CN112393880A - Screen replacement detection method and device - Google Patents
Screen replacement detection method and device Download PDFInfo
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- CN112393880A CN112393880A CN202011423339.4A CN202011423339A CN112393880A CN 112393880 A CN112393880 A CN 112393880A CN 202011423339 A CN202011423339 A CN 202011423339A CN 112393880 A CN112393880 A CN 112393880A
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- G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
Abstract
The invention relates to a screen replacement detection method and device, which are used for extracting light beam pattern characteristics of an original image after the original image of an equipment screen irradiated by a light beam is acquired, identifying the light beam pattern characteristics according to a preset identification model and judging whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
Description
Technical Field
The invention relates to the technical field of electronic products, in particular to a screen replacement detection method and device.
Background
With the development of electronic product technology, various intelligent devices such as smart phones, notebook computers, tablet computers, and the like are developed. At present, along with the rapid development of economy and technology, the popularization and the updating speed of intelligent equipment are also faster and faster. Taking a smart phone as an example, the coming of the 5G era accelerates the generation change of the smart phone. In the iterative process of the intelligent equipment, effective recovery is one of effective utilization means of the residual value of the intelligent equipment, and the chemical pollution to the environment and the waste can be reduced.
In the recovery process of intelligent equipment, equipment evaluation is used as an important intermediate link for recovering the equipment and replacing the equipment with new equipment, and the accuracy and the rationality of the evaluation indirectly influence the success rate of recovering the equipment and replacing the equipment with new equipment. In the process of recycling the equipment, whether the screen is originally installed or not has great influence on recycling the gross profit. Therefore, in the equipment recovery, whether the screen of the analysis recovery equipment is replaced or not needs to be detected, and an important reference is provided for the equipment recovery.
The traditional mode for detecting whether the screen of the intelligent equipment is replaced is mainly that whether the screen is replaced is determined by the subjective judgment of professional quality inspectors through the observation of human eyes of the professional quality inspectors. However, human eye observation is time-consuming and labor-consuming, and subjective judgment is affected by factors such as experience and state of professional quality inspectors, so that the accuracy of judgment is difficult to ensure.
Disclosure of Invention
Therefore, it is necessary to provide a method and an apparatus for detecting screen replacement in order to overcome the defects of the conventional method for detecting whether the screen of the smart device is replaced.
A screen replacement detection method includes the steps:
acquiring an original image of a device screen irradiated by a received light beam;
extracting the light beam pattern characteristics of the original image;
identifying the light beam pattern characteristics according to a preset identification model, and judging whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
According to the screen replacement detection method, after the original image of the equipment screen irradiated by the light beam is obtained, the light beam pattern characteristics of the original image are extracted, the light beam pattern characteristics are identified according to the preset identification model, and whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
In one embodiment, before the process of acquiring the original image of the device screen receiving the light beam irradiation, the method further comprises the following steps:
the irradiation device is controlled to irradiate a light beam onto the screen of the apparatus.
In one embodiment, the process of extracting the beam pattern feature of the original image includes the steps of:
preprocessing an original image to obtain a processed image;
beam pattern features are extracted from the processed image.
In one embodiment, the process of pre-processing the original image includes the steps of:
cutting an original image into an image with a set size to obtain a cut image;
and dividing the image of the area where the light beam pattern is located in the cutting image to obtain a processing image.
In one embodiment, the process of recognizing the beam pattern features according to the preset recognition model includes the steps of:
converting the beam pattern features into feature vectors;
and identifying the characteristic vector according to a preset identification model.
In one embodiment, the training process of the predetermined recognition model includes the steps of:
acquiring training original images of various types of training equipment;
defining a detection label for each training original image; the detection label is used for representing that a screen of the training equipment is original or replaced;
and performing data training on the training original image and the detection label to obtain a preset identification model.
In one embodiment, the process of data training the training raw images and the detection labels includes the steps of:
and performing data training on the training original image and the detection label through a machine learning classification algorithm.
