JPH0933227A - Three-dimensional shape identification method - Google Patents
Three-dimensional shape identification methodInfo
- Publication number
- JPH0933227A JPH0933227A JP7207758A JP20775895A JPH0933227A JP H0933227 A JPH0933227 A JP H0933227A JP 7207758 A JP7207758 A JP 7207758A JP 20775895 A JP20775895 A JP 20775895A JP H0933227 A JPH0933227 A JP H0933227A
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- Prior art keywords
- data
- image
- dimensional
- dimensional shape
- identification method
- 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.)
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Links
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000012545 processing Methods 0.000 claims abstract description 25
- 238000006073 displacement reaction Methods 0.000 claims abstract description 22
- 238000005286 illumination Methods 0.000 abstract description 4
- 230000000873 masking effect Effects 0.000 description 7
- 230000000052 comparative effect Effects 0.000 description 6
- 238000005259 measurement Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 235000004522 Pentaglottis sempervirens Nutrition 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
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- Length Measuring Devices By Optical Means (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
Abstract
(57)【要約】
【課題】 スローアウェチップ等の表面の三次元形状を
識別するため、従来の対象物へのそれぞれ特有の照明法
をとるようなことはしないで済むレーザ変位計を用い、
対象物の三次元データを処理して画像表現は簡単に表示
できようし、記憶した登録パターンとの対比を容易にす
る。
【解決手段】 レーザ変位計1を用いることによって得
られる対象物2の三次元データをデータ処理装置4で解
析し、イメージプロセッサボード5にて三次元データを
濃淡画像にし、この濃淡データを加工して対象物の特徴
を最も良く表わす高さ方向のデータのみを選択し他はマ
スクして画像化し、このデータを専用画像処理装置7に
入力し、パターンの登録や識別を行う。
(57) 【Abstract】 PROBLEM TO BE SOLVED: To identify a three-dimensional shape of a surface of a throwaway tip or the like, a laser displacement meter which does not need to adopt a conventional illumination method for an object is used.
The three-dimensional data of the object can be processed so that the image representation can be easily displayed and the comparison with the stored registered pattern is facilitated. SOLUTION: Three-dimensional data of an object 2 obtained by using a laser displacement meter 1 is analyzed by a data processing device 4, an image processor board 5 converts the three-dimensional data into a grayscale image, and the grayscale data is processed. Then, only the data in the height direction that best represents the characteristics of the object is selected, the others are masked to form an image, and this data is input to the dedicated image processing device 7 to register or identify the pattern.
Description
【0001】[0001]
【発明の属する技術分野】本発明はスローアウェイチッ
プのように、表面の凹凸に特徴をもつ対象物の品種識別
方法に関するものである。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for identifying a type of an object such as a throw-away tip, which has a feature of unevenness on the surface.
【0002】[0002]
【従来の技術】 画像処理で三次元形状の特徴をとらえるには、照明を
対象物の斜め上方から当てる方法(フロント・ライティ
ング)や、スリット光のような特定のパターンの光を当
てる方法(光切断、ストラクチャーライテング)などの
手法がとられている(映像情報 1993 Vol.25 P43-47 参
照)。また、安定した画像を得るために対象物の色を限
定するという手段が用いられている(特開昭 59-202198
号公報参照)。 レーザ変位計で三次元形状をとらえるには、スポット
状のレーザ変位計をX−Y方向に必要な範囲にわたって
移動させ、各点におけるZ方向データを取込むか、若し
くは、レーザ光を走査し、対象物を走査と直交する方向
に移動させる方式がある。なおレーザ変位計の原理は以
下のとおりである。レーザビームを例えば測定対象物垂
直方向より投光し、前記対象物について基準となる面で
のビームの乱反射による拡散光を、レンズ、スクリーン
からなる受光系の検出角を、動作中心で45度となるよう
に設定すると、前記基準面上におけるレーザポイントは
45度の検出角としてスクリーン上のポイントとして結像
する。次にこの基準面に測定対象物を挿入すると基準面
より測定対象物表面の高さが変るので、この測定対象物
表面での拡散光は受光系の検出角45度に対して変化した
角度となり、前記スクリーン上において基準面反射によ
って生じた結像より離れた結像をなすが、この基準面と
測定対象物面のレーザビーム投射方向の高さの差は、ス
クリーン上における基準面反射による結像位置から測定
対象物面反射による結像位置への変位と比例関係にあ
り、レーザビーム方向における測定対象物の高さ変化
(凹凸)は、スクリーン上で検出できるのである。この
原理は三角測量方式によるものである。2. Description of the Related Art In order to detect the features of a three-dimensional shape by image processing, a method of illuminating a subject obliquely from above (front lighting) or a method of illuminating a specific pattern such as slit light (light Techniques such as cutting and structure lighting are used (see Video Information 1993 Vol.25 P43-47). In addition, a means of limiting the color of an object is used to obtain a stable image (Japanese Patent Laid-Open No. 59-202198).
