CN110717901A - Cursor-based software scene DOE performance evaluation method - Google Patents

Cursor-based software scene DOE performance evaluation method Download PDF

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CN110717901A
CN110717901A CN201910924963.3A CN201910924963A CN110717901A CN 110717901 A CN110717901 A CN 110717901A CN 201910924963 A CN201910924963 A CN 201910924963A CN 110717901 A CN110717901 A CN 110717901A
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cursor
doe
performance
based software
error
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CN110717901B (en
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黄若普
鲁亚东
李安
陈驰
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Shenzhen Ansijiang Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/0012—Optical design, e.g. procedures, algorithms, optimisation routines
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/42—Diffraction optics, i.e. systems including a diffractive element being designed for providing a diffractive effect
    • G02B27/4205—Diffraction optics, i.e. systems including a diffractive element being designed for providing a diffractive effect having a diffractive optical element [DOE] contributing to image formation, e.g. whereby modulation transfer function MTF or optical aberrations are relevant
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection

Abstract

The invention provides a software scene DOE performance evaluation method based on a cursor, which comprises the following steps: s1: the speckle pattern with the cursor in the center is copied by the optical diffraction element and then projected to a target scene object; s2: collecting a pattern projected onto an object in a target scene; s3: randomly selecting a plurality of cursors from the collected image, and calculating fitting errors of the cursors; s4: and evaluating the performance of the DOE according to the obtained error mean value. The method for calculating the speckle pattern error by using the released cursor can avoid the traditional fussy process of calculating the error by calculating the pixel depth; the method can directly perform fitting on the selected cursor to obtain the error, and has a quick and efficient process on the basis of ensuring the precision.

