564 B2 JP2823564 B2 JP 2823564B2
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- spectral intensity
- spectral
- comparing
- intensity
- measuring
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Description
【発明の詳細な説明】 （発明の属する技術分野） 本発明は生物体の検知装置に関し、特に生物体を特徴
づける特定の波長の反射スペクトルに着目して生物体を
検知する装置に関する。Description: TECHNICAL FIELD The present invention relates to an apparatus for detecting an organism, and more particularly to an apparatus for detecting an organism by focusing on a reflection spectrum of a specific wavelength that characterizes the organism.
（従来の技術） 反射光の分光強度あるいは分光反射率をもとにした物
体識別は従来から見られ、カラーカメラの色分解機能を
利用したRGB色度による特定色物体の検出装置などとし
て実用されている。また最近では色フィルタを使用した
小型の３色分解用半導体素子も見受けられる。(Prior art) Object identification based on the spectral intensity or spectral reflectance of reflected light has been seen in the past, and has been put to practical use as a device for detecting a specific color object based on RGB chromaticity using the color separation function of a color camera. ing. Recently, small-sized three-color separation semiconductor devices using color filters have been found.
物体の種別判定のためには可視領域以外の反射率も有
用な情報として利用され、高空から地表面の利用形態を
調査する場合には、赤外線帯域を含む反射光のスペクト
ル情報が用いられている。例えば文献［鈴木光雄、農業
にみるリモートセンシング技術、センサ技術,Vol.6,No.
1,p32（1986年１月）］では土壌、岩石、水、雪のほか
植生の分光反射率が示されており、特に植生に関して
は、反射率が葉の種類、健康度、含水率の変化を反映す
るものとして農業の分野で利用されている。The reflectance outside the visible region is also used as useful information for determining the type of the object, and when investigating the use form of the ground surface from a high altitude, the spectrum information of the reflected light including the infrared band is used. . For example, see the literature [Mitsuo Suzuki, Remote Sensing Technology in Agriculture, Sensor Technology, Vol. 6, No.
1, p32 (January 1986)] shows the spectral reflectance of vegetation in addition to soil, rocks, water, snow, and especially for vegetation, the reflectance varies with leaf type, health, and moisture content. Is used in the field of agriculture to reflect this.
一方、今後のオフィスや家庭に於けるオートメーショ
ン化では、人間を中心とする生物体を自動検知し、これ
を機能の高度化に役立てたいという希望が強まってい
る。On the other hand, in the automation of offices and homes in the future, there is an increasing desire to automatically detect living organisms, mainly human beings, and to utilize these for advanced functions.
従来生物体の検出のためには波長５〜10ミクロンの赤
外線に感応動作するセンサが用いられることが多い。し
かし、そのセンサは基本的には発熱体の検出を行うもの
であり、必ずしも生物体に限定される特徴を利用してい
るわけではない。このため誤って生物体以外の発熱体を
も検知するといった問題がある。Conventionally, sensors that operate in response to infrared rays having a wavelength of 5 to 10 microns are often used for detecting living organisms. However, the sensor basically detects a heating element, and does not necessarily use a feature limited to a living body. Therefore, there is a problem that a heating element other than the living body is erroneously detected.
（発明の目的） 本発明は、生物体を特徴づける特定の波長の反射スペ
クトルに着目し、生物体のみを的確に識別して検出する
ことを目的とするものである。(Object of the Invention) An object of the present invention is to pay attention to a reflection spectrum of a specific wavelength that characterizes an organism, and accurately identify and detect only the organism.
（発明の構成） （発明の特徴と従来技術の差異） 本発明は、光源で照明された物体からの光の部分波長
帯に含まれる強度を測定する強度測定部を複数の部分波
長帯の各々に対応して備えた分光強度測定手段と、予め
求めた検知対象物体の分光強度の特徴を記録した記憶手
段と、前記分光強度測定手段の出力を前記記憶手段の内
容と比較する比較手段から構成され、任意物体について
前記分光強度測定手段により得られた分光強度と前記記
憶手段の内容の類似度に応じて、前記比較手段より数値
等の類似度情報を出力するとき、前記分光強度測定手段
の複数の部分波長帯の一つは、その中心波長が970nm付
近に設定されることを最も主要な特徴とする。(Structure of the Invention) (Features of the Invention and Difference from the Prior Art) The present invention provides an intensity measuring unit for measuring the intensity included in a partial wavelength band of light from an object illuminated by a light source, for each of a plurality of partial wavelength bands. A spectral intensity measuring means provided corresponding to the above, storage means for recording characteristics of the spectral intensity of the detection target object obtained in advance, and comparing means for comparing the output of the spectral intensity measuring means with the contents of the storage means. And outputting similarity information such as a numerical value from the comparing means according to the similarity between the spectral intensity obtained by the spectral intensity measuring means and the content of the storage means for an arbitrary object. One of the plurality of partial wavelength bands has the main feature that its center wavelength is set at around 970 nm.