Reference). In order to capture a three-dimensional shape with a laser displacement meter, a spot-shaped laser displacement meter is moved over the necessary range in the XY direction, and Z direction data at each point is acquired, or laser light is scanned. There is a method of moving an object in a direction orthogonal to scanning. The principle of the laser displacement meter is as follows. For example, the laser beam is projected from the vertical direction of the object to be measured, diffused light due to diffused reflection of the beam on the reference surface of the object, the detection angle of the light receiving system including the lens and the screen, and 45 degrees at the operation center. If set so that the laser point on the reference plane is
Image as a point on the screen with a detection angle of 45 degrees. Next, when the measurement object is inserted into this reference surface, the height of the measurement object surface from the reference surface changes, so the diffused light on this measurement object surface becomes an angle that changes with respect to the detection angle of 45 degrees of the light receiving system. The image formed on the screen is far from the image formed by the reflection of the reference surface. The difference in height between the reference surface and the surface of the measuring object in the laser beam projection direction is caused by the reflection of the reference surface on the screen. There is a proportional relationship with the displacement from the image position to the image formation position due to the reflection of the surface of the measuring object, and the height change (irregularities) of the measuring object in the laser beam direction can be detected on the screen. This principle is based on the triangulation method.
【0003】[0003]
【発明が解決しようとする課題】 従来の照明方法では最適条件を得るのが困難な上に、
得られた条件は限られた対象物にしか使用できず、例え
ば対象物の色、光沢、形状が変わると計測が安定しな
い。 照明で三次元形状を求めるためには、凹凸が深く、か
つシャープな物に限られ、ひらたく浅い凹凸は計測不可
能である。 レーザ変位計をトラバース(又はレーザスポットを走
査)して得られる三次元データはデータが膨大となるケ
ースが多く、結果を表示するにも鳥観図のような複雑な
ソフトを必要とした。また、このようなデータを基に三
次元形状を認識するにも専用のソフトを開発する必要が
あり、汎用的に展開する手段はなかった。 レーザを走査する場合、対象物が走査範囲より大きい
と、対象物をレーザ方向に動かし、複数回計測を必要と
した。 対象物の特徴を表す三次元形状が対象物の全体の高さ
に比べて小さい場合、特徴は全体形状に埋もれ、認識精
度が悪化することになる。[Problems to be Solved by the Invention] It is difficult to obtain optimum conditions by the conventional lighting method, and
The obtained conditions can be used only for a limited object, and the measurement is not stable if, for example, the color, gloss, or shape of the object changes. In order to obtain a three-dimensional shape by illumination, the unevenness is limited to deep and sharp objects, and it is impossible to measure open and shallow unevenness. The three-dimensional data obtained by traversing the laser displacement meter (or scanning the laser spot) is often enormous, and complicated software such as a bird's eye view is required to display the result. Further, it is necessary to develop dedicated software for recognizing a three-dimensional shape based on such data, and there is no means for general-purpose development. When the laser is scanned, if the object is larger than the scanning range, the object is moved in the laser direction, and the measurement needs to be performed a plurality of times. When the three-dimensional shape representing the feature of the object is smaller than the height of the entire object, the feature is buried in the overall shape, and the recognition accuracy deteriorates.
