KR102487970B1 - System and method for detecting defect of transparent object - Google Patents

Abstract

The transparent subject defect detection system of the present invention includes an imaging unit for generating and storing an image by photographing a transparent subject, a light source unit for emitting electromagnetic waves to the transparent subject, and a support unit for positioning the transparent subject.

Description

System and method for detecting defect of transparent object {System and method for detecting defect of transparent object}

The present invention relates to a transparent subject defect detection system.

Transparent objects such as diamonds or precious stones are valued according to their grade. Since the grade is determined according to the number and location of defects in the transparent subject, it is very important to determine defects in the transparent subject.

In the case of diamond, "4C" is a measure of value, and the 4C can be divided into four elements: Carat weight, Clarity, Color, and Cut. In the case of carat weight, the weight of a diamond can be accurately measured using an electronic scale as a standard for measuring the weight of a diamond.

Cut can judge the grade by comprehensively observing the overall proportions and finish of diamonds using a microscope. In addition, it is possible to accurately quantify the cut grade by introducing an automatic cutting measuring machine, but the cost is very high, so most of the methods using a microscope are used. Clarity can be determined using the plot method to determine the location and number of blemish and inclusion in an image magnified 10 times with a microscope. In the case of color, the grade can be judged by visually comparing the diamond and the master stone based on the master stone.

In the case of Clarity, Color, and Cut except for Carat weight, human eyes are judged, that is, visual measurement is used, so qualitative differences may occur depending on human error, which may affect the rating. Also, since Clarity, Color and Cut are judged separately, not only does it take a lot of time, but it is also less economical.

Therefore, it is necessary to develop a transparent subject defect detection system with excellent reliability by using a system that measures color and cut at the same time to increase economic efficiency in a system that measures clarity, and uses a quantified system that is not graded according to the judgment of an appraiser. Do.

An object of the present invention is to provide a transparent subject defect detection system with excellent reliability and high economic feasibility.

The above and other objects of the present invention can all be achieved by the present invention described below.

One aspect of the present invention relates to a transparent subject defect detection system.

According to one embodiment, the transparent subject defect detection system includes an imaging unit for generating and storing an image by photographing a transparent subject, a light source unit for emitting electromagnetic waves to the transparent subject, and a support unit for positioning the transparent subject.

The imaging unit is disposed above the position where the transparent subject is supported and generates a facet image by photographing the transparent subject, a focal length adjusting unit for adjusting the focal length of the camera, and storing the facet image generated by the camera It may include a storage unit and a control unit for controlling the camera, a focal length adjusting unit, and the storage unit.

The focal length adjusting unit may adjust the focal length while moving the focus of the camera by a predetermined distance in the thickness direction of the transparent subject.

The camera may capture two or more facet images while moving by a preset focal length.

The control unit may include one or more of a camera capture control module, a focal length adjustment module, a storage unit control module, and an image synthesis module.

The image synthesizing module may generate a synthesized image by overlapping two or more facet images stored in the storage unit.

The controller may further include a defect evaluation module, and the defect evaluation module may calculate a defect index by analyzing and searching the synthesized image.

The electromagnetic wave may have a wavelength of 10 nm to 1 mm.

The light source unit further includes a reference color light source, and the control unit further includes a color evaluation module, wherein the color evaluation module calculates a color index by comparing the reference color light source with at least one color of the facet image and the composite image. can

The control unit may further include a cutting evaluation module, and the cutting evaluation module may calculate a cutting index by estimating at least one of a table ratio, a crown angle, and a pavilion depth of the transparent subject through analysis of the synthesized image.

Another aspect of the present invention relates to a method for detecting defects in a transparent subject.

According to one embodiment, the step of seating the transparent object on the support, the step of emitting electromagnetic waves to the transparent object, the steps of photographing the transparent object N times with different focal lengths and storing each facet image, and the step of storing each facet image. The method may include obtaining a synthesized image by synthesizing the above facet images, and calculating a defect index of the transparent subject through the synthesized image.

The N number may be characterized in that it is 2 to 10 times.

The method may further include driving a reference color light source before photographing the transparent subject and calculating a color index of the transparent subject by comparing at least one of the facet image and the composite image with the reference color light source after photographing the transparent subject. there is.

The method may further include calculating a cutting index of the transparent subject through the synthesized image.

The present invention has an effect of providing a transparent subject defect detection system having excellent reliability and high economic efficiency.

