CN117351794A - Online course management system based on cloud platform - Google Patents
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Abstract
The invention relates to the field of data processing, in particular to an online course management system based on a cloud platform, which comprises the following components: the judging module detects the user behavior data, judges whether to delete courses, and sends course detection instructions when the courses are not deleted; the cloud storage module stores preset contrast of an interface picture and preset signal-to-noise ratio of audio; the contrast comparison module receives the course detection instruction to detect the contrast of the interface picture, and compares the contrast with a preset contrast to obtain a comparison result; the instruction sending module sends a picture repairing instruction when the contrast is smaller than a preset contrast, and sends an audio detection instruction when the contrast is larger than or equal to the preset contrast; the audio comparison module receives an audio detection instruction, detects audio in real time and compares the audio with a preset signal to noise ratio to obtain a comparison result; the course repair module repairs the picture contrast when receiving a picture repair instruction; and repairing the audio when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio. The method solves the problem of accuracy of course repair process.
Description
Technical Field
The invention relates to the field of data processing, in particular to an online course management system based on a cloud platform.
Background
Early cloud database technology mainly transfers traditional database software to a cloud platform to provide remote storage and access services. The service mode is mainly oriented to the inside of an enterprise, and data in the enterprise can be stored in the cloud through cloud database service, so that distributed management and sharing of the data are realized. With the advent of the big data age, cloud database technology has gradually evolved towards data warehouse and data analysis. In this stage, the cloud database not only can realize the storage and sharing of the operation data of the enterprise business system, but also can carry out deep analysis and mining on the data, thereby providing data support for the operation decision of the enterprise. The development of cloud database technology enters the third stage, which is also the stage of the artificial intelligence era. With the development of natural language processing, machine learning, deep learning and other technologies, the cloud database can already realize intelligent data analysis and service application.
The patent document of Chinese patent publication No. CN116153152A discloses a cloud teaching platform for online course learning, which comprises: the online course resource library establishing module is used for establishing an online course resource library; the online course selection interface display module is used for generating an online course selection interface based on the online course resource library and displaying the online course selection interface; the online course selection module is used for acquiring online courses selected by the login user from the online course selection interface; and the online course learning carrying module is used for carrying the login user to enter the learning of the online course.
In the prior art, the cloud platform cannot accurately judge whether the course needs to be deleted and the course needs to be repaired or not for course management, and some courses which are not needed or have problems can exist in the cloud platform all the time, so that not only the storage space is occupied, but also the trouble to a user can be caused.
Disclosure of Invention
Therefore, the online course management system based on the cloud platform can judge whether a course is deleted or not through analysis of user behavior data, and sequentially detect and repair the picture contrast and the audio definition of the undeleted course, so that the problem of accurate course updating process is solved.
In order to achieve the above object, the present invention provides an online course management system based on a cloud platform, including:
the judging module is used for detecting user behavior data, judging whether the course is deleted or not according to the user behavior data, and sending a course detection instruction when the course is not deleted, wherein the user behavior data comprises the watching frequency of a user watching the course and the watching duration of the user watching the course;
the cloud storage module is used for storing preset contrast of the interface picture of the course and preset signal-to-noise ratio of the audio corresponding to the course;
The contrast comparison module is connected with the judging module and the cloud storage module and is used for receiving the course detection instruction, carrying out contrast detection on interface pictures of the courses to obtain actual contrast, and comparing the actual contrast with the preset contrast to obtain a comparison result;
the instruction sending module is connected with the contrast comparison module and used for sending a picture repair instruction when the contrast is smaller than the preset contrast;
or alternatively, the first and second heat exchangers may be,
when the contrast is larger than or equal to the preset contrast, sending an audio detection instruction;
the audio comparison module is connected with the cloud storage module and the instruction sending module and is used for receiving the audio detection instruction, detecting the audio of the course in real time, acquiring the real-time signal-to-noise ratio of the audio of the course, and comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to acquire a comparison result;
the course repairing module is connected with the instruction sending module and used for repairing the contrast of the pictures of the courses according to the picture repairing instruction when receiving the picture repairing instruction;
or alternatively, the first and second heat exchangers may be,
and repairing the audio of the course when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio.