【0004】[0004]
【課題を解決するための手段】本発明は上記課題を解決
するためなされたものであって、次の構成を備えるもの
である。 (a)三次元形状を取込む手段として、レーザ変位計を
用い、そのデータは二次元濃淡画像に変換してモニタに
表示する。データ取込みを高速化する目的でレーザ変位
計はレーザスポットを走査するタイプが望まれる。 (b)対象物が大きい場合、これを回転させ、レーザス
ポットをその半径方向に走査させる構成とする。 (c)レーザ変位計から得られたデータをデータ処理装
置に取込んだ後、対象物の特徴を最も良く表わす高さ方
向のデータのみを選択し、他はマスク処理を行う。 (d)(c)の処理を行った後のデータを画像化し、そ
れを専用画像処理装置に入力するシステムとし、パター
ン登録や認識はこの専用画像処理装置で行う。The present invention has been made to solve the above problems, and has the following configuration. (A) A laser displacement meter is used as a means for capturing a three-dimensional shape, and the data is converted into a two-dimensional grayscale image and displayed on a monitor. For the purpose of speeding up data acquisition, it is desirable that the laser displacement meter be a type that scans a laser spot. (B) When the object is large, the object is rotated and the laser spot is scanned in the radial direction. (C) After the data obtained from the laser displacement meter is taken into the data processing device, only the data in the height direction that best represents the characteristics of the object is selected, and the mask processing is performed for the others. (D) After the processing of (c) is performed, the data is converted into an image, and the data is input to a dedicated image processing apparatus, and pattern registration and recognition are performed by this dedicated image processing apparatus.
【0005】[0005]
【発明の実施の形態】対象物の三次元形状を識別するた
めの手段としてレーザ変位計を用いることで、対象物の
色や凹凸の程度に影響を受けずに安定したデータを取込
むことが可能となる。また照明を必要としないので、複
雑な照明の調整が不要となり、形状、大きさの変る対象
物に対し、有効である。三次元データを高速に取込むた
めには、レーザスポットを走査させるレーザ変位計が有
効であるが、対象物が走査範囲より大きい場合、対象物
を回転させ、レーザをその半径方向に走査させる構成と
することで、走査範囲の2倍の対象物まで、その全体の
三次元形状を取込むことが可能となる。得られた膨大な
三次元データを二次元の濃淡画像に変換することによっ
て、凹凸データをモニタ上で目視で確認できる上、この
画像を専用画像装置に入力することで、パターン登録や
識別の実行を汎用画像処理装置で行うことが可能となる
から専用ソフトを開発する必要がなくなり、簡単にシス
テムを構築できる。対象物を識別するにあたり、取込ん
だ三次元データのうち、データ処理装置を用いて、その
対象物の特徴を最も良く得られる高さ方向(範囲)のデ
ータを有効とし、他はマスク処理を施すことにより、対
象物の全体高さがその特徴量に比べて大きな場合にも識
別精度を向上することができる。マスク処理を施すしき
い値は、取込まれたデータのヒストグラムを求め、その
分布を明確に分離できる値を求めることで自動的に得る
ことができる。BEST MODE FOR CARRYING OUT THE INVENTION By using a laser displacement meter as a means for identifying a three-dimensional shape of an object, stable data can be captured without being affected by the color or the degree of unevenness of the object. It will be possible. Further, since no illumination is required, complicated illumination adjustment is unnecessary, which is effective for an object whose shape and size are changed. A laser displacement meter that scans a laser spot is effective for capturing three-dimensional data at high speed. However, when the object is larger than the scanning range, the object is rotated and the laser is scanned in the radial direction. By doing so, it becomes possible to capture the entire three-dimensional shape of the object up to twice the scanning range. By converting the enormous amount of three-dimensional data obtained into a two-dimensional gray-scale image, the unevenness data can be visually confirmed on the monitor, and by inputting this image to a dedicated image device, pattern registration and identification can be performed. Since it can be performed by a general-purpose image processing device, it is not necessary to develop dedicated software, and the system can be easily constructed. In identifying the target object, of the captured three-dimensional data, the data processing device is used to validate the data in the height direction (range) that best obtains the characteristics of the target object, and the other is mask processing. By performing this, the identification accuracy can be improved even when the overall height of the object is larger than the feature amount. The threshold value to be masked can be automatically obtained by obtaining a histogram of captured data and obtaining a value that can clearly separate the distribution.