1 is a diagram briefly showing the basic configuration of a transparent subject defect detection system according to an embodiment of the present invention.
2 is a block diagram briefly illustrating the configuration of an imaging unit of a transparent subject defect detection system according to an embodiment of the present invention.
3 is a block diagram briefly showing the configuration of a control unit of a transparent subject defect detection system according to an embodiment of the present invention.
4 is a diagram showing the basic configuration of a transparent subject defect detection system according to another embodiment of the present invention.
5 is a photograph of a synthesized image generated by synthesizing five facet images of a transparent subject having different focal lengths according to an embodiment of the present invention.
6 is a photograph of a composite image generated by synthesizing 7 facet images of a transparent subject having different focal lengths according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, it will be described in more detail the specific examples of the present application. However, the technology disclosed in this application is not limited to the specific examples described herein and may be embodied in other forms.

However, the specific examples introduced herein are provided so that the disclosed content can be thorough and complete and the spirit of the present application can be sufficiently conveyed to those skilled in the art. In the drawing, in order to clearly express the components of each device, the size of the components, such as width or thickness, is shown somewhat enlarged. In addition, although only some of the components are shown for convenience of description, those skilled in the art will be able to easily grasp the remaining components of the components.

When describing the drawings as a whole, it has been described from an observer's point of view, and when an element is referred to as being located above or below another element, this means that the one element is located directly above or below another element, or an additional element between them. It includes all meanings that may be intervened. In addition, those skilled in the art will be able to implement the spirit of the present application in various other forms without departing from the technical spirit of the present application. Also, like reference numerals in a plurality of drawings denote substantially the same elements.

On the other hand, singular expressions described in this application should be understood to include plural expressions unless the context clearly indicates otherwise, and terms such as 'include' or 'having' refer to the described features, numbers, steps, It is intended to specify the presence of an operation, component, part, or combination thereof, but precludes the possibility of existence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof. It should be understood that it does not.

In addition, in the present specification, 'X to Y' representing a range means 'X or more and Y or less'.

In the entire specification, when a part is said to be 'connected' to another part, this includes not only a case where it is directly connected, but also a case where it is 'electrically connected' with another element interposed therebetween. In addition, when a part is said to 'include' a certain component, it means that it may further include other components without excluding other components unless otherwise stated.

In this specification, a “unit” includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Further, one unit may be realized using two or more hardware, and two or more units may be realized by one hardware. On the other hand, '~ unit' is not limited to software or hardware, and '~ unit' may be configured to be in an addressable storage medium or configured to reproduce one or more processors. Therefore, as an example, '~unit' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. Functions provided within components and '-units' may be combined into smaller numbers of components and '-units' or further separated into additional components and '-units'. In addition, components and '~parts' may be implemented to play one or more CPUs in a device or a secure multimedia card.

Transparent subject defect detection system

A transparent subject defect detection system according to an embodiment of the present invention will be described with reference to FIGS. 1 to 3 . 1 is a basic configuration of a transparent subject defect detection system according to an embodiment of the present invention.

Referring to FIG. 1, a transparent subject defect detection system 1000 according to one embodiment, which is one aspect of the present invention, includes an imaging unit 100 for generating and storing an image by photographing a transparent subject 1, and the transparent It includes a light source unit 200 for emitting electromagnetic waves to the subject 1 and a support unit 300 for positioning the transparent subject.

The transparent object 1 may be a diamond, a precious stone, a semiconductor ingot, or the like.

The imaging unit 100 may capture the transparent subject 1 to generate and store an image, and the imaging unit 100 of the transparent subject defect detection system 1000 of the present invention detects defects in the transparent subject 1. In addition, it has the advantage of being able to judge the color and cutting state.

In particular, the transparent subject defect detecting system 1000 including the imaging unit 100 can compensate for the disadvantages of the transparent subject defect detecting system that may cause human error by using a conventional sight measurement method.

2 is a block diagram briefly illustrating the configuration of an imaging unit of a transparent subject defect detection system according to an embodiment of the present invention.

Referring to FIGS. 1 and 2 , the image pickup unit 100 includes a camera 110 disposed above a position where the transparent subject 1 is supported and generating a facet image by photographing the transparent subject 1; A focal length adjustment unit 120 for adjusting the focal length of the camera 110, a storage unit 130 for storing facet images generated by the camera 110, and the camera 110, the focal length adjustment unit 120 And it may include a control unit 140 that controls the storage unit 130.