Further, the judging module comprises a frequency detecting unit, a duration detecting unit and a judging unit, wherein,
the frequency detection unit is used for counting the times of clicking interface pictures entering courses by a user to obtain the real-time watching frequency of the user watching the courses;
the time length detection unit is used for detecting and calculating the starting time, the ending time and the pause period of the course watched by the user to obtain the real-time watching time length of the course watched by the user;
the judging unit is connected with the frequency detecting unit and the duration detecting unit and is used for judging whether the courses are deleted or not according to comparison of the real-time watching frequency and the preset watching frequency and/or the comparison of the real-time watching duration and the preset watching duration.
Further, the frequency detection unit comprises an interface detection subunit, an interface discrimination subunit and a statistics subunit, wherein,
the interface detection subunit is used for detecting a user interface in real time to acquire a plurality of real-time images;
the interface judging subunit is connected with the interface detecting subunit and is used for extracting edge contour features in a plurality of real-time images through an edge detecting algorithm, carrying out similarity calculation on the edge contour features and the edge contour features of the interface pictures of the courses, and if the similarity calculation result is greater than or equal to a preset similarity, using an interface by the user as the interface picture of the courses;
The statistics subunit is connected with the interface discrimination subunit and is used for counting the times of using an interface by the user as an interface picture of the course, namely the real-time watching frequency.
Further, the duration detection unit includes a start time detection subunit, a stop time detection subunit, a pause period detection subunit, and a calculation subunit, wherein,
the starting time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface enters the interface picture of the course as the starting time;
the termination time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface exits from the interface picture of the course as the termination time;
the pause period detection subunit is used for counting the pause period of the user in the same picture after entering the interface picture of the course;
the calculating subunit is configured to obtain the final difference value as the viewing duration by continuously making a difference between the difference value between the ending time and the starting time and the pause period.
Further, the judging unit comprises a frequency comparing subunit and a duration comparing subunit, wherein,
The frequency comparison subunit is configured to compare the real-time viewing frequency with a preset viewing frequency, delete the course if the real-time viewing frequency is smaller than the preset viewing frequency, and send a duration comparison instruction if the real-time viewing frequency is greater than or equal to the preset viewing frequency;
the time length comparison subunit is connected with the frequency comparison subunit and is used for receiving the time length comparison instruction, comparing the real-time watching time length with the preset watching time length, deleting the course if the real-time watching time length is smaller than the preset watching time length, and sending a course detection instruction if the watching time length is larger than or equal to the preset watching time length.
Further, the contrast comparison module comprises a gray level detection unit, a contrast calculation unit and a comparison unit, wherein,
the gray level detection unit is used for detecting gray level values of images of interface pictures of the courses through image processing software, obtaining a plurality of gray level values, and extracting the maximum gray level value and the minimum gray level value in the gray level values;
the contrast calculating unit is connected with the gray level detecting unit and is used for calculating the contrast of the image according to the formula C= (H) max -H min )/H min Calculating the actual contrast, wherein C is the actual contrast, H max For the maximum gray value, H min Is the minimum gray value;
the comparison unit is connected with the contrast calculating unit and used for comparing the actual contrast with the preset contrast to obtain a comparison result.
Further, the audio comparison module comprises an audio acquisition unit, an audio separation unit, a noise calculation unit, a non-noise calculation unit, a signal to noise ratio calculation unit and a comparison unit, wherein,
the audio acquisition unit is used for extracting the audio in the course through audio processing software and acquiring an audio signal of the course;
the audio separation unit is connected with the audio acquisition unit and used for separating a noise signal and a non-noise signal in the audio signal through a high-pass filter to acquire the noise signal and the non-noise signal;
the noise calculation unit is connected with the audio separation unit and used for extracting noise signals in a preset period, and the power spectrum density of the noise signals in the preset period is obtained by carrying out power spectrum density calculation on the noise signals;
the non-noise calculation unit is connected with the audio separation unit and used for extracting a non-noise signal in the same preset period, and the power spectrum density of the non-noise signal in the preset period is obtained by carrying out power spectrum density calculation on the non-noise signal;
The signal-to-noise ratio calculating unit is connected with the noise calculating unit and the non-noise calculating unit and is used for calculating the noise by the formula of X=P Non-noise /P Noise (S) Calculating the real-time signal-to-noise ratio, wherein X is the signal-to-noise ratio and P Non-noise Power spectral density, P, of non-noise signals Noise (S) Power spectral density for noise signals;
the comparison unit is connected with the signal-to-noise ratio calculation unit and used for comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to obtain a comparison result.