A screen replacement detecting device comprising:
the image acquisition module is used for acquiring an original image of the equipment screen irradiated by the received light beam;
the characteristic extraction module is used for extracting the light beam pattern characteristics of the original image;
the characteristic identification module is used for identifying the light beam pattern characteristics according to a preset identification model and judging whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
According to the screen replacement detection device, after the original image of the equipment screen irradiated by the light beam is obtained, the light beam pattern characteristics of the original image are extracted, the light beam pattern characteristics are identified according to the preset identification model, and whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
A computer storage medium having computer instructions stored thereon, the computer instructions when executed by a processor implementing the screen replacement detection method of any of the above embodiments.
After the computer storage medium obtains the original image of the equipment screen irradiated by the received light beam, the light beam pattern characteristics of the original image are extracted, the light beam pattern characteristics are identified according to the preset identification model, and whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
A computer device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the screen replacement detection method of any one of the embodiments.
After the computer equipment obtains the original image of the equipment screen irradiated by the received light beam, the light beam pattern characteristics of the original image are extracted, the light beam pattern characteristics are identified according to the preset identification model, and whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
Drawings
FIG. 1 is a flowchart of a screen replacement detection method according to an embodiment;
FIG. 2 is a flowchart of a screen replacement detection method according to another embodiment;
FIG. 3 is a flow diagram of a pre-processing method according to one embodiment;
FIG. 4 is a flowchart of a screen replacement detection method according to yet another embodiment
FIG. 5 is a flowchart of a method for training a predetermined recognition model according to an embodiment;
fig. 6 is a block diagram of a screen replacement detecting apparatus according to an embodiment.
Detailed Description
For better understanding of the objects, technical solutions and effects of the present invention, the present invention will be further explained with reference to the accompanying drawings and examples. Meanwhile, the following described examples are only for explaining the present invention, and are not intended to limit the present invention.
The embodiment of the invention provides a screen replacement detection method.
Fig. 1 is a flowchart illustrating a screen replacement detection method according to an embodiment, and as shown in fig. 1, the screen replacement detection method according to an embodiment includes steps S100 to S102:
s100, acquiring an original image of a device screen irradiated by a received light beam;
the screen of the equipment to be recovered is irradiated by a light beam at a specific angle and a specific distance, and the screen of the equipment is shot by the camera equipment to obtain an original image of the screen of the equipment. And acquiring an original image acquired by the camera equipment.
In one embodiment, fig. 2 is a flowchart of a screen replacement detection method according to another embodiment, and as shown in fig. 2, before the process of acquiring an original image of a device screen receiving the light beam irradiation in step S100, the method further includes step S200:
and S200, controlling the irradiation device to irradiate the light beam onto the screen of the equipment.
Before step S100, the irradiation device is controlled to irradiate a light beam onto the screen of the device, so as to realize real-time irradiation and collection. In one embodiment, the beam is a 150 lumen to 1000 lumen intense light beam.
S101, extracting light beam pattern characteristics of an original image;
wherein the light beam impinges on the device screen and forms a light beam pattern feature on the visually black device screen in accordance with the reflection of the device screen. In one embodiment, the beam pattern features include the shape or color of the beam pattern, etc. And extracting the light beam pattern characteristics through an image processing algorithm.
In one embodiment, as shown in fig. 2, the process of extracting the beam pattern feature of the original image in step S101 includes steps S300 and S301:
s300, preprocessing the original image to obtain a processed image;
s301, extracting beam pattern features in the processed image.
By preprocessing the original image, the data processing amount required by the light beam pattern feature extraction is reduced, and the accuracy of the light beam pattern feature extraction is improved. The preprocessing comprises image filtering, image cutting or Fourier transformation and the like.
In one embodiment, fig. 3 is a flowchart of a preprocessing method according to an embodiment, and as shown in fig. 3, the process of preprocessing the original image in step S300 includes steps S400 and S401:
s400, cutting the original image into an image with a set size to obtain a cut image;
and after the original image is acquired, cutting the original image into a set size. Wherein the set size may be determined according to the irradiation position of the light beam.
S401, an image of the area where the beam pattern is located is divided in the cutting image, and a processing image is obtained.