従来の技術とは、生物体を特徴づける波長970nm付近
の赤外線の反射スペクトルを利用して、背景の中から生
物体のみを的確に識別し、検知する点が異なる。The difference from the conventional technique is that only the living body is accurately identified and detected from the background by using the reflection spectrum of infrared light having a wavelength around 970 nm, which characterizes the living body.
（実施例） 第１図および第２図は本発明の各実施例を示す。第１
図で、１−１から１−ｎはｎチャンネルの光強度測定部
で、それぞれは互いに異なる中心波長を持った帯域フィ
ルタ２−１から２−ｎを備えており、それらの出力は別
々に蓄積部３に蓄積される。すなわち、これらは全体で
通常の分光強度測定部４を構成し、光源６で照明された
物体５の表面からの反射光の分光強度を測定する。蓄積
部３からの出力は比較部８に入力される。記憶部７には
検知対象物体からの分光強度の特徴に関するデータが記
録されており、比較部８では蓄積部３の出力と記憶部７
の記憶内容とが比較され、その結果両者の類似程度に関
する出力信号が出力端子９に出力される。(Embodiment) FIGS. 1 and 2 show each embodiment of the present invention. First
In the figure, 1-1 to 1-n are n-channel light intensity measuring units each having band filters 2-1 to 2-n having different center wavelengths, and their outputs are stored separately. Stored in the unit 3. That is, these components constitute a normal spectral intensity measuring unit 4 as a whole, and measure the spectral intensity of the reflected light from the surface of the object 5 illuminated by the light source 6. The output from the storage unit 3 is input to the comparison unit 8. The storage unit 7 stores data on the characteristic of the spectral intensity from the detection target object, and the comparison unit 8 outputs the output of the storage unit 3 and the storage unit 7.
Are compared with each other, and as a result, an output signal relating to the degree of similarity between the two is output to the output terminal 9.
第２図は物体５の表面からの反射光が対物レンズ10を
通過したのち、回折格子２′により分光される場合で、
光強度測定部１−１から１−ｎには互いに異なった波長
の光が入射し、全体で分光強度が測定される。FIG. 2 shows the case where the reflected light from the surface of the object 5 passes through the objective lens 10 and is then separated by the diffraction grating 2 '.
Light having different wavelengths is incident on the light intensity measuring units 1-1 to 1-n, and the spectral intensity is measured as a whole.
第１図はカラーカメラのようにチャンネル数が少なく
とも帯域幅の大きい場合に適した構成であり、第２図は
いわゆる分光測定器のようにチャンネル数が多く帯域幅
の小さい場合に適したものである。FIG. 1 shows a configuration suitable for a case where the number of channels is at least large such as a color camera, and FIG. 2 shows a configuration suitable for a case where the number of channels is large and the bandwidth is small such as a so-called spectrometer. is there.
第３図は強度測定部１−1,1−2,…１−ｎ等を半導体
光電気変換素子としたもので、それぞれの受光部は帯域
フィルタ２−1,2−２…２−ｎ等で覆われている。この
ような半導体素子は小型で使い勝手もよく、ファクトリ
ーオートメーション（FA）の分野で色による部品の選別
装置のセンサとして近年多用されている。FIG. 3 shows the intensity measuring units 1-1, 1-2,... 1-n and the like as semiconductor photoelectric conversion elements. Covered with. Such a semiconductor element is small and easy to use, and is widely used in recent years as a sensor for a device for sorting components by color in the field of factory automation (FA).