Description

Cursor-based software scene DOE performance evaluation method
Technical Field
The invention relates to the technical field of graphic projection, in particular to a software scene DOE performance evaluation method based on a cursor.
Background
Diffractive optics are very widely used. In some applications, Diffractive Optical Elements (DOEs) are used to generate the desired projection pattern according to a corresponding purpose, such as optical three-dimensional mapping. However, under the influence of different device tolerance, environment and operation, different fault deviations occur in the DOE, and further the precision and the quality of the product are directly influenced. Therefore, whether the DOE performance can be monitored and evaluated timely and efficiently in practical application becomes a work with profound significance.
The chinese patent application with prior publication number 109342028A provides a diffractive optical element detection method, including: a calibration stage: the light source emits light beams, the light beams are converged through the lens and project parallel light beams to the detector, and the control processor receives parallel light beam images collected by the detector; a measurement stage: the light source emits light beams, the light beams are converged through the lens and project parallel light beams to the DOE, the DOE receives and splits the parallel light beams and projects diffracted light beams to the detector, and the control processor receives diffracted light beam images collected by the detector; and (3) performance detection stage: a control processor receives the parallel beam image and the diffracted beam image collected from the detector and processes to detect the performance of the DOE. The method can be used for detecting the performance of the DOEs and classifying the DOEs in batches.
And chinese patent application publication No. 109974978A provides a performance detection method of a diffractive optical element, including: controlling a light emitting device to emit predetermined light to a diffractive optical element which diffracts the predetermined light to form a plurality of light spots on a receiving screen; acquiring images of a plurality of said spots of light; calculating the diffraction efficiency, diffraction uniformity and field angle of the diffractive optical element according to the image.
Disclosure of Invention
The invention mainly aims to solve the performance judgment problem of a Diffractive Optical Element (DOE) in the application process and provides a method for evaluating the performance of the DOE by using the fitting loss of a speckle cursor in a software scene; according to the method, the speckle depth can not be calculated, the fitting error analysis can be directly carried out on the set cursor, and the DOE performance can be evaluated according to the size of the fitting error.
The invention adopts the following specific technical scheme:
a cursor-based software scene DOE performance evaluation method comprises the following steps:
s1: the speckle pattern with the cursor in the center is copied by the optical diffraction element and then projected to a target scene object;
s2: collecting a pattern projected onto an object in a target scene;
s3: randomly selecting a plurality of cursors from the collected image, and calculating fitting errors of the cursors;
s4: and evaluating the performance of the DOE according to the obtained error mean value.
According to the method, the speckle pattern error is calculated by using the input cursor, so that the traditional complex process of calculating the pixel depth to obtain the error can be avoided. The method can directly perform fitting on the selected cursor to obtain the error, and has a quick and efficient process on the basis of ensuring the precision. In addition, the invention provides a method for evaluating the DOE performance in real time by using a software program, so that the DOE performance can be monitored in real time, and the precision and the quality of a product can be effectively mastered.
Preferably, the cursor is composed of discrete speckle points.
Preferably, the cursor is in a cross shape.
In the present invention, the design of the cursor may be, but not limited to, a cross shape, an x shape, or other distribution shapes that are convenient for collection and calculation.
Preferably, in step S3, a cursor is selected in the acquired speckle pattern grid image according to the row, column, diagonal or position rule.
Preferably, in step S3, several cursors located on the same straight line are selected in the acquired speckle pattern grid image.
Preferably, for the selected cursor Z (x, y), there is a linear relationship between the variables x, y, and the regression equation is a straight line:
y＝b0+b1x
selected cursor Zi(xi,yi) The residual in the direction of the line y is:
Vi＝yi-y＝yi-b0-b1xi
according to the principle of least squares:
Figure BDA0002218654570000031
where S (y) represents the mean error value.
Preferably, in step S4, a performance determination threshold is set, and when the error mean value is greater than the performance determination threshold, it is determined that the DOE failure determination condition is satisfied, and it is determined that a performance problem occurs in the diffractive optical element DOE.
Preferably, the fitting error is calculated for each of the plurality of images acquired in step S3, and the errors are summed and averaged.
Compared with the prior art, the invention has the following beneficial effects:
(1) the speckle pattern error calculation method provided by the invention can be used for directly fitting the placed cursor without calculating the speckle depth, and deducing the speckle pattern error through the fitting error, so that the complicated mode of conventionally utilizing the pixel depth to calculate is avoided.
(2) The method for evaluating the DOE performance based on the program design can determine the DOE performance error condition by analyzing the fitted cursor error and evaluate the DOE performance in real time according to the DOE performance error condition. The DOE performance can be judged quickly and efficiently, and the DOE performance information can be mastered in time.
Drawings
FIG. 1 is a diagram of an optical three-dimensional mapping system;
FIG. 2 is a schematic diagram of a speckle imaging system;
FIG. 3 is a DOE cross cursor setting diagram;
FIG. 4 is a schematic diagram of cross cursor fitting error;
fig. 5 is a program processing flow diagram.
Fig. 6 is a DOE performance evaluation diagram in a software scenario.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A cursor-based software scene DOE performance evaluation method comprises the following steps:
s1: the speckle pattern with the cursor in the center is copied by the optical diffraction element and then projected to a target scene object;
s2: collecting a pattern projected onto an object in a target scene;
s3: randomly selecting a plurality of cursors from the collected image, and calculating fitting errors of the cursors;
s4: and evaluating the performance of the DOE according to the obtained error mean value.