And (3) dividing an image of the area where the beam pattern is located in the cutting image through an image processing algorithm, and performing beam pattern feature extraction by taking the divided image as a processing image. It should be noted that the beam pattern is not equivalent to the beam pattern feature. And the processing amount of subsequent beam pattern feature extraction is reduced by further processing the obtained processing image.
S102, identifying the light beam pattern characteristics according to a preset identification model, and judging whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
The preset recognition model comprises a corresponding relation between each type of light beam pattern characteristic and an equipment screen which are trained in advance. The beam pattern features reflected off different types of device screens are different, and the type of device screen corresponds to the device. Therefore, the corresponding relation between the light beam pattern characteristics of various types and the equipment screen is continuously trained, and the corresponding accuracy of the equipment screen and the light beam pattern characteristics is ensured.
In one embodiment, fig. 4 is a flowchart of a screen replacement detection method according to yet another embodiment, and as shown in fig. 4, the process of recognizing the beam pattern feature according to the preset recognition model in step S102 includes steps S500 and S501:
s500, converting the light beam pattern features into feature vectors;
s501, recognizing the characteristic vector according to a preset recognition model.
And vectorizing the light beam pattern characteristics to obtain characteristic vectors so as to facilitate the identification calculation of a subsequent preset identification model.
In one embodiment, fig. 5 is a flowchart of a preset recognition model training method according to an embodiment, and as shown in fig. 5, the preset recognition model training method according to an embodiment includes steps S600 to S602:
s600, acquiring training original images of various types of training equipment;
the training equipment of each type is the same as or similar to the equipment to be recovered, and comprises a smart phone, a notebook computer or a tablet computer and the like. The screen of the training equipment is irradiated by the light beam, and the screen of the training equipment is shot by the camera equipment, so that an image of the screen of the training equipment, namely a training original image is obtained.
S601, defining a detection label for each training original image; the detection label is used for representing that a screen of the training equipment is original or replaced;
after the training original images are obtained, a detection label is marked on each training original image. Wherein the detection label comprises a replacement label for indicating that the screen has been replaced and an original label for indicating that the screen is original.
And S602, performing data training on the training original image and the detection label to obtain a preset identification model.
The method comprises the steps of obtaining a preset identification model by carrying out data training on a training original image and a detection label, and determining whether a screen of equipment of a specific model is replaced or not according to the preset identification model. Moreover, the preset recognition model can be trained for multiple times in the actual work of the screen replacement detection method, and the accuracy of the preset recognition model is further improved.
In one embodiment, the training raw images and the detection labels are data trained by a machine learning classification algorithm.
The preset recognition model is trained by applying image enhancement processing, image segmentation region processing and machine learning classification algorithm processing to the training original image. In one embodiment, the machine learning classification algorithm includes a linear svm (support vector machine) algorithm or a K-nearest neighbor classification algorithm.
In the screen replacement detection method in any embodiment, after the original image of the device screen irradiated by the light beam is acquired, the light beam pattern features of the original image are extracted, the light beam pattern features are identified according to the preset identification model, and whether the device screen corresponding to the light beam pattern features is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
The embodiment of the invention also provides a screen replacement detection device.
Fig. 6 is a block diagram of a screen replacement detecting apparatus according to an embodiment, and as shown in fig. 6, the screen replacement detecting apparatus according to an embodiment includes a block 100, a block 101, and a block 102:
an image acquisition module 100, configured to acquire an original image of a device screen that receives light beam irradiation;
a feature extraction module 101, configured to extract a light beam pattern feature of an original image;
the characteristic identification module 102 is used for identifying the light beam pattern characteristics according to a preset identification model and judging whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
The screen replacement detection device in any embodiment extracts the light beam pattern features of the original image after acquiring the original image of the device screen irradiated by the received light beam, identifies the light beam pattern features according to the preset identification model, and judges whether the device screen corresponding to the light beam pattern features is replaced by the screen. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
The embodiment of the invention also provides a computer storage medium, wherein computer instructions are stored on the computer storage medium, and when the instructions are executed by a processor, the method for detecting screen replacement of any one of the above embodiments is realized.
Those skilled in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Random Access Memory (RAM), a Read-Only Memory (ROM), a magnetic disk, and an optical disk.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a RAM, a ROM, a magnetic or optical disk, or various other media that can store program code.
