WO2022176460A1 - 光演算装置及び光演算方法 - Google Patents
光演算装置及び光演算方法 Download PDFInfo
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- 238000005516 engineering process Methods 0.000 description 7
- 230000008859 change Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000007689 inspection Methods 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B5/00—Optical elements other than lenses
- G02B5/18—Diffraction gratings
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B5/00—Optical elements other than lenses
- G02B5/18—Diffraction gratings
- G02B5/1814—Diffraction gratings structurally combined with one or more further optical elements, e.g. lenses, mirrors, prisms or other diffraction gratings
- G02B5/1819—Plural gratings positioned on the same surface, e.g. array of gratings
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- G—PHYSICS
- G02—OPTICS
- G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
- G02F3/00—Optical logic elements; Optical bistable devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06E—OPTICAL COMPUTING DEVICES; COMPUTING DEVICES USING OTHER RADIATIONS WITH SIMILAR PROPERTIES
- G06E3/00—Devices not provided for in group G06E1/00, e.g. for processing analogue or hybrid data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/067—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using optical means
Definitions
- the present invention relates to an optical computing device and an optical computing method that perform optical computing using an optical diffraction element.
- An optical diffraction element that has a plurality of microcells and is designed to optically perform a predetermined operation by causing mutual interference between signal lights that have passed through each microcell.
- Optical computation using an optical diffraction element has the advantage of high speed and low power consumption compared to electrical computation using a processor.
- Patent Document 1 discloses an optical neural network having an input layer, an intermediate layer, and an output layer. The optical filter described above can be used, for example, as an intermediate layer of such an optical neural network.
- optical computing was performed by inputting signal light representing a single image into an optical diffraction element. Therefore, it has not been possible to perform light calculation using information that cannot be obtained from only a single image, such as three-dimensional information of an object.
- One aspect of the present invention has been made in view of the above problems, and an object of the present invention is to provide an optical operation device and an optical operation capable of using information that cannot be obtained from only a single image for optical operation. to implement the method.
- An optical arithmetic device includes an optical diffraction element group including at least one optical diffraction element having an optical arithmetic function, and signal light input to the optical diffraction element group, which are formed by different optical systems. and a light emitting unit that generates signal light representing each of the plurality of images that have been generated.
- An optical computing method is an optical computing method using an optical diffraction element group including at least one optical diffraction element having an optical computing function, wherein signal light input to the optical diffraction element group and generating signal light representing each of a plurality of images formed by different optical systems.
- an optical operation device or an optical operation method that can utilize information that cannot be obtained from only an image formed by a single camera for optical operation.
- FIG. 1 is a perspective view showing the configuration of an optical arithmetic device according to one embodiment of the present invention
- FIG. 2 is a plan view showing the configuration of an optical diffraction element included in the optical arithmetic device shown in FIG. 1
- FIG. 3 is an enlarged perspective view of a part of the optical diffraction element shown in FIG. 2;
- FIG. 1 is a perspective view showing the configuration of an optical arithmetic device according to one embodiment of the present invention
- FIG. 2 is a plan view showing the configuration of an optical diffraction element included in the optical arithmetic device shown in FIG. 1
- FIG. 3 is an enlarged perspective view of a part of the optical diffraction element shown in FIG. 2;
- FIG. 1 is a perspective view showing the configuration of an optical arithmetic device 1. As shown in FIG.
- the optical arithmetic device 1 includes a light emitting section 11, an optical diffraction element group 12, and a light receiving section 13, as shown in FIG.
- the light emitting unit 11 is configured to generate signal light.
- the signal light generated by the light emitting unit 11 is signal light representing each of the images formed by the two cameras C1 and C2.
- the image formed by the camera C1 is displayed on half of the display surface (for example, the right half or upper half), and the remaining half of the display surface (for example, the left half or lower half).
- a display for displaying an image formed by the camera C2 is used as the light emitting unit 11.
- the signal light output from the light emitting unit 11 is also referred to as "input signal light". A specific example of the two images represented by the input signal light will be described later.
- the optical diffraction element group 12 is arranged on the optical path of the input signal light.
- the optical diffraction element group 12 is a set of n optical diffraction elements 12a1 to 12an.
- n is a natural number of 1 or more.
- Each optical diffraction element 12ai is a configuration for executing a predetermined optical calculation, in other words, a configuration for converting the two-dimensional intensity distribution of signal light according to a predetermined conversion rule.
