Signal quality detection method based on video telephone real-time communication

Abstract

The invention relates to the technical field of communication quality detection, and discloses a signal quality detection method based on video telephone real-time communication, which comprises the steps of data acquisition, feature extraction, feature evaluation, quality analysis and real-time feedback, and realizes accurate detection of video telephone real-time communication signal quality. According to the method, communication videos are collected at fixed time intervals, a plurality of key feature data such as a video frame rate, an audio sampling rate, a video code rate, an audio code rate, a packet loss rate and delay time are extracted, and the quality condition of communication signals can be comprehensively and accurately reflected. And performing evaluation processing on each piece of feature data to obtain a corresponding evaluation value. According to the quantitative evaluation mode, the scientificity and objectivity of detection are improved, interference of human factors is reduced, and the evaluation result is more reliable.

Description

Technical Field

[0001] This invention relates to the field of communication quality testing technology, and specifically to a signal quality testing method based on real-time videophone communication. Background Technology

[0002] With the rapid development of communication technology, real-time video telephony has become increasingly important in people's daily lives and work. Video telephony allows people to communicate face-to-face, greatly improving the efficiency and quality of communication. However, during real-time video telephony communication, due to the complexity and variability of the network environment, signal quality is often affected by various factors, such as network congestion, bandwidth limitations, and device performance.

[0003] These issues can lead to problems such as video stuttering, audio distortion, excessive latency, and even communication interruptions, severely impacting the user experience. Therefore, effectively detecting signal quality during real-time videophone communication and promptly identifying and resolving problems is crucial for improving communication quality and user satisfaction.

[0004] Currently, existing signal quality detection methods suffer from shortcomings such as incomplete detection, low accuracy, and insufficient real-time performance, failing to meet users' demands for high-quality videophone communication. To overcome these problems, this invention proposes a signal quality detection method based on real-time videophone communication, aiming to more comprehensively, accurately, and in real-time evaluate signal quality and provide users with superior communication services. Summary of the Invention

[0005] The purpose of this invention is to provide a signal quality detection method based on real-time videophone communication, which solves the technical problems mentioned in the background art.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A signal quality detection method based on real-time videophone communication includes: Example 1 Please see Figure 1 and Figure 2 As shown, the present invention is a signal quality detection method based on real-time videophone communication, comprising: Step 1: Data Collection During real-time video call communication, a segment of video is captured at fixed time intervals. Step 2: Feature Extraction Multiple feature data were extracted from the collected communication video using FFmpeg and network quality testing tools: The multiple feature data refer to video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency, respectively. Step 3: Feature Evaluation The video frame rate, audio sampling rate, video bit rate, audio bit rate, packet loss rate, and latency are evaluated using a pre-trained evaluation model, and corresponding evaluation values ​​are added. Step 4: Quality Analysis Step 1: Using the signal quality assessment formula: Calculate the signal quality evaluation index Z; In the formula, α1, α2, α3, α4, α5, and α6 are the preset weight values ​​for the corresponding evaluation values; Step 2: Obtain the pre-set threshold values ​​Z1, Z2, Z3, and Z4, where Z1 > Z2 > Z3 > Z4; The threshold for the grade indicator is used to determine the signal quality grade at which the signal quality assessment indicator is located. Step 3: Compare the signal quality assessment indicators with the threshold values ​​for the corresponding signal quality levels. Step 5: Real-time feedback The analyzed signal quality level is fed back to the communication platform corresponding to the real-time videophone communication in real time.

[0008] As a further aspect of the present invention: the evaluation model is pre-set with evaluation formulas corresponding to video frame rate, video bit rate, audio sampling rate, audio bit rate, packet loss rate, and latency. The formula for evaluating video frame rate is as follows: The calculation result P SPZ As an evaluation value for video frame rate; In the formula, L1 min It is the minimum video frame rate preset for determining signal quality; The formula for evaluating video bitrate is as follows: The calculation result P SPM As an evaluation value for video bitrate; In the formula, L2 min It is the minimum video bitrate preset for determining signal quality; The formula for evaluating audio sampling rate is as follows: The calculation result P CY As an evaluation value for audio sampling rate; In the formula, L3 min It is the minimum audio sampling rate preset for determining signal quality; The formula for evaluating audio bitrate is as follows: P will be calculated from the results. YPM This is an evaluation value for the audio bitrate; In the formula, L4 min It is the minimum audio bitrate preset for determining signal quality; The formula for evaluating packet loss rate is as follows: , calculate the result P DB As an evaluation value for packet loss rate; The formula for evaluating delay time is as follows: The calculation result P YC As an evaluation value for delay time; In the formula, L5 max It is the maximum delay time preset for determining signal quality.