Specifically, the storage unit 130 may store a facet image of the transparent subject 1 photographed by the camera 110 . The focal length of the camera 110 may be adjusted by the focal length adjusting unit 120 . The facet image refers to an image composed of a continuous plane of one image as a facet image.

The focal length adjusting unit 120 may adjust the focal length while moving the focus of the camera 110 by a predetermined distance in the thickness direction of the transparent subject 1 .

In one embodiment, the preset distance may be set by reflecting depth of field (DOF). In this case, the Zeiss formula may be applied to the depth of field, and for example, https://qastack.kr/photo/24826/is-there-a-formula-to-calculate-dof may be referred to. Specifically, the depth of field may consider the viewing distance, resolution of the final image, zoom, focal length, aperture, circles of confusion (CoC), distance between the camera 110 and the subject, lens size, and the like.

The focal length may be calculated so that depths of field corresponding to adjacent focal lengths overlap each other by 0.01 mm to 0.5 mm. In this case, two or more facet images overlap adjacent facet images by 0.01 mm to 0.5 mm in depth of field, so that all areas of the transparent subject 1 can be captured, and the longer the focal length, the greater the depth of field. By taking only the minimum required facet image, there is an effect of increasing the reliability of various indices calculated from the composite image and improving the detection efficiency.

A distance sensor (not shown) may be applied to the distance between the camera 110 and the subject, and the number of times the camera takes pictures is determined according to the calculated depth of field.

The camera 110 may capture two or more facet images while moving by the preset focal length. The camera 110 may be a camera 110 capable of capturing electromagnetic waves having a wavelength of 10 nm to 1 mm, specifically, 400 nm to 700 mm. Depending on the difference in the refractive index of light passing through the above range of wavelengths, it is possible to confirm the exact position of the defect, thereby increasing the reliability of defect detection.

3 is a block diagram briefly showing the configuration of a control unit of a transparent subject defect detection system according to an embodiment of the present invention.

1 to 3, the control unit 140 includes at least one of a camera capture control module 141, a focal length adjustment module 142, a storage unit control module 143, and an image synthesis module 144. can do.

The camera photographing control module 141 may control the overall operation of the camera 110 and set a range of the transparent subject 1 to be photographed. The camera capture control module 141 transmits a control signal to the camera 110, and the camera 110 can capture an image of a corresponding area according to the control signal.

The focal length adjusting module 142 may control the focal length according to the preset distance. Depending on the size or type of the transparent subject 1, the set value of the focal length may be different. The focal length adjusting module 142 transmits a control signal to the focal length adjusting unit 120, and the focal length adjusting unit 120 adjusts the focal length of the camera 110 according to the control signal, so that the camera (110) can capture two or more facet images.

The image synthesizing module 144 may generate a synthesized image by overlapping two or more facet images stored in the storage unit 130 .

Specifically, facet images according to the depth of the transparent subject 1 are photographed and stored by adjusting the focal length, and then the image composition module 144 overlaps the facet images to generate a synthesized image. The composite image may be transmitted to the defect evaluation module 145 . The facet image can be photographed by adjusting the focal length to prevent a problem in which only a specific surface is in focus, so that a facet image with high sharpness can be obtained in all areas. Therefore, the composite image obtained by synthesizing the facet images also has high sharpness, so it is easy to determine defects. Two or more facet images were obtained by varying the focal length, and composite image photos generated by combining them are shown in FIGS. 5 and 6 .

The controller 140 may further include a defect evaluation module 145, and the defect evaluation module 145 may calculate a defect index by analyzing and searching the synthesized image.

Specifically, the defect index may be calculated through image analysis of a synthesized image, and a real defect and a reflective defect may be distinguished, and each weight may be changed and reflected in the defect index.

Alternatively, the defect evaluation module 145 may calculate a defect index by learning the defect evaluation module 205 through machine learning. For the machine learning, one or more of a speeded up robust features (SRF) algorithm, a convolutional neural network (CNN) algorithm, and a support vector machine (SVM) algorithm may be applied.

The transparent subject defect detection system 1000 including the defect evaluation module 145 can calculate a defect index through image analysis or machine learning, and thus has the advantage of obtaining a highly reliable defect index.

The electromagnetic wave may have a wavelength of 10 nm to 1 mm, specifically, 400 nm to 700 nm. Depending on the difference in the refractive index of light passing through the above range of wavelengths, the exact position of the defect can be confirmed, thereby increasing the reliability of defect detection.