このように分光強度測定部４には目的に応じて種々の
構成が実用されているが、本発明はそれらの構成方法自
体には無関係で、後述のように光強度測定部の中心波長
の設定を、生物体を特長づける特定の波長に着目して規
定する点に特徴を有する。As described above, various configurations are practically used for the spectral intensity measurement unit 4 according to the purpose. However, the present invention is not related to the configuration method itself, and the setting of the center wavelength of the light intensity measurement unit is described later. Is defined by focusing on a specific wavelength that characterizes a living organism.
また物体５の表面からの反射光の分光強度は物体に固
有の分光反射率と、照明光源の分光強度分布の相乗値と
して現れるから、蓄積部３が分光強度を出力するもので
あれば、記憶部７には光源の種類毎の特徴が記憶される
とともに、比較部８に出力される特徴を光源の種類に対
応して選択する機能が必要である。しかしながら、蓄積
部３に二つの蓄積部と、両者間の除算を行う機能とがあ
れば、初めに物体からの反射光の、ついで標準白色板か
らの反射光の分光強度を測定し、これらを別々に蓄積し
て置き両者の比を取ることにより、物体に固有の分光反
射率を比較部８に出力することが可能となる。明らかに
この場合には記憶部７は分光反射率の特徴のみが記憶さ
れていれば十分である。The spectral intensity of the light reflected from the surface of the object 5 appears as a synergistic value of the spectral reflectance specific to the object and the spectral intensity distribution of the illumination light source. The unit 7 needs to have a function of storing features for each type of light source and selecting a feature output to the comparing unit 8 in accordance with the type of light source. However, if the accumulating unit 3 has two accumulating units and a function of performing division between them, first, the spectral intensities of the reflected light from the object and then the reflected light from the standard white plate are measured, and these are measured. By storing them separately and taking the ratio between them, it is possible to output the spectral reflectance specific to the object to the comparison unit 8. Obviously, in this case, it is sufficient that the storage unit 7 stores only the characteristic of the spectral reflectance.
次に本発明を実施するための中心波長の設定方法とそ
の効果を、実測結果などを引用して説明する。種々の物
質の分光反射率を、例えば第３図に示した構成の生物体
検知装置を用い、JISに示された「１光路の分光測定器
を使用する場合」に準じて測定し、次のような結果が得
られた。Next, a method of setting a center wavelength for implementing the present invention and its effect will be described with reference to actual measurement results and the like. The spectral reflectances of various substances are measured, for example, using a living body detection device having the configuration shown in FIG. 3 according to "when using a one-path spectrometer" specified in JIS. Such a result was obtained.
第４図はJIS準拠の標準色票（三属性表示で5YR3/2）
の場合を示す。図の場合、反射率は可視領域の波長600n
mで最大で近赤外線の領域1000nm付近までほぼ一定であ
る。この他に日常使用する紙類、木材、皮革類、布地、
プラスチックス、塗装金属面など非生物体ではいずれの
場合にも反射率は、波長750〜1000nmの範囲で一定か、
または波長が増すとともに増加する特性を示すことが認
められた。Fig. 4 is a standard color chart conforming to JIS (5YR3 / 2 in three attribute display)
The case of is shown. In the case of the figure, the reflectance is 600n in the visible region.
At m, it is almost constant up to the near infrared region of 1000 nm. In addition to this, paper, wood, leather, fabric,
For non-living objects such as plastics and painted metal surfaces, in any case, the reflectance is constant in the wavelength range of 750 to 1000 nm,
Alternatively, it was recognized that the property of increasing the wavelength was shown.
これに対して、生物体として、人間の皮膚、魚肉、果
物類の表面の場合には、反射率が750〜800nm付近で極大
値を取るが、それ以上の波長では減少し、波長970nm付
近で極小値をとることが分かった。人間の皮膚の値と、
上記色票の値とを第１表に示す。In contrast, in the case of human skin, fish meat, and the surface of fruits, as a living organism, the reflectance has a maximum value at around 750 to 800 nm, but decreases at wavelengths longer than that, and at around 970 nm. It was found to take a minimum. Human skin values,
Table 1 shows the values of the color chart.
この表では各波長454,534,614ならびに974nmに於ける
反射率を800nmに於ける反射率で規格化した値が示され
ている。ちなみに前３波長は、NTSC方式のカラーテレビ
に於ける３原色の中心波長にほぼ等しい。表のように生
物体の場合には974nmの反射率が非生物の場合より小さ
くなることが特徴で、この事実を生物体の検出に利用す
ることが本発明の要点である。 This table shows values obtained by standardizing the reflectance at each of the wavelengths 454, 534, 614 and 974 nm by the reflectance at 800 nm. Incidentally, the first three wavelengths are almost equal to the center wavelengths of the three primary colors in the NTSC color television. As shown in the table, in the case of living organisms, the reflectance at 974 nm is smaller than that of non-living organisms, and it is the gist of the present invention to utilize this fact for the detection of living organisms.