【0006】[0006]
【実施例】以下にスローアウェイチップの識別例につい
て説明する。図1はスローアウェイチップの形状識別装
置の一例を示す。図示のように、1軸ステージ3に対向
して、その上に、レーザ変位計1が配置される。レーザ
変位計1とデータ処理装置4とは電気的に接続され、デ
ータ処理装置4はイメージプロセッサボード5と電気的
に接続され、イメージプロセッサボード5はモニタ6、
専用画像処理装置7と電気的に接続されている。EXAMPLE An example of identifying a throw-away tip will be described below. FIG. 1 shows an example of a throwaway tip shape identifying device. As shown in the figure, the laser displacement meter 1 is arranged on the uniaxial stage 3 so as to face it. The laser displacement meter 1 and the data processing device 4 are electrically connected, the data processing device 4 is electrically connected to the image processor board 5, and the image processor board 5 is the monitor 6.
It is electrically connected to the dedicated image processing device 7.
【0007】1軸ステージ3の上に測定対象物2、この
場合は図2に示すスローアウェイチップ(以下TAとい
う)を載置し、その上方に設置されたレーザ変位計1に
てTA表面の凹凸の状態を検出する。ここで用いられる
レーザ変位計1はレーザスポットを走査する形式のもの
で、図において示す直交x,y,z座標軸において矢印
で示すy方向にレーザスポットを走査する。これによっ
てy方向の各位置におけるz方向の凹凸を計測すること
ができる。本例でTAは三角形状のチップとして示され
ているが、各辺に切刃8が形成され、その内側にブレー
カ9がそれぞれ形成されている。1軸ステージ3をx方
向にモーターmで定速で動かし、同時にレーザスポット
をy方向で走査し、z方向のTA表面の凹凸データを検
出し、この動作を繰返えして行けば、1軸ステージ3を
含むTAの表面凹凸データが順次検出される。図3は凹
凸データ検出の概念図である。A measuring object 2, in this case, a throw-away tip (hereinafter referred to as TA) shown in FIG. 2 is placed on a uniaxial stage 3, and a laser displacement meter 1 installed above the TA is used to measure the TA surface. Detect the state of unevenness. The laser displacement meter 1 used here is of a type that scans a laser spot, and scans the laser spot in the y direction indicated by the arrow on the orthogonal x, y, z coordinate axes shown in the drawing. This makes it possible to measure unevenness in the z direction at each position in the y direction. Although the TA is shown as a triangular tip in this example, a cutting edge 8 is formed on each side and a breaker 9 is formed inside the cutting edge 8. The uniaxial stage 3 is moved at a constant speed by the motor m in the x direction, the laser spot is simultaneously scanned in the y direction, the unevenness data of the TA surface in the z direction is detected, and if this operation is repeated, 1 Surface irregularity data of TA including the axis stage 3 is sequentially detected. FIG. 3 is a conceptual diagram of detecting unevenness data.
【0008】レーザ変位計で検出された凹凸データは遂
次データ処理装置に取込む。The unevenness data detected by the laser displacement meter is taken into the sequential data processing device.
【0009】データ処理装置4に取込んだ前記データは
0〜255 の段階の整数に変換し、データ処理装置4に付
設されたイメージプロセッサボード5に書込むことで濃
淡画像を作成する。図4(a)は濃淡画像に変換後の画
像の例を示し、図4(b)は、図4(a)のx方向のA
断面における明度のデータを示している。The data taken in the data processing device 4 is converted into an integer in the range of 0 to 255 and written in the image processor board 5 attached to the data processing device 4 to create a grayscale image. FIG. 4A shows an example of an image after conversion into a grayscale image, and FIG. 4B shows an A in the x direction of FIG. 4A.