The light source unit 200 may further include a reference color light source, and the controller 140 may further include a color evaluation module 146 . Specifically, the color evaluation module 146 may calculate a color index by comparing the reference color light source with at least one color of the facet image and composite image.

Alternatively, the color evaluation module 146 may calculate a color index by learning the defect evaluation module 206 through machine learning. For the machine learning, one or more of a speeded up robust features (SRF) algorithm, a convolutional neural network (CNN) algorithm, and a support vector machine (SVM) algorithm may be applied.

The transparent subject defect detection system 1000 including the color evaluation module 146 has an advantage of excellent reliability because it can prevent human error compared to the prior art of determining color using a master stone. In addition, whereas conventionally, only the defect index can be determined, the transparent subject defect detecting system 1000 of the present invention can calculate not only the defect index but also the color index by applying electromagnetic waves of 400 nm to 700 nm to the light source unit 200. It has the advantage of high economic efficiency.

The control unit 140 further includes a cutting evaluation module 147, and the cutting evaluation module 147 determines one of the table ratio, crown angle, and pavilion depth of the transparent subject 1 through the analysis of the synthesized image. By estimating the above, the cutting index can be calculated.

For example, in the table ratio, the lines from the vertex where the star facet junction lines meet through the table edge to the star facet vertex are gathered to form a square, and the weight is given according to how much each line constituting the square is bent. It can be reflected in the cutting index by changing . The crown angle can be reflected in the cutting index by varying the weight according to the difference in width of the pavilion main facet seen from the corner of the bezel facet and the corner of the table facet, and the depth of the pavilion according to the degree of reflection of the table.

Alternatively, the cutting evaluation module 147 may calculate a color index by learning the cutting evaluation module 147 through machine learning. For the machine learning, one or more of a speeded up robust features (SRF) algorithm, a convolutional neural network (CNN) algorithm, and a support vector machine (SVM) algorithm may be applied.

Transparent subject defect detection method

A transparent subject defect detection method according to another embodiment of the present invention will be described with reference to FIG. 4 . 4 is a view showing the basic configuration of a transparent subject defect detection system 2000 according to another embodiment of the present invention, in which diamond is applied to the transparent subject 2. If the transparent subject 2 is a diamond, the description of each configuration can also be applied to the transparent subject defect detection system, which is one aspect of the present invention.

In this specific embodiment, the upper portion of the transparent subject 2 is referred to as a crown, and the lower portion is referred to as a pavilion.

The crown consists of a table, star facet, bezel facet and upper girdle facet, and the widest part in the center of the crown is called the table.

The pavilion is composed of a pavilion facet, a lower girdle facet, and a culet, and a small face located in the center of the pavilion is called a culet.

Another aspect of the present invention, a transparent subject defect detection method, includes the steps of seating the transparent subject 2 on a support, emitting electromagnetic waves to the transparent subject 2, and varying the focal length to detect the transparent subject 2. It may include photographing N times and storing each facet image, synthesizing two or more stored facet images to obtain a synthesized image, and calculating a defect index of the transparent subject 2 through the synthesized image. .

After the transparent subject 2 is seated on the support 600 , the light source 500 emits electromagnetic waves to the transparent subject 2 . The electromagnetic wave may have a wavelength of 10 nm to 1 mm, specifically, 400 nm to 700 nm.

In a state where the electromagnetic waves are being emitted, the camera 410 may photograph the transparent subject 2 N times by varying the focal length. The focal length may be adjusted while moving by a preset distance by a focal length adjusting module.

The camera photographs the transparent subject 2 N times, and stores each facet image in the storage unit 430 . The image synthesizing module may generate a synthesized image by overlapping two or more stored facet images.

The combination evaluation module may calculate a defect index by analyzing and searching the synthesized image. Alternatively, the defect index may be calculated by learning the coupling evaluation module through machine learning.

The grade of the transparent object 2 may be determined by determining whether a defect exists and the location of the defect using the calculated defect index.

The N number may be characterized in that 2 to 10 times. In the above range, it is possible to obtain a synthesized image that is easy to calculate the defect index, and noise may occur in the case of more than 10 times.

The transparent subject defect detection method comprises the steps of driving a reference color light source before photographing the transparent subject 2 and comparing at least one of the facet image and the composite image with the reference color light source after photographing the transparent subject 2. A step of calculating a color index of the transparent subject 2 may be further included.