- i is each natural number of 1 or more and n or less.
- a set of two optical diffraction elements 12a1 and 12a2 is used as the optical diffraction element group 12.
- FIG. The configuration of the optical diffraction element 12ai will be described later with reference to different drawings.
- the optical diffraction elements 12a1 to 12an are arranged in a straight line on the optical path of the input signal light. Therefore, the input signal light passes through the first optical diffraction element 12a1, the second optical diffraction element 12a2, . . . , the n-th optical diffraction element 12an in this order. Therefore, in the optical diffraction element group 12, the input signal light undergoes the first optical operation by the first optical diffraction element 12a1, the second optical operation by the second optical diffraction element 12a2, . The n-th optical operation by the optical diffraction element 12an is executed in this order. The intensity distribution of the signal light output from the optical diffraction element group 12 represents the results of these calculations.
- the signal light output from the optical diffraction element group 12 is also referred to as "output signal light".
- the light receiving section 13 is arranged on the optical path of the output signal light.
- the light receiving section 13 is configured to detect the output signal light.
- an image sensor that detects a two-dimensional intensity distribution of output signal light is used as the light receiving section 13 .
- a first specific example of the two images represented by the input signal light is two images containing the same object as a subject, and two images taken in different imaging directions. If the difference in imaging direction is small, these two images form a parallax image (for example, a right-eye image and a left-eye image). In this case, for example, two cameras forming a stereo camera are used as the two cameras C1 and C2. If the difference in imaging direction is large, these two images constitute a multi-angle image (eg front and side images). In this case, two cameras forming a multi-angle camera, for example, are used as the two cameras C1 and C2.
- a second specific example of the two images represented by the input signal light is two images containing the same object as a subject, and two images with different imaging magnifications (for example, a wide-angle image and a telephoto image).
- a wide-angle camera and a telephoto camera are used as the two cameras C1 and C2.
- the automatic inspection technology it is sometimes necessary to make judgments with reference to information regarding the entire inspection target (object) and information regarding details of the inspection target. Therefore, automatic inspection technology is a suitable application example of this configuration.
- a third specific example of the two images represented by the input signal light is two images containing the same object as a subject, and two images with different imaging wavelengths (for example, a visible light image and an infrared light image).
- two images with different imaging wavelengths for example, a visible light image and an infrared light image.
- a visible light camera and an infrared light camera are used as the two cameras C1 and C2.
- the laser processing process monitoring technology it may be necessary to make judgments with reference to information about the shape and temperature of the object to be processed (object). Therefore, the laser machining process monitoring technology is a suitable application example of this configuration.
- FIG. 2 is a plan view showing the configuration of the optical diffraction element 12ai.
- FIG. 3 is an enlarged perspective view of a portion of the optical diffraction element 12ai (the portion surrounded by the dotted line in FIG. 2).
- the optical diffraction element 12ai is composed of a plurality of microcells whose thicknesses or refractive indices are set independently of each other.
- the signal lights with different phases diffracted by the microcells interfere with each other, thereby performing a predetermined light calculation (two-dimensional intensity distribution according to a predetermined conversion rule). conversion) is performed.
- the term “microcell” refers to a cell with a cell size of less than 10 ⁇ m, for example.
- the term “cell size” refers to the square root of the cell area. For example, when the microcell has a square shape in plan view, the cell size is the length of one side of the cell. The lower limit of cell size is, for example, 1 nm.
- the optical diffraction element 12ai illustrated in FIG. 2 is composed of 200 ⁇ 200 microcells arranged in a matrix.
- the plan view shape of each microcell is a square of 500 nm ⁇ 500 nm
- the plan view shape of the optical diffraction element 12ai is a square of 100 ⁇ m ⁇ 100 ⁇ m.
- each microcell is composed of a quadrangular prism-shaped pillar having a square bottom surface with the length of each side equal to the size of the cell.
- the amount of phase change of light passing through the microcell is determined according to the height of this pillar. That is, the phase change amount of light transmitted through the microcells composed of tall pillars increases, and the phase change amount of light transmitted through the microcells composed of short pillars decreases.
- the setting of the thickness or refractive index of each microcell can be realized using machine learning, for example.
- machine learning for example, the two-dimensional intensity distribution of the signal light input to the optical diffraction element 12ai is input, and the two-dimensional intensity distribution of the signal light output from the optical diffraction element 12ai is output.