In another embodiment, as shown in fig. 1, an optical three-dimensional mapping system corresponding to the cursor-based software scene DOE performance evaluation method includes: a projection assembly 9 comprising a radiation source 10 and a Diffractive Optical Element (DOE) 3. A set speckle pattern is generated and projected by DOE replication onto the target scene object. And the image acquisition component 6 is used for acquiring the pattern projected onto the scene body and then sending the acquired data to the processor 8 for processing. The image acquisition assembly 6 will acquire one or more patterns, depending on the programming of the processor.
Fig. 2 is a schematic diagram of a speckle imaging system. The radiation source 10 emits a laser beam (e.g., infrared laser) to a Diffractive Optical Element (DOE), and the DOE diffuses and replicates the incident laser beam into a plurality of laser beams, which are then uniformly projected onto the surface of the object in space. The reflected pattern of the object surface is imaged on an infrared camera, the camera records the reflected pattern, and the reflected speckle pattern records the depth information of the space object.
In another embodiment, the incident light carries a speckle pattern with a cursor in the center, and after passing through an optical diffraction element (DOE), the light beam is shaped, replicated, and projected onto a target scene object to form a predetermined speckle pattern with different distributions, angles, and intensities.
In another embodiment, a cursor is placed in the center of the image while the speckle pattern is being set, the cursor consisting of discrete speckle points.
In another embodiment, for the convenience of acquisition and calculation, the cursor distribution is in a cross shape, namely a cross cursor; as shown in fig. 3.
In another embodiment, the cursor may be a star or other distribution shape that facilitates acquisition and computation.
In the embodiment shown in fig. 4, the randomly selecting a plurality of cursors means that a plurality of cursors are randomly selected in a grid-shaped speckle pattern continuously or discontinuously according to a row, a column, a diagonal or a certain relative position rule. Fitting refers to calculating the cursor error by the least squares method.
In the embodiment shown in fig. 5, several cursors located on the same straight line are selected in the acquired speckle pattern grid image. Each line in the figure represents a selection, but is not limited to the selection in the figure.
For the selected cursor Z (x, y), there is a linear relationship between the variables x, y, and the regression equation is a straight line:
y＝b0+b1x
selected cursor Zi(xi,yi) The residual in the direction of the line y is:
Vi＝yi-y＝yi-b0-b1xi
according to the principle of least squares:
Figure BDA0002218654570000051
where S (y) represents the mean error value.
If it is not
Figure BDA0002218654570000052
The smaller the value, the more approximate the fit to the cursor, the smaller the standard deviation s (y), i.e. the smaller the speckle pattern error.
In another embodiment, in step S4, a performance judgment threshold needs to be set, and when the error mean value is greater than the performance judgment threshold, it is determined that the DOE failure judgment condition is satisfied, and it is determined that a performance problem occurs in the diffractive optical element DOE.
In another embodiment, the fitting error for each speckle pattern is calculated for the plurality of images acquired in step S3, and the mean of the fitting errors for all the acquired speckle patterns is determined. And comparing the fitting error mean value with a set threshold value to determine whether the DOE performance is in a normal range. The smaller the fitting error, the higher the DOE performance.
In another embodiment, the DOE performance evaluation under the software scenario is shown in fig. 6, and the steps are as follows:
1) processor 8 continuously or intermittently captures a plurality of frames of images via image capture assembly 6 under program guidance. And when the number of the collected images is less than the threshold value N, the collection is continued until the threshold value condition is met.
2) And when the number of the collected images meets the threshold condition N, calculating a fitting error of each image, and finally performing mean value processing after summing the errors.
3) And evaluating the performance of the DOE according to the obtained error mean value. And when the error mean value is larger than the performance judgment threshold value, judging that the DOE fault judgment condition is met, and judging that the performance problem occurs in the DOE of the diffractive optical element. When the error mean value is smaller than the performance judgment threshold value, the DOE is considered to work normally, and the performance is good.
The above description is only exemplary of the preferred embodiments of the present invention, and is not intended to limit the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. A cursor-based software scene DOE performance evaluation method is characterized by comprising the following steps:
s1: the speckle pattern with the cursor in the center is copied by the optical diffraction element and then projected to a target scene object;
s2: collecting a pattern projected onto an object in a target scene;
s3: randomly selecting a plurality of cursors from the collected image, and calculating fitting errors of the cursors;
s4: and evaluating the performance of the DOE according to the obtained error mean value.
2. The cursor-based software scene DOE performance evaluation method of claim 1, wherein the cursor consists of discrete speckle points.
3. The cursor-based software scene DOE performance assessment method according to claim 1 or 2, wherein said cursor is in the shape of a cross.
4. The cursor-based software scene DOE performance evaluation method of claim 1, wherein in step S3, a cursor is selected in a row, column, diagonal or position rule in the acquired speckle pattern grid image.
5. The cursor-based software scene DOE performance evaluation method according to claim 1, wherein in step S3, several cursors located on the same straight line are selected from the acquired speckle pattern grid image.
6. A cursor-based software scene DOE performance assessment method according to claim 5, characterized in that for a selected cursor Z (x, y), there is a linear relationship between the variables x, y, and the regression equation is a straight line:
y＝b0+b1x
selected cursor Zi(xi,yi) The residual in the direction of the line y is:
Vi＝yi-y＝yi-b0-b1xi
according to the principle of least squares:
where S (y) represents the mean error value.
7. The cursor-based software scene DOE performance evaluation method according to claim 1, wherein in step S4, a performance judgment threshold is set, and when the error mean value is greater than the performance judgment threshold, the DOE failure judgment condition is considered to be satisfied, and it is determined that a performance problem occurs in the diffractive optical element DOE.
8. The cursor-based software scene DOE performance assessment method according to claim 1, wherein a plurality of images collected in step S3 are subjected to a mean processing after calculating a fitting error for each image and summing the errors.
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