Corresponding to the computer storage medium, in one embodiment, a computer device is further provided, where the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement any one of the screen replacement detection methods in the embodiments.
After the computer equipment acquires the original image of the equipment screen irradiated by the received light beam, the light beam pattern characteristics of the original image are extracted, the light beam pattern characteristics are identified according to the preset identification model, and whether the equipment screen corresponding to the light beam pattern characteristics is replaced by the screen is judged. Based on this, whether the screen that comes check out test set through pattern recognition and model training has been changed, when reducing quality control personnel work load among the equipment recovery process, avoid subjective factor to change the influence that detects to the screen, improve accuracy and the efficiency of changing the detection to the screen.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A screen replacement detection method is characterized by comprising the following steps:
acquiring an original image of a device screen irradiated by a received light beam;
extracting the light beam pattern characteristics of the original image;
identifying the light beam pattern characteristics according to a preset identification model, and judging whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
2. The screen replacement detecting method according to claim 1, further comprising, before the process of acquiring the original image of the device screen which receives the light beam irradiation, the steps of:
controlling the irradiation device to irradiate the light beam onto the screen of the equipment.
3. The screen replacement detecting method according to claim 1, wherein the process of extracting the beam pattern feature of the original image includes the steps of:
preprocessing the original image to obtain a processed image;
and extracting the beam pattern features in the processing image.
4. The screen replacement detecting method according to claim 3, wherein the process of preprocessing the original image includes the steps of:
cutting the original image into an image with a set size to obtain a cut image;
and segmenting the image of the area where the light beam pattern is located in the cutting image to obtain the processing image.
5. The screen replacement detecting method according to claim 1, wherein the process of recognizing the beam pattern feature according to a preset recognition model includes the steps of:
converting the beam pattern features into feature vectors;
and identifying the characteristic vector according to a preset identification model.
6. The screen replacement detecting method according to claim 1, wherein the training process of the preset recognition model includes the steps of:
acquiring training original images of various types of training equipment;
defining a detection label for each training original image; the detection label is used for representing that the screen of the training equipment is original or replaced;
and performing data training on the training original image and the detection label to obtain the preset recognition model.
7. The screen replacement detecting method according to claim 6, wherein the process of data training the training original image and the detection label includes the steps of:
and performing data training on the training original image and the detection label through a machine learning classification algorithm.
8. A screen replacement detecting device, comprising:
the image acquisition module is used for acquiring an original image of the equipment screen irradiated by the received light beam;
the characteristic extraction module is used for extracting the light beam pattern characteristics of the original image;
the characteristic identification module is used for identifying the light beam pattern characteristics according to a preset identification model and judging whether the screen of the equipment corresponding to the light beam pattern characteristics is replaced by the screen; the preset identification model comprises the corresponding relation between the pattern characteristics of each light beam and the screen of the equipment.
9. A computer storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the device appearance image brightness adjustment method according to any one of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for adjusting brightness of an appearance image of a device according to any one of claims 1 to 7 when executing the program.
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| CN202011423339.4A CN112393880A (en) | 2020-12-08 | 2020-12-08 | Screen replacement detection method and device |
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| CN202011423339.4A CN112393880A (en) | 2020-12-08 | 2020-12-08 | Screen replacement detection method and device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113298078A (en) * | 2021-06-22 | 2021-08-24 | 广州绿怡信息科技有限公司 | Equipment screen fragmentation detection model training method and equipment screen fragmentation detection method |
| US11922467B2 (en) | 2020-08-17 | 2024-03-05 | ecoATM, Inc. | Evaluating an electronic device using optical character recognition |
-
2020
- 2020-12-08 CN CN202011423339.4A patent/CN112393880A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11922467B2 (en) | 2020-08-17 | 2024-03-05 | ecoATM, Inc. | Evaluating an electronic device using optical character recognition |
| CN113298078A (en) * | 2021-06-22 | 2021-08-24 | 广州绿怡信息科技有限公司 | Equipment screen fragmentation detection model training method and equipment screen fragmentation detection method |
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