The lightness data in the cross section is shown.
【0010】ブレーカ形状を識別する時は、TAの全体
的な形状(図での三角形)は不要であるので、イメージ
プロセッサボード5での操作により、図5に示すように
周囲をマスク処理する。マスク処理する際のしきい値は
得られたデータのヒストグラム分布から求め、しきい値
より小さい値をマスクする。逆に全体形状を識別すると
きは、ブレーカー形状が不要となるので、図6に示すよ
うにブレーカーをマスク処理する。マスク処理する際の
しきい値は得られたデータのヒストグラム分布から求
め、しきい値より大きい値をマスク処理する。When identifying the breaker shape, the overall shape of TA (triangle in the figure) is not necessary, and therefore the image processor board 5 is operated to mask the periphery as shown in FIG. The threshold value for masking is obtained from the histogram distribution of the obtained data, and values smaller than the threshold value are masked. On the contrary, when identifying the entire shape, the breaker shape is not necessary, so the breaker is masked as shown in FIG. The threshold value for the mask processing is obtained from the histogram distribution of the obtained data, and the value larger than the threshold value is masked.
【0011】この画像を専用画像処理装置に入力し、予
め記録させておいた複数のパターンとの相関関係を次式
により計算し、最も相関値の高いパターンとして認識す
る。This image is input to a dedicated image processing apparatus, the correlation with a plurality of patterns recorded in advance is calculated by the following equation, and the pattern having the highest correlation value is recognized.
【0012】[0012]
【数1】 [Equation 1]
【0013】図7(a)は登録パターン(M)を示し、
図(b)は比較画像(I)を示す。この場合、登録パタ
ーンは、比較画像作成の手法と同様な手法によって所要
箇所に同様条件によってマスク等加工して作成したもの
である。比較画像を多数登録パターンと比較して、その
いずれにも属さないときは、この比較画像も新たに登録
することができる。数式1に示すように、相関係数Co
は登録パターンの明度データMi、比較する画像の明度
データIiが大きく関与し、2つの明度データが一致す
る時Co=1となり、明度データの差が大きくなるに従
って0に近付く。TAの場合、その大きさ、被削材の相
違などによってブレーカの形状がわずかに異なってお
り、品種ごとに異なる微小な凹凸の差を基に自動識別に
よる簡単なシステムを実現することができる。FIG. 7A shows a registered pattern (M),
Figure (b) shows a comparative image (I). In this case, the registered pattern is created by processing a mask or the like on a required portion under the same conditions by a method similar to the method for creating a comparative image. The comparative image is compared with a large number of registered patterns, and if the comparative image does not belong to any of them, this comparative image can be newly registered. As shown in Equation 1, the correlation coefficient Co
Is greatly related to the brightness data Mi of the registered pattern and the brightness data Ii of the image to be compared, and Co = 1 when the two brightness data match, and approaches 0 as the difference between the brightness data increases. In the case of TA, the shape of the breaker is slightly different due to the size, difference in the work material, etc., and a simple system can be realized by automatic identification based on the difference in minute unevenness that differs for each product type.
【0014】図8はレーザを走査する場合、対象物が走
査範囲より大きいとき回転ステージ10を用い、この回転
ステージ10の回転軸上に対象物、例えばTAの中心を置
き、レーザ変位計1のレーザースポットがTAの中心よ
り半径方向に走査できるように配置し、レーザスポット
で半径方向に走査し、回転ステージ10を遂次回転させる
方法を採れば、すくなくともレーザ変位計の走査範囲の
2倍以内の範囲にある対象物の三次元パターンを認識で
きる。In FIG. 8, when a laser is scanned, the rotary stage 10 is used when the object is larger than the scanning range, and the object, for example, the center of TA is placed on the rotation axis of the rotary stage 10 and the laser displacement meter 1 is operated. If the laser spot is arranged so that it can be scanned in the radial direction from the center of the TA, the laser spot is scanned in the radial direction, and the rotary stage 10 is successively rotated, at least within twice the scanning range of the laser displacement meter. It is possible to recognize the three-dimensional pattern of the object within the range.