なお、比較のために、３原色に於ける反射率を規格化
したものを第２表に示す。For comparison, Table 2 shows normalized values of the reflectance in the three primary colors.
また、周知のように分反射率は各波長毎に対象物体の
反射光強度の光源の強度の比を取ったものであるが、上
記のような規格化は対象物体と光源の距離の影響を除く
効果がある。 Also, as is well known, the fractional reflectance is obtained by taking the ratio of the light source intensity of the reflected light intensity of the target object for each wavelength, but the standardization as described above affects the influence of the distance between the target object and the light source. Has the effect of removing.
分光反射率の差異に基づいて生物体の検出は、第１表
の数値を要素とするベクトルの類似度判定により行うこ
ととなるが、その具体的手順を、人間の皮膚の場合を例
に取り以下に述べる。The detection of living organisms based on the difference in spectral reflectance is performed by determining the similarity of the vectors having the numerical values in Table 1 as elements. The specific procedure is described taking the case of human skin as an example. It is described below.
（ア）ベクトル間の距離としてはユークリッド距離を初
めとして、数種類の概念が定義されているが、個々では
要素間の相関を取り込むことが可能なマハラノビス平方
距離を用いた。(A) Several types of concepts are defined as the distance between vectors, including the Euclidean distance, but the Mahalanobis square distance that can capture the correlation between elements is used.
（イ）人間の皮膚の母集団ベクトルを求めるため、合計
35人については分光反射率を実測し、個々のデータから
第１表に示したような要素をそれぞれ抽出した。これら
35例から、皮膚の母平均ベクトルと母分散・共分散マト
リクスを算出した。(A) To obtain the population vector of human skin,
For 35 individuals, the spectral reflectance was measured, and the elements shown in Table 1 were extracted from the individual data. these
From 35 cases, a population mean vector and a population variance / covariance matrix of the skin were calculated.
（ウ）任意の供試ベクトルと、皮膚の母平均ベクトルの
間のマハラノビス平方距離Ｄを、母分散・共分散マトリ
クスを用いて算出した。Ｄがカイ２乗分布に従うことを
利用して供試ベクトルと、母平均ベクトルの類似度に関
する帰無仮説検定を行った。(C) A Mahalanobis square distance D between an arbitrary test vector and a skin mean vector was calculated using a population variance / covariance matrix. A null hypothesis test was performed on the similarity between the test vector and the population mean vector using the fact that D follows a chi-square distribution.
マハラノビス平方距離Ｄの算出結果を第５図に示す。
同図で縦軸はＤを表す。横軸（ａ）は有意水準％に対応
するＤ値を表している。（ｂ）は標準色票のＤ値を示す
部分、（ｃ）は皮膚以外に測定した物質等のＤ値であ
る。この場合、掌と果物は有意水準99％で皮膚との差が
あるとは認められないという結果が得られたが、標準色
票については、測定した73例全てが、有意水準99％皮膚
と識別されたことが分かる。The calculation result of the Mahalanobis square distance D is shown in FIG.
In the figure, the vertical axis represents D. The horizontal axis (a) represents the D value corresponding to the significance level%. (B) is a portion showing the D value of the standard color chart, and (c) is a D value of a substance or the like measured other than the skin. In this case, the palm and fruit were found to have a significant level of 99%, indicating that there was no difference from the skin. However, for the standard color chart, all 73 cases measured had a 99% significant level of skin. It turns out that it was identified.
