Character icon dynamic display detection method

Abstract

The invention discloses a character icon dynamic display detection method. The method comprises the following steps: S1, image acquisition: capturing characters or patterns on a controller display screen by adopting a CCD (Charge Coupled Device) camera or other image acquisition equipment; s2, image processing: preprocessing the collected image; s3, image analysis: identifying key features in the image; s4, data conversion: converting the analyzed image data into a digital signal; s5, adjusting algorithm parameters: adopting a self-adaptive algorithm, utilizing a machine learning model to train and optimize, and automatically adjusting test parameters; and S6, fusion of visual analysis and electrical performance detection: a visual detection system and electronic performance monitoring are integrated on the same platform, and images and electrical parameters are analyzed at the same time. According to the invention, intelligent pattern acquisition, image analysis and post-data conversion are realized, and intelligent parameter adjustment is carried out on the parameters of the produced controller according to a software algorithm in combination with an electric control technology, so that the labor cost is reduced, and the risk of manual misjudgment is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of household appliance character icon detection, in particular to a character icon dynamic display detection method. Background Art

[0002] With the development of science and technology, the Internet of Things technology is widely used in home appliances such as air conditioners, refrigerators, televisions, and rice cookers, and homes are also becoming intelligent. With the continuous upgrading of intelligent home appliances, functions such as human-computer dialogue and contactless gesture recognition are also constantly appearing in smart homes. Therefore, strengthening the research and development of intelligent control will be a major trend in the development of the industry in the future.

[0003] In the production and testing of intelligent controllers, it is often necessary to manually judge the status and parameters of each product display part. However, long-term manual work has a certain risk of misjudgment, which may even seriously affect the user's overall machine function. Summary of the invention

[0004] The purpose of the present invention is to provide a character icon dynamic display detection method to solve the problems in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for detecting dynamic display of character icons, comprising the following steps:

[0006] S1. Image acquisition: Use a CCD camera or other image acquisition device to capture characters or patterns on the controller display screen;

[0007] S2, image processing: preprocessing the collected images;

[0008] S3, Image parsing: Identify key features in the image;

[0009] S4, data conversion: converting the parsed image data into digital signals;

[0010] S5, Algorithm parameter adjustment: Adopt adaptive algorithm, use machine learning model training and optimization, and automatically adjust test parameters;

[0011] S6. Integration of visual analysis and electrical performance testing: Integrate visual inspection systems and electronic performance monitoring on the same platform to analyze images and electrical parameters simultaneously;

[0012] S7. Test result display: The test result is directly displayed on the screen.

[0013] Preferably, the image preprocessing in S2 is used for image denoising, contrast enhancement, and edge detection, which includes smoothing filtering, histogram equalization, and threshold segmentation.

[0014] Preferably, the key features of the recognized image in S3 are obtained by using template matching, shape recognition or deep learning models; the key features of the extracted image include color, texture and shape.

[0015] Preferably, the image analysis also includes exception handling. When analysis fails or the result is unsatisfactory, resampling, parameter adjustment or other analysis strategies are required.

[0016] Preferably, the S5 also includes a communication module, which communicates with the controller and sends the adjusted parameters, and the communication adopts Modbus, CAN bus or RS-485.

[0017] Preferably, a feedback module is also included: a closed-loop feedback system is established from hardware to software and then to hardware.

[0018] Preferably, it also includes a data storage and recording module: saving test results and adjustment history for subsequent analysis and troubleshooting.

[0019] Preferably, it also includes an error handling and alarm module: when an abnormal situation occurs, an alarm is issued in time.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. Realize intelligent pattern acquisition, image analysis and post-data conversion, and make intelligent parameter adjustments to the controller parameters of production based on software algorithms combined with electronic control technology, which greatly reduces labor costs and reduces the risk of manual misjudgment.

[0022] 2. Automatically judge the collected digital signal and the target value. If it is within the standard range, it will automatically pass. If it is not within the standard range, the algorithm will trigger the control signal. At the same time, the parameters of the tested product will be adjusted and then re-judged until it is adjusted to the standard range. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0024] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention.

[0026] See also Figure 1 In an embodiment of the present invention, a character icon dynamic display detection method includes the following steps:

[0027] S1. Image acquisition: Use CCD camera or other image acquisition device to capture characters or patterns on the controller display screen; the selection of CCD camera or other image acquisition device takes into account factors such as resolution, frame rate, spectral response and interface;

[0028] S2, image processing: preprocessing the collected images;

[0029] S3, Image parsing: Identify key features in the image;

[0030] S4, data conversion: converting the parsed image data into digital signals;

[0031] S5. Algorithm parameter adjustment: Adopt adaptive algorithm, use machine learning model training and optimization, and automatically adjust test parameters. Automatically judge by collecting digital signals and target values. If it is within the standard range, it will automatically pass. If it is not within the standard range, the algorithm will trigger the control signal. At the same time, the parameters of the tested product will be adjusted and re-judged until it is adjusted to the standard range.