[0009] As a further aspect of the present invention: wherein the signal quality level includes: The highest quality level indicates excellent signal quality in real-time communication. The second quality level indicates good signal quality in real-time communication; The third quality level indicates moderate signal quality in real-time communication; The fourth quality level indicates poor signal quality in real-time communication; The fifth quality level indicates extremely poor signal quality in real-time communication.

[0010] As a further aspect of the present invention, the comparison method in Step 3 is as follows: If Z≥Z1, then the signal quality evaluation index is at the first quality level; If Z1>Z≥Z2, then the signal quality evaluation index is at the second quality level; If Z2>Z≥Z3, then the signal quality evaluation index is at the third quality level; If Z3>Z≥Z4, then the signal quality evaluation index is at the fourth quality level; If Z < Z4, then the signal quality assessment index is at the fifth quality level.

[0011] As a further aspect of the present invention: the video frame rate refers to the number of video frames transmitted in one second; Audio sampling rate refers to the number of samples taken per unit time when converting an analog signal into a digital signal; Video bitrate refers to the amount of data a video file uses per unit of time, that is, the amount of video data transmitted per second. Audio bitrate refers to the amount of data used by audio data per unit of time, that is, the amount of audio data transmitted per second. Packet loss rate refers to the proportion of data packets lost during network transmission out of the total number of data packets sent; Delay time refers to the time it takes for audio or video data to be transmitted from the sending end to the receiving end.

[0012] The beneficial effects of this invention are: This invention enables precise detection of the real-time communication signal quality of videophones. By acquiring communication video at fixed time intervals and extracting multiple key feature data such as video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency, the quality of the communication signal can be comprehensively and accurately reflected.

[0013] This invention utilizes a pre-trained evaluation model and specific evaluation formulas to evaluate and process various feature data, obtaining corresponding evaluation values. This quantitative evaluation method improves the scientific rigor and objectivity of the detection process, reduces interference from human factors, and makes the evaluation results more reliable.

[0014] This invention calculates various evaluation values ​​using a predetermined signal quality assessment formula to obtain accurate signal quality evaluation indicators, which are then compared with preset level thresholds to determine a clear and definite signal quality level. This helps users and communication platforms quickly and intuitively understand the quality level of communication signals.

[0015] This invention can provide real-time feedback on signal quality levels to the communication platform corresponding to real-time videophone communication, enabling the platform to take timely optimization measures, such as adjusting encoding parameters and optimizing network configuration, to improve communication quality and ensure a good user experience.

[0016] This invention is of great significance for improving the overall quality and stability of real-time video telephony communication. It can effectively reduce problems such as video stuttering, audio distortion, and delay caused by poor signal quality, thereby improving the smoothness and reliability of communication.

[0017] This invention provides strong support for the development and optimization of communication technology. Through precise detection and analysis of signal quality, it can provide valuable data and reference for improving network infrastructure, optimizing communication protocols, and developing related technologies.

[0018] In summary, the signal quality detection method based on real-time videophone communication of the present invention can significantly improve the quality of videophone communication and user experience, and promote the development and progress of communication technology. Attached Figure Description

[0019] The invention will now be further described with reference to the accompanying drawings.

[0020] Figure 1 This is a flowchart illustrating a signal quality detection method based on real-time videophone communication according to the present invention.