これらに対して、第６図は前記第２表のような３原色
の反射率を要素とするベクトルを考え、やはりＤ値によ
る検定を行った結果であり、可視領域に於ける分光反射
率が皮膚のそれに近い皮革の場合のＤ値が第５図よりも
小さくなり、又皮膚に近い色の３種の色票については皮
膚との識別が不可能という結果となっている。しかし、
これらについても、赤外線領域に於ける生物体の特徴を
考慮した類似度検定を実施すれば生物体か否かの区別を
つけることが可能となり、このことによって第５図に見
られるような皮膚との識別を行うことができた。On the other hand, FIG. 6 shows a result obtained by considering a vector having the reflectance of the three primary colors as an element as shown in Table 2 above and also performing a test based on the D value. The D value in the case of leather close to that of the skin is smaller than that in FIG. 5, and it is impossible to distinguish three types of color patches close to the skin from the skin. But,
As for these, if a similarity test is performed in consideration of the characteristics of the organism in the infrared region, it is possible to distinguish between the organism and the non-organism, whereby the skin and the skin as shown in FIG. Could be identified.
以上述べたように本発明による生物体検知装置では、
赤外線の特定の波長領域（970nm付近）の反射率に生物
体と非生物体の間で明確な差異のあることに着目し、こ
の波長領域を分光測定部の中心波長に含めた構成とした
ので、生物体の識別検出を高い精度で行うことができ
る。As described above, in the living body detection device according to the present invention,
Focusing on the fact that there is a clear difference between the reflectance of a specific wavelength region (around 970 nm) of infrared light between living organisms and non-living organisms, this wavelength range was included in the center wavelength of the spectrometer. In addition, it is possible to perform identification and detection of a living body with high accuracy.
上記の検定例では赤外線領域で二つの中心波長を設定
して、これを可視領域のスペクトル情報と併用する場合
を示した。しかし、上記作用の説明のように生物体の識
別のためには赤外線領域の２波長の強度比が要点となっ
ているから、これのみを用いる構成としてもよい。可視
領域の情報は検出精度をさらに高めるための効果を持つ
ことはいうまでもない。また可視領域と併用する場合に
は、赤外線領域の波長を波長974nmの唯ひとつとしても
本発明による効果は変わらない。In the above test example, the case where two center wavelengths were set in the infrared region and used together with the spectral information in the visible region was shown. However, as described in the above operation, the essential point is the intensity ratio of the two wavelengths in the infrared region for identification of a living body, and therefore, a configuration using only this is also possible. It goes without saying that the information in the visible region has the effect of further increasing the detection accuracy. When used in the visible region, the effect of the present invention does not change even if the wavelength in the infrared region is only 974 nm.
本発明の応用例として、カメラにより得られた画像か
ら人間等の特定の生物体を検出する場合が考えられる。
この目的のため、従来手法による場合には、可視領域の
カラーカメラ画像中から対象物体に対応した特定の色度
座標部分を抽出することになる。しかし、人間の肌を検
出する場合を例に取ると、日常の情景中には茶系の壁、
家具など人肌に類似した色度を持つ物体は多く見られる
から、肌の部分のみを高い精度で抽出することは一般に
は困難である。このような場合に本発明のように赤外線
領域への強度測定帯域の追加、具体的には赤外線カメラ
による画像を追加することによって、前述で効果を示し
たように非生物体を除外することが可能となり、検出精
度を飛躍的に高めることができる。赤外線情報のみによ
る場合には夜間等での検知にも使用できる。これらの結
果、オフィス／ホームオートメーションやセキュリティ
分野への効果的な応用が期待できる。As an application example of the present invention, a case where a specific living body such as a human is detected from an image obtained by a camera can be considered.
For this purpose, when the conventional method is used, a specific chromaticity coordinate portion corresponding to the target object is extracted from the color camera image in the visible region. However, taking the case of detecting human skin as an example, in everyday scenes, tea-based walls,
Since there are many objects having chromaticity similar to human skin, such as furniture, it is generally difficult to extract only the skin portion with high accuracy. In such a case, by adding an intensity measurement band to the infrared region as in the present invention, specifically, by adding an image by an infrared camera, it is possible to exclude a non-living object as shown above. This makes it possible to dramatically improve the detection accuracy. If only infrared information is used, it can be used for nighttime detection. As a result, effective application to office / home automation and security fields can be expected.