【0015】[0015]
【発明の効果】本発明は、これまで画像処理が困難とさ
れた、光沢のある(又は色の種類が多い)対象物の三次
元計測を実用化したもので、金属、プラスチックの表面
に付けられた浅い刻印の識別や表面実装部品の識別に適
用できる。INDUSTRIAL APPLICABILITY The present invention is one in which three-dimensional measurement of a glossy (or many kinds of color) object which has been difficult to perform image processing has been put into practical use. It can be applied to the identification of shallow markings and surface mount components.
【図1】スローアウェイチップの形状識別装置の一例を
示す。FIG. 1 shows an example of a throwaway tip shape identifying device.
【図2】スローアウェイチップを斜視図で示す。FIG. 2 shows a throw-away tip in perspective view.
【図3】図1の装置によりレーザスポットを走査して検
出される凹凸データの概念図である。FIG. 3 is a conceptual diagram of unevenness data detected by scanning a laser spot with the apparatus of FIG.
【図4】(a)は濃淡画像に変換後の画像を示し、
(b)は(a)図のx方向のA断面における明度のデー
タを示している。FIG. 4A shows an image after being converted into a grayscale image,
(B) shows the lightness data in the A section in the x direction of FIG.
【図5】(a)はマスク処理を示し、(b)はマスク処
理によってブレーカ形状のみの像を示し、(C)はマス
ク処理のしきい値を求めるためのヒストグラム分布を示
す。5A shows a masking process, FIG. 5B shows an image of only a breaker shape by the masking process, and FIG. 5C shows a histogram distribution for obtaining a threshold value of the masking process.
【図6】(a)はマスク処理を示し、(b)はマスク処
理によってスローアウェイチップの外形形状のみの像を
示し、(C)はマスク処理のしきい値を求めるためのヒ
ストグラム分布を示す。6A shows a masking process, FIG. 6B shows an image of only the outer shape of the throw-away chip by the masking process, and FIG. 6C shows a histogram distribution for obtaining the threshold value of the masking process. .
【図7】(a)は識別用の登録パターン、(b)は比較
画像を示す。FIG. 7A shows a registered pattern for identification, and FIG. 7B shows a comparative image.
【図8】本発明による対象物の回転、レーザ変位計のレ
ーザスポット走査による対象物表面凹凸データ採取の例
を示す。FIG. 8 shows an example of object surface unevenness data collection by rotation of the object and laser spot scanning of a laser displacement meter according to the present invention.
1 レーザ変位計 2 対象物 3 1軸ステージ 4 データ処理装置 5 イメージプロセッサボード 6 モニタ 7 専用画像処理装置 8 スローアウェイチップ 9 ブレーカ 10 回転ステージ 1 Laser displacement meter 2 Object 3 1-axis stage 4 Data processing device 5 Image processor board 6 Monitor 7 Dedicated image processing device 8 Throwaway chip 9 Breaker 10 Rotation stage
Claims (5)
れる対象物の三次元データをデータ処理装置で解析し、
あらかじめ記憶させておいたデータのパタンとの類似性
を比較することで、対象物がどのパタンのものかを識別
する三次元形状識別方法。1. A data processor analyzes three-dimensional data of an object obtained by using a laser displacement meter,
A three-dimensional shape identification method for identifying which pattern an object has by comparing the similarity of the data stored in advance with the pattern.
の濃淡画像に変換し、モニタに表示することで、対象物
の凹凸をカメラで写した像のように再現する方法を具備
した請求項1記載の三次元形状識別方法。2. A method for converting three-dimensional data into a two-dimensional gray-scale image by a data processing device and displaying the two-dimensional gray-scale image on a monitor to reproduce the unevenness of an object like an image taken by a camera. The three-dimensional shape identification method described in 1.