Further, the course repair module comprises a picture repair unit and an audio repair unit, wherein,
the picture repairing unit is used for receiving the picture repairing instruction, and performing contrast repairing on the interface picture of the course through a contrast enhancement algorithm to obtain a repairing image;
the audio repairing unit is used for receiving the audio repairing instruction and repairing noise of the audio of the lesson through a noise reduction algorithm.
Further, the picture repairing unit comprises a picture extracting subunit and a picture repairing subunit, wherein,
the picture extraction subunit is configured to extract a picture corresponding to the actual contrast smaller than the preset contrast in the interface picture of the course as a picture to be repaired;
The picture repairing subunit is connected with the picture extracting subunit and used for obtaining an image gray level histogram of the picture to be repaired through image processing software, calculating a cumulative distribution function of each gray level according to the image gray level histogram result, and mapping the gray level value of each pixel point in the image of the picture to be repaired to a new gray level to obtain a repaired image.
Further, the obtaining, by the picture repairing subunit, the image gray level histogram of the picture to be repaired by using image processing software includes:
converting the picture to be repaired into a gray level image, and obtaining the gray level image to be repaired;
acquiring a plurality of pixel values in the gray level image to be repaired through image processing software;
acquiring a plurality of gray value levels corresponding to a plurality of pixel values by searching a gray value level database;
establishing a rectangular coordinate system with an X axis as a gray level and a Y axis as the number of pixels corresponding to each gray level, and drawing the gray levels corresponding to a plurality of pixel values and the number of pixels corresponding to each gray level in the rectangular coordinate system to obtain an image gray histogram of the picture to be repaired.
Compared with the prior art, the invention has the advantages that the judgment module is arranged to detect the user behavior data, whether the lessons are deleted or not is judged according to the watching frequency and watching time of the user watching the lessons, so that the system improves the accuracy of the lesson management, when the lessons are not deleted, the lesson detection instruction is sent, thereby realizing the intelligent management of the online lessons, improving the efficiency of the lesson management, by arranging the preset contrast of the interface picture of the lessons and the preset signal-to-noise ratio of the audio corresponding to the lessons stored by the cloud storage module, facilitating the subsequent detection and repair of the lesson picture and the audio, providing a data basis for the lesson detection, improving the playing quality of the lessons, comparing the actual contrast with the preset contrast by the contrast comparison module, obtaining the comparison result, realizing the automatic detection of the lesson picture, improving the detection efficiency, and the automatic efficiency of the repair management, or the automatic repair instruction sending the instruction of the lesson when the contrast is smaller than the preset contrast, or the contrast is larger than the preset contrast of the preset audio, thereby realizing the automatic comparison of the automatic detection of the lesson picture, the automatic comparison of the voice picture, the automatic comparison of the lesson, the automatic comparison of the comparison, the picture, the improvement of the detection efficiency, the improvement of the automatic comparison, the picture, and the improvement of the comparison, the improvement of the contrast, the improvement of the accuracy, and the improvement of the comparison, the course repair module is arranged to repair the contrast of the picture of the course according to the picture repair instruction when receiving the picture repair instruction, or repair the audio of the course when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio, so that the automatic repair of the picture and the audio of the course is realized, and the repair efficiency and the accuracy of the system to the course are improved.
In particular, the frequency detection unit is set to count the times of clicking the interface picture entering the course by the user, so as to obtain the real-time watching frequency of the user watching the course, thereby accurately knowing the interest and attention degree of the user for the course, providing a judging basis for whether the course is deleted or not, and the time detection unit is set to detect and calculate the starting time, the ending time and the pause time of the user watching the course, so as to obtain the real-time watching time length of the user watching the course, accurately knowing the time and energy spent by the user on the course, providing a judging basis for whether the course is deleted or not, enabling the judging result to be accurate, and judging whether the course is deleted or not according to the comparison of the real-time watching frequency and the preset watching frequency and/or the real-time watching time length and the preset watching time length by the judging unit, thereby intelligently managing the course according to the interest and attention degree of the user and the spent time and energy, more comprehensively knowing the interest and attention degree of the user for the course, avoiding the one-piece of single index and errors, and improving the accuracy and reliability of the judgment.