[0021] Figure 2 This is a flowchart illustrating the evaluation model in a signal quality detection method based on real-time videophone communication according to the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 Please see Figure 1 and Figure 2 As shown, the present invention is a signal quality detection method based on real-time videophone communication, comprising: Step 1: Data Collection During real-time video call communication, a segment of video is captured at fixed time intervals. Step 2: Feature Extraction Multiple feature data were extracted from the collected communication video using FFmpeg and network quality testing tools: The multiple feature data refer to video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency, respectively. in, Video frame rate refers to the number of video frames transmitted per second; Among them, the video frame rate reflects the smoothness of the video picture; the higher the frame rate, the smoother the picture; conversely, the lower the frame rate, the stronger the sense of judder in the picture. Audio sampling rate refers to the number of samples taken per unit time when converting an analog signal into a digital signal, and is expressed in Hertz (Hz). Among them, the higher the sampling rate, the higher the audio fidelity; Video bitrate refers to the amount of data a video file uses per unit of time, that is, the amount of video data transmitted per second. Audio bitrate refers to the amount of data used by audio data per unit of time, that is, the amount of audio data transmitted per second. Among them, the bitrate affects the accuracy and compression ratio of the data; the higher the bitrate, the better the quality. Packet loss rate refers to the proportion of data packets lost during network transmission out of the total number of data packets sent. A high packet loss rate can seriously affect the quality of audio and video calls. Latency refers to the time it takes for audio or video data to be transmitted from the sending end to the receiving end; In this embodiment, the extraction of video frame rate, audio sampling rate, video bitrate, and audio bitrate is achieved by parsing the communication video using FFmpeg and providing information about the video frame rate, audio sampling rate, video bitrate, and audio bitrate. FFmpeg is an open-source computer program that can be used to record and convert digital audio and video and convert them into streams, and it is existing technology. Packet loss rate and latency can be measured and extracted using network quality testing tools, such as the "ping" command, which can be used to test packet loss and provide a rough estimate of round-trip latency. Step 3: Feature Evaluation The video frame rate, audio sampling rate, video bit rate, audio bit rate, packet loss rate, and latency are evaluated using a pre-trained evaluation model, and corresponding evaluation values ​​are added. The evaluation model is pre-set with minimum video frame rate, minimum video bit rate, minimum audio sampling rate, minimum audio bit rate, and maximum latency, which are used to determine the signal quality of real-time communication. The evaluation model is used to assess video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency in the following ways: When evaluating video frame rate: First, compare the video frame rate with the minimum video frame rate: When the video frame rate is greater than or equal to the minimum video frame rate, the evaluation value of the video frame rate is 1; When the video frame rate is greater than 0 and less than the minimum video frame rate, the evaluated value of the video frame rate is obtained by dividing the video frame rate by the minimum video frame rate. When evaluating video bitrate, the evaluation model should: First, compare the video bitrate with the minimum video bitrate: When the video bitrate is greater than or equal to the minimum video bitrate, the evaluation value of the video bitrate is 1; When the video bitrate is greater than 0 and less than the minimum video bitrate, the evaluated value of the video bitrate is obtained by dividing the video bitrate by the minimum video bitrate. When evaluating the audio sampling rate, the evaluation model should be used as follows: First, compare the audio sampling rate with the minimum audio sampling rate: When the audio sampling rate is greater than or equal to the minimum audio sampling rate, the evaluation value of the audio sampling rate is 1; When the audio sampling rate is greater than 0 and less than the minimum audio sampling rate, the evaluation value of the audio sampling rate is obtained by dividing the audio sampling rate by the minimum audio sampling rate. When evaluating audio bitrate, the evaluation model should: First, compare the audio bitrate with the minimum audio bitrate: When the audio bitrate is greater than or equal to the minimum audio bitrate, the evaluation value of the audio bitrate is 1; When the audio bitrate is greater than 0 and less than the minimum audio bitrate, the evaluated value of the audio bitrate is obtained by dividing the audio bitrate by the minimum audio bitrate. When evaluating the delay time, the evaluation model should: The value obtained by subtracting the packet loss rate from 1 is used as the evaluation value of the packet loss rate; When evaluating the delay time, the evaluation model should: First, compare the delay time with the maximum delay time: When the delay time is less than or equal to the maximum delay time, the audio bitrate is evaluated as 1. When the delay time is greater than the maximum delay time, the audio bitrate is evaluated as the maximum delay time divided by the delay time. Step 4: Quality Analysis Step 1: Using the signal quality assessment formula: Calculate the signal quality evaluation index Z; In the formula, α1, α2, α3, α4, α5, and α6 are the preset weight values ​​for the corresponding evaluation values; Step 2: Obtain the pre-set threshold values ​​Z1, Z2, Z3, and Z4, where Z1 > Z2 > Z3 > Z4; The threshold for the grade indicator is used to determine the signal quality grade at which the signal quality assessment indicator is located. Step 3: Compare the signal quality assessment indicators with the threshold values ​​for the corresponding signal quality levels. If Z≥Z1, then the signal quality evaluation index is at the first quality level, indicating that the signal quality of real-time communication is excellent; If Z1>Z≥Z2, then the signal quality evaluation index is at the second quality level, indicating that the signal quality of real-time communication is good; If Z2>Z≥Z3, then the signal quality evaluation index is at the third quality level, indicating that the signal quality of real-time communication is medium. If Z3>Z≥Z4, then the signal quality evaluation index is at the fourth quality level, indicating that the signal quality of real-time communication is poor. If Z < Z4, then the signal quality evaluation index is at the fifth quality level, indicating that the signal quality of real-time communication is extremely poor. Step 5: Real-time feedback The analyzed signal quality level is fed back to the communication platform corresponding to the real-time videophone communication in real time. The communication platform can take corresponding adjustment measures according to the signal quality level, such as adjusting encoding parameters, increasing bandwidth, and optimizing routing, in order to improve communication quality.