移動させることによって得られる三次元データのうち、
その対象物の特徴を最も良く表わす高さ方向データのみ
を有効とし、他の部分はマスクすることによって識別精
度を向上することを特徴とする請求項1記載の三次元形
状識別方法。3. Of three-dimensional data obtained by scanning a laser spot light or moving an object,
3. The three-dimensional shape identification method according to claim 1, wherein only the height direction data that best represents the characteristics of the object is validated and the other portions are masked to improve the identification accuracy.
て、レーザスポットの走査範囲より大きい対象物のパタ
ーンを認識するために対象物を回転させ、その半径を走
査することで対象物全体の三次元情報を得ることを特徴
とする請求項1記載の三次元形状識別方法。4. When the laser is scanned in one direction, the object is rotated in order to recognize a pattern of the object larger than the scanning range of the laser spot, and the radius thereof is scanned, thereby three-dimensionally measuring the entire object. The three-dimensional shape identification method according to claim 1, wherein information is obtained.
用画像処理装置に入力することによって、品種登録、識
別を行うことができる請求項1記載の三次元形状識別方
法。5. The three-dimensional shape identification method according to claim 1, wherein the product type registration and identification can be performed by inputting the grayscale image converted according to claim 2 to a dedicated image processing device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP20775895A JP3633675B2 (en) | 1995-07-21 | 1995-07-21 | 3D shape identification method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP20775895A JP3633675B2 (en) | 1995-07-21 | 1995-07-21 | 3D shape identification method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH0933227A true JPH0933227A (en) | 1997-02-07 |
| JP3633675B2 JP3633675B2 (en) | 2005-03-30 |
Family
ID=16545066
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP20775895A Expired - Fee Related JP3633675B2 (en) | 1995-07-21 | 1995-07-21 | 3D shape identification method |
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| Country | Link |
|---|---|
| JP (1) | JP3633675B2 (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007091604A1 (en) * | 2006-02-09 | 2007-08-16 | Honda Motor Co., Ltd. | Three-dimensional-object detecting device |
| JP2008058150A (en) * | 2006-08-31 | 2008-03-13 | Nidec Tosok Corp | Marking inspection apparatus |
| JP2008064637A (en) * | 2006-09-08 | 2008-03-21 | Nidec Tosok Corp | Engraved mark inspecting apparatus |
| JP2012168014A (en) * | 2011-02-14 | 2012-09-06 | Sharp Corp | Data analysis device, program, recording medium, data analysis method, and protein analysis device |
| CN105931234A (en) * | 2016-04-19 | 2016-09-07 | 东北林业大学 | Ground three-dimensional laser scanning point cloud and image fusion and registration method |
-
1995
- 1995-07-21 JP JP20775895A patent/JP3633675B2/en not_active Expired - Fee Related
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007091604A1 (en) * | 2006-02-09 | 2007-08-16 | Honda Motor Co., Ltd. | Three-dimensional-object detecting device |
| JP2007213353A (en) * | 2006-02-09 | 2007-08-23 | Honda Motor Co Ltd | Apparatus for detecting three-dimensional object |
| US8396283B2 (en) | 2006-02-09 | 2013-03-12 | Honda Motor Co., Ltd. | Three-dimensional object detecting device |
| JP2008058150A (en) * | 2006-08-31 | 2008-03-13 | Nidec Tosok Corp | Marking inspection apparatus |
| JP2008064637A (en) * | 2006-09-08 | 2008-03-21 | Nidec Tosok Corp | Engraved mark inspecting apparatus |
| JP2012168014A (en) * | 2011-02-14 | 2012-09-06 | Sharp Corp | Data analysis device, program, recording medium, data analysis method, and protein analysis device |
| CN105931234A (en) * | 2016-04-19 | 2016-09-07 | 东北林业大学 | Ground three-dimensional laser scanning point cloud and image fusion and registration method |
Also Published As
| Publication number | Publication date |
|---|---|
| JP3633675B2 (en) | 2005-03-30 |
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