The transparent subject defect detection method can calculate not only a defect index but also a color index.

After the transparent subject 2 is seated on the support 600 and electromagnetic waves are emitted to the transparent subject 2, a reference color light source may be driven. The reference color light source may be an LED, but is not limited thereto.

The transparent subject 2 is photographed N times at different focal lengths, and each facet image is stored in the storage unit 430 . The image synthesizing module may generate a synthesized image by overlapping two or more stored facet images.

A color index may be calculated by comparing at least one of the stored facet image and composite image with a reference color light source.

The color evaluation module may calculate a color index by comparing one or more colors of the facet image and the composite image with a reference color light source. Alternatively, the color index may be calculated by learning the color evaluation module through machine learning.

A color grade of the transparent subject 2 may be determined using the calculated color index.

The transparent subject defect detection method may also calculate a cutting index.

After the transparent subject 2 is seated on the support 600 and electromagnetic waves are emitted to the transparent subject 2, the transparent subject 2 may be photographed N times by varying the focal length.

Each facet image may be stored in the storage unit 430, and the image synthesis module may generate a synthesized image by overlapping two or more stored facet images.

The cutting evaluation module may calculate a cutting index by estimating one or more of a table ratio, a crown angle, and a pavilion depth of the transparent subject 2 through the analysis of the synthesized image. Alternatively, the cutting index may be calculated by learning the cutting evaluation module through machine learning.

A cutting grade of the transparent subject 2 may be determined using the calculated cutting index.

The transparent subject defect detection system and method simultaneously measure not only the defect index but also the color index and the cutting index to increase economic feasibility and provide a transparent subject defect detection system and method with excellent reliability by using a quantified system. .

Although the embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, but may be manufactured in various different forms, and those skilled in the art to which the present invention belongs can understand the technical spirit of the present invention. However, it will be understood that it may be embodied in other specific forms without changing its essential features. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

1: Transparent subject 2: Transparent subject
100: imaging unit 110: camera
120: focal length adjustment unit 130: storage unit
140: control unit 141: camera shooting control module
142: focal length adjustment module 143: storage unit control module
144: image synthesis module 145: defect evaluation module
146: color evaluation module 147: cutting evaluation module
200: light source unit 300: support unit
400: imaging unit 410: camera
420: focal length adjustment unit 430: storage unit
440: control unit
1000: transparent subject defect detection system
2000: Transparent subject defect detection system

Claims (10)

an imaging unit including a camera generating a facet image by taking a picture of a transparent subject including a diamond, precious stone or semiconductor ingot, and storing the facet image;
a light source unit that emits electromagnetic waves to the transparent subject;
a support for positioning the transparent subject; and
A controller that controls the camera and includes an image synthesis module;
The camera captures two or more facet images while moving by a preset focal length,
The transparent subject defect detection system, characterized in that the image synthesis module generates a composite image by overlapping two or more facet images.
According to claim 1,
The imaging unit,
a focal length adjustment unit for adjusting the focal length of the camera; and
A storage unit for storing the facet image generated by the camera; further comprising,
The control unit further controls the focal length adjusting unit and the storage unit.
According to claim 2,
The focal length adjusting unit,
The transparent subject defect detection system for adjusting the focal length while moving the focus of the camera by a predetermined distance in the thickness direction of the transparent subject.
delete According to claim 2,
The control unit,
A transparent subject defect detection system further comprising at least one of a camera shooting control module, a focal length adjustment module, and a storage unit control module.
delete According to claim 5,
The control unit,
Further comprising a defect evaluation module,
The defect evaluation module analyzes and searches the synthesized image to calculate a defect index.
According to claim 1,
The electromagnetic wave,
A transparent subject defect detection system, characterized in that the wavelength is 10 nm to 1 mm.
Placing a transparent object including a diamond, precious stone or semiconductor ingot on a support;
emitting electromagnetic waves to the transparent subject;
photographing the transparent subject N times by varying the focal length set in advance and storing each facet image;
obtaining a synthesized image by overlapping two or more stored facet images; and
A transparent subject defect detection method comprising: calculating a defect index of the transparent subject through the synthesized image.
According to claim 9,
driving a reference color light source before photographing the transparent subject; and
After capturing the transparent subject, comparing at least one of the facet image and the composite image with the reference color light source to calculate a color index of the transparent subject;

Images