なお、本発明では赤外線領域を1000nm以下に限定した
が、このことは第３図で述べた半導体素子を用いる場合
の装置構成上の利点となっている。すなわち、シリコン
素子のような量子型の光電気変換素子は、高感度かつ高
応答速度であるため広く使用されている。しかしこの特
性は波長1000nm以下の場合であり、それ以上の長波長で
は感度が急激に低下する。従って、対象波長を1000nm以
下とすることにより、第３図の構成ですべての強度測定
部を同じ材質とし、帯域フィルタのみを異ならせればよ
く、このことは実用上の大きな利点である。In the present invention, the infrared region is limited to 1000 nm or less, which is an advantage in the configuration of the device when the semiconductor element described in FIG. 3 is used. That is, quantum photoelectric conversion elements such as silicon elements are widely used because of their high sensitivity and high response speed. However, this characteristic is at a wavelength of 1000 nm or less, and at longer wavelengths, the sensitivity sharply decreases. Therefore, by setting the target wavelength to 1000 nm or less, all the intensity measuring sections need to be made of the same material in the configuration of FIG. 3 and only the band-pass filter is changed, which is a great advantage in practical use.
（発明の効果） 以上のべたように本発明は、赤外線の特定の波長領域
の反射率に生物体と非生物体の間で明確な差異のあるこ
とに着目し、この波長領域を分光測定部の中心波長に含
めた構成により、生物体の識別検出を高い精度で行なう
ことができる。(Effect of the Invention) As described above, the present invention focuses on the fact that there is a clear difference between the reflectance of a specific wavelength region of infrared light between a living organism and a non-living organism, and uses this wavelength range as a spectrometer. With the configuration including the center wavelength, the identification and detection of the living body can be performed with high accuracy.
第１図ないし第３図は本発明の各実施例の構成図、第４
図は標準色票の分光反射率測定の一例、第５図は皮膚を
検知対象として本発明を実施した場合の識別結果を示す
図、第６図は同じ検知対象について従来手法を適用した
場合の識別結果を示す図である。 １−１〜１−ｎ……光強度測定部、２−１〜２−ｎ……
中心波長の異なる帯域フィルタ、３……分光放射強度の
蓄積部、４……分光強度測定部、５……測定対象物体、
６……光源、７……測定対象物体の反射率情報の記憶
部、８……比較部、９……出力端子、２′……回折格
子、10……レンズ。FIG. 1 to FIG. 3 are structural views of each embodiment of the present invention, and FIG.
Fig. 5 shows an example of the spectral reflectance measurement of the standard color chart, Fig. 5 shows the identification result when the present invention is implemented with the skin as the detection target, and Fig. 6 shows the case where the conventional method is applied to the same detection target. It is a figure showing an identification result. 1-1 to 1-n... Light intensity measuring section, 2-1 to 2-n.
Band-pass filters having different center wavelengths, 3... A spectral radiation intensity accumulating unit, 4... A spectral intensity measuring unit, 5.
6 light source, 7 storage unit for reflectance information of the object to be measured, 8 comparison unit, 9 output terminal, 2 'diffraction grating, 10 lens.
Claims (2)
帯に含まれる強度を測定する強度測定部を複数の部分波
長帯の各々に対応して備えた分光強度測定手段と、予め
求めた検知対象物体の分光強度の特徴を記録した記憶手
段と、前記分光強度測定手段の出力を前記記憶手段の内
容と比較する比較手段から構成し、 前記分光強度測定手段の複数の部分波長帯を赤外線領域
に２以上設定し、且つ、その一つは中心波長を970nm付
近とし、 任意物体について前記分光強度測定手段により得られた
分光強度と前記記憶手段の内容を前記比較手段で比較す
ることにより生物体を検知することを特徴とする生物体
検知装置。1. Spectral intensity measuring means provided for each of a plurality of partial wavelength bands, comprising: an intensity measuring section for measuring an intensity included in a partial wavelength band of light from an object illuminated by a light source; Storage means for recording characteristics of the spectral intensity of the detection target object, and comparing means for comparing the output of the spectral intensity measurement means with the contents of the storage means, wherein a plurality of partial wavelength bands of the spectral intensity measurement means By setting two or more in the infrared region, and one of them having a center wavelength around 970 nm, by comparing the spectral intensity obtained by the spectral intensity measuring means with respect to an arbitrary object and the content of the storage means by the comparing means. An organism detecting device for detecting an organism.