In particular, the interface detection subunit is set to detect the user interface in real time to obtain a plurality of real-time images, so that information of the user interface can be obtained in real time, basis is provided for subsequent interface discrimination and statistics, the interface discrimination subunit is set to extract edge profile features in a plurality of real-time images by adopting an edge detection algorithm, similarity calculation is carried out on the edge profile features of the interface images of the courses and the edge profile features of the interface images of the courses, if the similarity calculation result is greater than the preset similarity, the user interface is used as the interface image of the courses, and therefore whether the user interface is used as the interface image of the courses can be accurately judged, misjudgment and missed judgment are avoided, the statistics subunit is set to count the times of using the interface as the interface image of the courses, namely, the real-time watching frequency is used, so that the times of watching the courses of the user can be accurately counted, basis is provided for subsequent course management and recommendation, the detection efficiency and the management efficiency of the system are improved, and the management cost is reduced.
In particular, by setting the actual detection of the user interface by the start time detection subunit and the end time detection subunit, the time when the user enters and exits the interface picture of the course by using the interface can be accurately obtained, so that the time when the user watches the course can be accurately calculated, by setting the pause period detection subunit to count the pause period of the user in the same picture after entering the interface picture of the course as the pause period, the pause time of the user in the course of watching the course can be accurately obtained, so that the time when the user watches the course can be more accurately calculated, by setting the calculation subunit to adopt the mode that the difference between the end time and the start time is inferior to the pause period continuously, the time when the user watches the course can be accurately calculated, the one-sided performance and the error of a single index are avoided, and the accuracy and the reliability of calculation are improved.
In particular, the gray level detection unit is arranged to detect the gray level value of the image of the interface picture of the course by adopting image processing software, so that the gray level information of the image can be accurately obtained, a basis is provided for the subsequent contrast calculation, the contrast calculation unit is arranged to calculate the actual contrast by adopting the formula C= (Hmax-Hmin)/Hmin, the actual contrast of the interface picture of the course can be accurately calculated, a basis is provided for the subsequent comparison, the comparison unit is arranged to compare the actual contrast with the preset contrast, the comparison result can be accurately obtained, whether the contrast of the interface picture of the course meets the requirement is judged, a basis is provided for the subsequent course repair, and the accuracy and pertinence of the repair are improved.
In particular, the audio frequency acquisition unit is arranged to extract the audio frequency in the course by adopting the audio frequency processing software, so that the audio frequency signal of the course can be accurately acquired, the basis is provided for the subsequent audio frequency separation and signal to noise ratio calculation, the high-pass filter is arranged to separate the noise signal and the non-noise signal in the audio frequency signal, the noise signal and the non-noise signal can be accurately acquired, the basis is provided for the subsequent power spectrum density calculation of the noise signal and the non-noise signal, the noise signal in the preset period is extracted by the noise calculation unit, the power spectrum density of the noise signal in the preset period can be accurately acquired by the power spectrum density calculation of the noise signal, the basis is provided for the subsequent signal to noise ratio calculation, the non-noise calculating unit is arranged to extract the non-noise signals in the same preset period, the power spectrum density of the non-noise signals in the preset period can be accurately obtained by carrying out power spectrum density calculation on the non-noise signals, a basis is provided for subsequent signal-to-noise ratio calculation, the real-time signal-to-noise ratio of the audio of the course can be accurately calculated by arranging the signal-to-noise ratio calculating unit to calculate the real-time signal-to-noise ratio by adopting the formula X=P non-noise/P noise, a basis is provided for subsequent comparison, the comparison unit is arranged to compare the real-time signal-to-noise ratio with the preset signal-to-noise ratio, a comparison result can be accurately obtained, whether the signal-to-noise ratio of the audio of the course meets the requirement is judged, a basis is provided for subsequent course repair, and the accuracy and pertinence of repair are improved.