- a model can be used that includes the thickness or refractive index of each microcell as a parameter.
- the two-dimensional intensity distribution of signal light input to the optical diffraction element 12ai refers to a set of intensities of signal light input to each microcell constituting the optical diffraction element 12ai.
- the two-dimensional intensity distribution of the signal light output from the optical diffraction element 12ai is a set of the intensity of the signal light input to each microcell constituting the optical diffraction element 12ai+1 arranged after the optical diffraction element 12ai.
- it refers to a set of intensities of signal light input to each microcell constituting the light receiving section 13 arranged after the optical diffraction element 12ai.
- the light emitting section 11 is configured with a plurality of optical systems that guide the light from the object to the optical diffraction element group 12 .
- the light emitting unit 11 includes a first optical system (including, for example, lenses and mirrors) that guides light emitted from the object in a first direction to the optical diffraction element group 12, and a second optical system from the object. and a second optical system (including, for example, lenses and mirrors) that guides the light emitted in the direction to the optical diffraction element group 12 .
- An optical arithmetic device includes an optical diffraction element group including at least one optical diffraction element having an optical arithmetic function, and a signal light input to the optical diffraction element group, formed by different optical systems. and a light emitting unit that generates signal light representing each of the plurality of images that have been generated.
- the light emitting unit in addition to the configuration of the optical arithmetic device according to aspect 1, the light emitting unit generates signal light representing each of a plurality of images formed by different cameras. configuration is adopted.
- the plurality of images are images including the same object as a subject, and are captured in different directions. is an image of .
- the plurality of images are images including the same object as a subject, and have different imaging magnifications. is an image of .
- information regarding the entire object and information regarding details of the object can be used for optical calculation.
- the plurality of images are images including the same object as a subject, and have different imaging wavelengths. is an image of .
- information regarding the appearance of the object and information regarding the temperature of the object can be used for optical calculation.
- the optical diffraction element is composed of a plurality of microcells whose thicknesses or refractive indices are set independently of each other. The configuration is adopted.
- the optical diffraction element can be easily manufactured using nanoimprint technology or the like.
- An optical computing method is an optical computing method using an optical diffraction element group including at least one optical diffraction element having an optical computing function, wherein signal light input to the optical diffraction element group and generating signal light representing each of a plurality of images formed by different optical systems.
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Abstract
Description
本発明の一実施形態に係る光演算装置1について、図1を参照して説明する。図1は、光演算装置1の構成を示す斜視図である。