帯に含まれる強度を測定する強度測定部を複数の部分波
長帯の各々に対応して備えた分光強度測定手段と、予め
求めた検知対象物体の分光強度の特徴を記録した記憶手
段と、前記分光強度測定手段の出力を前記記憶手段の内
容と比較する比較手段から構成し、 前記分光強度測定手段の複数の部分波長帯を可視領域と
赤外線領域にそれぞれ１以上設定し、且つ、赤外線領域
の一つは中心波長を970nm付近とし、 任意物体について前記分光強度測定手段により得られた
分光強度と前記記憶手段の内容を前記比較手段で比較す
ることにより生物体を検知することを特徴とする生物体
検知装置。2. A spectral intensity measuring means comprising: an intensity measuring section for measuring the intensity included in a partial wavelength band of light from an object illuminated by a light source corresponding to each of a plurality of partial wavelength bands; Storage means for recording characteristics of the spectral intensity of the detection target object, and comparing means for comparing the output of the spectral intensity measurement means with the contents of the storage means, wherein a plurality of partial wavelength bands of the spectral intensity measurement means At least one is set for each of the visible region and the infrared region, and one of the infrared regions has a center wavelength of around 970 nm, and compares the spectral intensity obtained by the spectral intensity measurement unit with the content of the storage unit for an arbitrary object. A living body detection device, wherein the living body is detected by means of comparison.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP63128521A JP2823564B2 (en) | 1988-05-27 | 1988-05-27 | Organism detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP63128521A JP2823564B2 (en) | 1988-05-27 | 1988-05-27 | Organism detection device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH01299488A JPH01299488A (en) | 1989-12-04 |
| JP2823564B2 true JP2823564B2 (en) | 1998-11-11 |
Family
ID=14986801
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP63128521A Expired - Lifetime JP2823564B2 (en) | 1988-05-27 | 1988-05-27 | Organism detection device |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP2823564B2 (en) |
Families Citing this family (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09231435A (en) * | 1996-02-21 | 1997-09-05 | Copal Co Ltd | Paper sheet counterfeit discriminating device |
| US7076088B2 (en) * | 1999-09-03 | 2006-07-11 | Honeywell International Inc. | Near-infrared disguise detection |
| JP4442472B2 (en) * | 2005-03-07 | 2010-03-31 | 株式会社豊田中央研究所 | Device part identification device |
| JP2008178572A (en) * | 2007-01-25 | 2008-08-07 | Matsushita Electric Works Ltd | Optical regulation apparatus for body hair growth |
| EP2106824A4 (en) * | 2007-01-25 | 2010-10-27 | Panasonic Elec Works Co Ltd | Optical body hair growth regulating device |
| JP5224906B2 (en) * | 2008-05-23 | 2013-07-03 | 株式会社Ｉｈｉ | Vegetation detection apparatus and method |
| JP5699557B2 (en) * | 2010-11-16 | 2015-04-15 | 住友電気工業株式会社 | Object identification device and object identification method |
| US9042941B2 (en) | 2011-12-28 | 2015-05-26 | Nokia Solutions And Networks Oy | Uplink grouping and aperture apparatus |
| US10452894B2 (en) | 2012-06-26 | 2019-10-22 | Qualcomm Incorporated | Systems and method for facial verification |
| US8913972B2 (en) | 2012-10-11 | 2014-12-16 | Nokia Siemens Networks Oy | Antenna clustering for multi-antenna aperture selection |
| US9996726B2 (en) | 2013-08-02 | 2018-06-12 | Qualcomm Incorporated | Feature identification using an RGB-NIR camera pair |
| EP3270354B1 (en) | 2015-03-13 | 2022-10-26 | Nec Corporation | Living body detection device, living body detection method, and recording medium |
| JP6454748B2 (en) * | 2016-05-18 | 2019-01-16 | レノボ・シンガポール・プライベート・リミテッド | Method for certifying presence / absence of user, method for controlling device, and electronic apparatus |
| JP6819653B2 (en) * | 2018-07-09 | 2021-01-27 | 日本電気株式会社 | Detection device |
| JP2021047929A (en) * | 2020-12-28 | 2021-03-25 | 日本電気株式会社 | Information processor |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6168571A (en) * | 1984-09-12 | 1986-04-08 | Mitsubishi Electric Corp | Image tracking apparatus |
| JPS6373141A (en) * | 1986-09-16 | 1988-04-02 | Shimadzu Corp | Data retrieving apparatus |
-
1988
- 1988-05-27 JP JP63128521A patent/JP2823564B2/en not_active Expired - Lifetime
Also Published As
| Publication number | Publication date |
|---|---|
| JPH01299488A (en) | 1989-12-04 |
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