Drawings
FIG. 1 is a first block diagram of an online course management system based on a cloud platform according to an embodiment of the present invention;
FIG. 2 is a second block diagram of an online course management system based on a cloud platform according to an embodiment of the present invention;
FIG. 3 is a third block diagram of an online course management system based on a cloud platform according to an embodiment of the present invention;
fig. 4 is a fourth structural block diagram of the online course management system based on the cloud platform according to the embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, the present invention provides an online course management system based on a cloud platform, which includes:
the judging module 10 is configured to detect user behavior data, judge whether to delete a course according to the user behavior data, and send a course detection instruction when the course is not deleted, where the user behavior data includes a viewing frequency of a user viewing the course and a viewing duration of the user viewing the course;
the cloud storage module 20 is configured to store a preset contrast of an interface picture of the lesson and a preset signal-to-noise ratio of audio corresponding to the lesson;
The contrast comparison module 30 is connected with the judging module 10 and the cloud storage module 20, and is used for receiving the course detection instruction, carrying out contrast detection on the interface picture of the course, obtaining an actual contrast, and comparing the actual contrast with the preset contrast to obtain a comparison result;
the instruction sending module 40 is connected with the contrast comparing module 30, and is configured to send a picture repairing instruction when the contrast is smaller than the preset contrast;
or alternatively, the first and second heat exchangers may be,
when the contrast is larger than or equal to the preset contrast, sending an audio detection instruction;
the audio comparison module 50 is connected with the cloud storage module 20 and the instruction sending module 40, and is used for receiving the audio detection instruction, detecting the audio of the course in real time, obtaining the real-time signal-to-noise ratio of the audio of the course, and comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to obtain a comparison result;
the course repair module 60 is connected with the instruction sending module 40, and is used for repairing the contrast of the pictures of the course according to the picture repair instruction when receiving the picture repair instruction;
Or alternatively, the first and second heat exchangers may be,
and repairing the audio of the course when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio.
Specifically, the preset contrast is 55dB, and the preset signal-to-noise ratio is 48dB.
Specifically, the embodiment of the invention detects the user behavior data by setting the judging module 10, judges whether to delete the course according to the watching frequency and watching time of the user watching the course, so that the system improves the accuracy of course management, when the course is not deleted, the course detection instruction is sent, thereby realizing intelligent management of the online course, improving the efficiency of course management, and the cloud storage module 20 is set to store the preset contrast of the interface picture of the course and the preset signal-to-noise ratio of the audio corresponding to the course, thereby facilitating the subsequent detection and repair of the course picture and the audio, providing a data basis for the course, improving the playing quality of the course, carrying out contrast detection on the interface picture of the course by setting the contrast comparison module 30, obtaining the actual contrast, and comparing the actual contrast with the preset contrast to obtain a comparison result, thereby realizing automatic detection of the course images, improving the detection efficiency, improving the accuracy of subsequent course repair management, automatically detecting the course audio by setting the instruction transmitting module 40 to transmit an image repair instruction when the contrast is smaller than the preset contrast or to transmit an audio detection instruction when the contrast is greater than or equal to the preset contrast, thereby realizing automatic processing of the course images and the audio, improving the processing efficiency of system course management, detecting the audio of the course in real time by setting the audio comparison module 50, obtaining the real-time signal-to-noise ratio of the audio of the course, comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio, obtaining the comparison result, thereby realizing automatic detection of the course audio, improving the accuracy and efficiency of the system for audio noise detection, by setting the course repair module 60 to repair the contrast of the picture of the course according to the picture repair instruction when receiving the picture repair instruction or repair the audio of the course when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio, the automatic repair of the picture and the audio of the course is realized, and the repair efficiency and the accuracy of the system to the course are improved.
Referring to fig. 2, the judging module 10 includes a frequency detecting unit 11, a duration detecting unit 12, and a judging unit 13, wherein,
the frequency detection unit 11 is configured to obtain a real-time viewing frequency of a user for viewing a course by counting the number of times the user clicks an interface screen for entering the course;
the duration detection unit 12 is configured to obtain a real-time viewing duration of the user viewing the course by detecting and calculating a start time, a stop time, and a pause period of the user viewing the course;
the judging unit 13 is connected to the frequency detecting unit 11 and the duration detecting unit 12, and is configured to judge whether the course is deleted according to the comparison between the real-time viewing frequency and a preset viewing frequency and/or the comparison between the real-time viewing duration and a preset viewing duration.