入力信号光の表す2つの画像の第1の具体例は、同一の対象物を被写体として含む2つの画像であって、撮像方向の異なる2つの画像である。撮像方向の差が小さい場合、これら2つの画像は、視差画像(例えば、右目用画像及び左目用画像)を構成する。この場合、2つのカメラC1,C2として、例えば、ステレオカメラを構成する2つのカメラを用いる。撮像方向の差が大きい場合、これら2つの画像は、マルチアングル画像(例えば、正面画像及び側面画像)を構成する。この場合、2つのカメラC1,C2として、例えば、マルチアングルカメラを構成する2つのカメラを用いる。これにより、光回折素子群12においては、単一の画像だけからでは得ることのできない情報、例えば、対象物の三次元情報を利用した光演算を行うことが可能になる。自動運転技術では、障害物(対象物)の三次元情報を参照した自動車の制御が必要になることがある。このため、自動運転技術は、本構成の好適な適用例となる。
光回折素子12aiの構成について、図2及び図3を参照して説明する。図2は、光回折素子12aiの構成を示す平面図である。図3は、光回折素子12aiの一部(図2において点線で囲んだ部分)を拡大した斜視図である。
本実施形態においては、入力信号光として、2つの画像を表す入力信号光を用いる構成を採用しているが、本発明は、これに限定されない。すなわち、入力信号光として、3つ以上の画像を表す入力信号光を用いる構成を採用してもよい。
本発明の態様1に係る光演算装置は、光演算機能を有する少なくとも1つの光回折素子からなる光回折素子群と、前記光回折素子群に入力する信号光であって、異なる光学系により形成された複数の画像の各々を表す信号光を生成する発光部と、を備えている。
本発明は、上述した実施形態に限定されるものでなく、請求項に示した範囲で種々の変更が可能であり、上述した実施形態にそれぞれ開示された技術的手段を適宜組み合わせて得られる実施形態についても、本発明の技術的範囲に含まれる。
11 発光部
12 光回折素子群
12a1,12a2 光回折素子
13 受光部
C1,C2 カメラ
Claims (7)
- 光演算機能を有する少なくとも1つの光回折素子からなる光回折素子群と、
前記光回折素子群に入力する信号光であって、異なる光学系により形成された複数の画像の各々を表す信号光を生成する発光部と、を備えている、
ことを特徴とする光演算装置。 - 前記発光部は、異なるカメラにより形成された複数の画像の各々を表す信号光を生成する、
ことを特徴とする請求項1に記載の光演算装置。 - 前記複数の画像は、同一の対象物を被写体として含む画像であって、撮像方向の異なる複数の画像である、
ことを特徴とする請求項2に記載の光演算装置。 - 前記複数の画像は、同一の対象物を被写体として含む画像であって、撮像倍率の異なる複数の画像である、
ことを特徴とする請求項2に記載の光演算装置。 - 前記複数の画像は、同一の対象物を被写体として含む画像であって、撮像波長の異なる複数の画像である、
ことを特徴とする請求項2に記載の光演算装置。 - 前記光回折素子は、厚み又は屈折率が互いに独立に設定された複数のマイクロセルにより構成されている、
ことを特徴とする請求項1~5の何れか一項に記載の光演算装置。 - 光演算機能を有する少なくとも1つの光回折素子からなる光回折素子群を用いた光演算方法であって、
前記光回折素子群に入力する信号光であって、異なる光学系により形成された複数の画像の各々を表す信号光を生成する工程を含んでいる、
ことを特徴とする光演算方法。
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Citations (7)
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JPH03233433A (ja) * | 1989-12-08 | 1991-10-17 | Oki Electric Ind Co Ltd | 光学並列相関演算装置 |
JPH08262516A (ja) * | 1995-03-23 | 1996-10-11 | Matsushita Giken Kk | 光学装置 |
US20060050391A1 (en) * | 2004-08-10 | 2006-03-09 | Johan Backlund | Structured-groove diffraction granting and method for control and optimization of spectral efficiency |
US20090284489A1 (en) * | 2000-10-20 | 2009-11-19 | Batchko Robert G | Multiplanar volumetric three-dimensional display apparatus |
JP2011523538A (ja) * | 2008-05-20 | 2011-08-11 | ペリカン イメージング コーポレイション | 異なる種類の撮像装置を有するモノリシックカメラアレイを用いた画像の撮像および処理 |
WO2019186548A1 (en) * | 2018-03-27 | 2019-10-03 | Bar Ilan University | Optical neural network unit and optical neural network configuration |
WO2020153504A1 (ja) * | 2019-01-25 | 2020-07-30 | 大日本印刷株式会社 | 回折光学素子、照明装置、投射装置、投射型表示装置および要素回折光学素子の製造方法 |
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- 2022-01-14 WO PCT/JP2022/001049 patent/WO2022176460A1/ja active Application Filing
- 2022-01-14 US US18/262,382 patent/US20240078420A1/en active Pending
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
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JPH03233433A (ja) * | 1989-12-08 | 1991-10-17 | Oki Electric Ind Co Ltd | 光学並列相関演算装置 |
JPH08262516A (ja) * | 1995-03-23 | 1996-10-11 | Matsushita Giken Kk | 光学装置 |
US20090284489A1 (en) * | 2000-10-20 | 2009-11-19 | Batchko Robert G | Multiplanar volumetric three-dimensional display apparatus |
US20060050391A1 (en) * | 2004-08-10 | 2006-03-09 | Johan Backlund | Structured-groove diffraction granting and method for control and optimization of spectral efficiency |
JP2011523538A (ja) * | 2008-05-20 | 2011-08-11 | ペリカン イメージング コーポレイション | 異なる種類の撮像装置を有するモノリシックカメラアレイを用いた画像の撮像および処理 |
WO2019186548A1 (en) * | 2018-03-27 | 2019-10-03 | Bar Ilan University | Optical neural network unit and optical neural network configuration |
WO2020153504A1 (ja) * | 2019-01-25 | 2020-07-30 | 大日本印刷株式会社 | 回折光学素子、照明装置、投射装置、投射型表示装置および要素回折光学素子の製造方法 |
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