[0024] This embodiment can comprehensively collect and analyze multiple key feature data in real-time videophone communication, including video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency, thereby providing a multi-dimensional evaluation of communication signal quality. Through a pre-trained evaluation model and clear evaluation criteria, an evaluation value is added to each feature data, making the evaluation results more accurate and objective. Using scientific signal quality evaluation formulas and level indicator thresholds, signal quality levels are clearly defined, providing a clear basis for subsequent adjustment measures. Real-time feedback of the signal quality level to the communication platform helps the platform take timely and targeted adjustment measures to improve the quality of real-time videophone communication.

[0025] Example 2 As a second embodiment of the present invention, in specific implementation, the technical solution of this embodiment differs from that of embodiment one only in that: In this embodiment, based on the previous embodiment, one or more feature data are arbitrarily removed in the feature extraction step, that is, the removed feature data is removed and only the retained feature data is extracted. Then, the retained feature data is evaluated to obtain the evaluation value corresponding to the retained feature data. Then, the signal quality evaluation index is calculated using the signal quality evaluation formula, and then the signal quality level of the signal quality evaluation index is determined by the level index threshold. In the signal quality assessment formula, the preset weight values ​​corresponding to the assessment values ​​are not included in the calculation when calculating the signal quality assessment index. In this embodiment, at least three feature data points are retained for signal quality detection.

[0026] This embodiment adds flexibility to the first embodiment, allowing one or more feature data to be removed for detection according to actual needs, adapting to different application scenarios and resource constraints; even if some feature data is removed, effective signal quality detection can still be performed using at least 3 retained feature data, reducing the complexity of data processing while ensuring a certain level of detection accuracy.

[0027] Example 3 As a third embodiment of the present invention, in specific implementation, compared with embodiments one and two, the technical solution of this embodiment is to combine the solutions of embodiments one and two.

[0028] This embodiment combines the comprehensiveness of Embodiment 1 with the flexibility of Embodiment 2, enabling the selection of the most suitable detection scheme based on specific circumstances. It allows for the flexible application of different combinations in different scenarios, maximizing the satisfaction of various complex signal quality detection needs and improving the overall detection effect and adaptability.

[0029] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0030] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A signal quality detection method based on real-time videophone communication, characterized in that, include: The first step is to capture a segment of video communication at fixed time intervals during real-time video call communication. The second step involves extracting multiple feature data from the collected communication video using FFmpeg and network quality testing tools: The third step is to evaluate and process multiple feature data using a pre-trained evaluation model, and obtain the corresponding evaluation value for each feature data. The fourth step is to obtain the corresponding evaluation values ​​of each feature data, calculate them using the predetermined signal quality evaluation formula, and obtain the signal quality evaluation index of the communication video segment. Then, compare the signal quality evaluation index with the preset level index threshold and determine its signal quality level. The level index threshold is used to determine the signal quality level of the signal quality evaluation index. Step 5: Real-time feedback The analyzed signal quality level is fed back to the communication platform corresponding to the real-time videophone communication in real time.