[0032] S6. Integration of visual analysis and electrical performance testing: Integrate visual inspection systems and electronic performance monitoring on the same platform to analyze images and electrical parameters simultaneously;

[0033] S7. Test result display: The test result is directly displayed on the screen.

[0034] Preferably, the image preprocessing in S2 is used for image denoising, contrast enhancement, and edge detection, which includes smoothing filtering, histogram equalization, and threshold segmentation.

[0035] Preferably, the key features of the identified image in S3 are obtained by using template matching, shape recognition or deep learning models; the key features extracted from the image include color, texture and shape.

[0036] Preferably, the image analysis also includes exception handling. When analysis fails or the result is unsatisfactory, resampling, parameter adjustment or other analysis strategies are required.

[0037] Preferably, the S5 also includes a communication module, which communicates with the controller and sends the adjusted parameters, and the communication adopts Modbus, CAN bus or RS-485.

[0038] Preferably, a feedback module is also included: a closed-loop feedback system from hardware to software and then to hardware is established to ensure the accuracy and stability of the test process.

[0039] Preferably, it also includes a data storage and recording module: saving test results and adjustment history for subsequent analysis and troubleshooting.

[0040] Preferably, it also includes an error handling and alarm module: when an abnormal situation occurs, an alarm is issued in time.

[0041] The working principle of the present invention is: using a CCD camera or other image acquisition device to capture characters or patterns on a controller display screen; the selection of a CCD camera or other image acquisition device takes into account factors such as resolution, frame rate, spectral response and interface; preprocessing the collected image; identifying key features in the image; converting the parsed image data into a digital signal; using an adaptive algorithm, using machine learning model training and optimization, and automatically adjusting the test parameters; automatically judging the collected digital signal and the target value, automatically passing if it is within the standard range, and triggering a control signal using the algorithm if it is not within the standard range, and at the same time, performing a secondary re-judgment on the tested product after adjusting the parameters until it is adjusted to the standard range; integrating a visual inspection system and electronic performance monitoring on the same platform, and analyzing images and electrical parameters at the same time; and the test results are directly displayed on the screen.

[0042] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for detecting dynamic display of character icons, characterized in that: The following steps are involved: S1. Image acquisition: Use a CCD camera or other image acquisition device to capture characters or patterns on the controller display screen; S2, image processing: preprocessing the collected images; S3, Image parsing: Identify key features in the image; S4, data conversion: converting the parsed image data into digital signals; S5, Algorithm parameter adjustment: Adopt adaptive algorithm, use machine learning model training and optimization, and automatically adjust test parameters; S6. Integration of visual analysis and electrical performance testing: Integrate visual inspection systems and electronic performance monitoring on the same platform to analyze images and electrical parameters simultaneously; S7. Test result display: The test result is directly displayed on the screen.

2. A character icon dynamic display detection method according to claim 1, characterized in that: The image preprocessing in S2 is used for image denoising, contrast enhancement, and edge detection, and includes smoothing filtering, histogram equalization, and threshold segmentation.

3. A character icon dynamic display detection method according to claim 1, characterized in that: The key features of the identified image in S3 are obtained by using template matching, shape recognition or deep learning models; the key features of the extracted image include color, texture and shape.

4. A character icon dynamic display detection method according to claim 1 or 3, characterized in that: The image analysis also includes exception handling. When analysis fails or the result is not ideal, resampling, parameter adjustment or other analysis strategies are required.

5. A character icon dynamic display detection method according to claim 1, characterized in that: The S5 also includes a communication module, which communicates with the controller and sends the adjusted parameters, and the communication adopts Modbus, CAN bus or RS-485.

6. A character icon dynamic display detection method according to claim 1, characterized in that: It also includes a feedback module: establishing a closed-loop feedback system from hardware to software and then back to hardware.

7. A character icon dynamic display detection method according to claim 1, characterized in that: Also includes data storage and logging modules: save test results and adjustment history for subsequent analysis and troubleshooting.

8. A character icon dynamic display detection method according to claim 1, characterized in that: It also includes error handling and alarm modules: when abnormal situations occur, alarms are issued in a timely manner.

Images