2. The signal quality detection method based on real-time videophone communication according to claim 1, characterized in that, The multiple feature data refer to video frame rate, audio sampling rate, video bitrate, audio bitrate, packet loss rate, and latency, respectively.

3. The signal quality detection method based on real-time videophone communication according to claim 2, characterized in that, The evaluation model has pre-set evaluation formulas corresponding to video frame rate, video bit rate, audio sampling rate, audio bit rate, packet loss rate, and latency; and pre-set minimum video frame rate, minimum video bit rate, minimum audio sampling rate, minimum audio bit rate, and maximum latency based on each evaluation formula.

4. The signal quality detection method based on real-time videophone communication according to claim 3, characterized in that, The formula for evaluating video frame rate is as follows: The calculation result P SPZ As an evaluation value for video frame rate; In the formula, L1 min The preset minimum video frame rate; The formula for evaluating video bitrate is as follows: The calculation result P SPM As an evaluation value for video bitrate; In the formula, L2 min The preset minimum video bitrate; The formula for evaluating audio sampling rate is as follows: The calculation result P CY As an evaluation value for audio sampling rate; In the formula, L3 min The preset minimum audio sampling rate; The formula for evaluating audio bitrate is as follows: P will be calculated from the results. YPM This is an evaluation value for the audio bitrate; In the formula, L4 min The minimum audio bitrate that is preset; The formula for evaluating packet loss rate is as follows: , calculate the result P DB As an evaluation value for packet loss rate; The formula for evaluating the delay time is as follows: The calculation result P YC As an evaluation value for delay time; In the formula, L5 max The maximum delay time is preset.

5. The signal quality detection method based on real-time videophone communication according to claim 4, characterized in that, The signal quality assessment formula is: Calculate the signal quality evaluation index Z; In the formula, P SPZ P SPM P CY P YPM P DB P YC α1, α2, α3, α4, α5, and α6 are the evaluation values ​​of each feature data, and the preset weight values ​​are the evaluation values ​​of each feature data.

6. The signal quality detection method based on real-time videophone communication according to claim 5, characterized in that, The method for determining the signal quality level in step four is as follows: First, obtain the pre-set threshold values ​​Z1, Z2, Z3, and Z4 for the grade indicators, where Z1 > Z2 > Z3 > Z4. Next, the signal quality assessment index Z is compared with the level index thresholds Z1, Z2, Z3, and Z4, respectively, and the corresponding signal quality level is obtained based on the comparison results.

7. The signal quality detection method based on real-time videophone communication according to claim 6, characterized in that, in, Signal quality levels include: The highest quality level indicates excellent signal quality in real-time communication. The second quality level indicates good signal quality in real-time communication; The third quality level indicates moderate signal quality in real-time communication; The fourth quality level indicates poor signal quality in real-time communication; The fifth quality level indicates extremely poor signal quality in real-time communication.

8. A signal quality detection method based on real-time videophone communication according to claim 7, characterized in that, The comparison method in Step 3 is as follows: If Z≥Z1, then the signal quality evaluation index is at the first quality level; If Z1>Z≥Z2, then the signal quality evaluation index is at the second quality level; If Z2>Z≥Z3, then the signal quality evaluation index is at the third quality level; If Z3>Z≥Z4, then the signal quality evaluation index is at the fourth quality level; If Z < Z4, then the signal quality assessment index is at the fifth quality level.

9. The signal quality detection method based on real-time videophone communication according to claim 1, characterized in that, Video frame rate refers to the number of video frames transmitted per second; Audio sampling rate refers to the number of samples taken per unit time when converting an analog signal into a digital signal; Video bitrate refers to the amount of data a video file uses per unit of time, that is, the amount of video data transmitted per second. Audio bitrate refers to the amount of data used by audio data per unit of time, that is, the amount of audio data transmitted per second. Packet loss rate refers to the proportion of data packets lost during network transmission out of the total number of data packets sent; Delay time refers to the time it takes for audio or video data to be transmitted from the sending end to the receiving end.

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