Specifically, the preset viewing frequency is 3, and the preset viewing duration is 5min.
Specifically, the frequency detection unit 11 is set to count the number of times that the user clicks the interface picture of entering the course, so as to obtain the real-time watching frequency of the user watching the course, thereby accurately knowing the interest and attention degree of the user for the course, providing a judging basis for whether the course is deleted, the duration detection unit 12 is set to detect and calculate the starting time, the ending time and the pause time of the user watching the course, and obtain the real-time watching time length of the user watching the course, thereby accurately knowing the time and effort spent by the user on the course, providing a judging basis for whether the course is deleted, so that the judging result is accurate, and the judging unit 13 is set to judge whether the course is deleted according to the comparison of the real-time watching frequency and the preset watching frequency and/or the real-time watching time length and the preset watching time length, thereby intelligently managing the course according to the interest and attention degree of the user and the spent time and effort, more comprehensively knowing the interest and attention degree of the user for the course, avoiding the one-sided nature and error of a single index, and improving the accuracy and reliability of judgment.
Specifically, the frequency detection unit 11 includes an interface detection subunit, an interface discrimination subunit, and a statistics subunit, wherein,
the interface detection subunit is used for detecting a user interface in real time to acquire a plurality of real-time images;
the interface judging subunit is connected with the interface detecting subunit and is used for extracting edge contour features in a plurality of real-time images through an edge detecting algorithm, carrying out similarity calculation on the edge contour features and the edge contour features of the interface pictures of the courses, and if the similarity calculation result is greater than or equal to a preset similarity, using an interface by the user as the interface picture of the courses;
the statistics subunit is connected with the interface discrimination subunit and is used for counting the times of using an interface by the user as an interface picture of the course, namely the real-time watching frequency.
Specifically, the similarity calculation may select cosine similarity.
Specifically, the embodiment of the invention carries out real-time detection on the user interface by setting the interface detection subunit to acquire a plurality of real-time images, so that information of the user interface can be acquired in real time, basis is provided for subsequent interface discrimination and statistics, the interface discrimination subunit is set to extract edge profile features in a plurality of real-time images by adopting an edge detection algorithm, similarity calculation is carried out on the edge profile features of the interface images of the courses and the edge profile features of the interface images of the courses, if the similarity calculation result is larger than the preset similarity, the user interface is the interface image of the courses, thereby accurately judging whether the user interface is the interface image of the courses, avoiding misjudgment and missed judgment, and counting the number of times of the user interface is the interface image of the courses, namely, real-time watching frequency by setting the statistics subunit, thereby accurately counting the number of times of watching the courses by the user, providing basis for subsequent course management and recommendation, improving the detection efficiency and management efficiency of the system, and simultaneously reducing management cost.
The frequency detection unit 11 adopts an edge detection algorithm to extract edge contour features in the real-time image, and performs similarity calculation with the edge contour features of the interface picture of the course, so that whether the user interface is the interface picture of the course can be accurately judged, and the judgment accuracy and reliability are improved.
Specifically, the duration detection unit 12 includes a start time detection subunit, a stop time detection subunit, a suspension period detection subunit, and a calculation subunit, wherein,
the starting time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface enters the interface picture of the course as the starting time;
the termination time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface exits from the interface picture of the course as the termination time;
the pause period detection subunit is used for counting the pause period of the user in the same picture after entering the interface picture of the course;
the calculating subunit is configured to obtain the final difference value as the viewing duration by continuously making a difference between the difference value between the ending time and the starting time and the pause period.
Specifically, the interface picture of the user entering the course by using the interface is that the similarity calculation result of the edge profile feature of the interface of the user entering the course and the edge profile feature of the interface picture of the course is greater than or equal to the preset similarity, the interface picture of the user exiting the course by using the interface is that the similarity calculation result of the edge profile feature of the interface of the user entering the course and the edge profile feature of the interface picture of the course is smaller than the preset similarity, and the similarity calculation result of the edge profile feature of the user entering the interface picture of the course is 100% when the user enters the interface picture of the course and is adjacent to the picture on the same picture.
Specifically, the embodiment of the invention can accurately acquire the time when the user enters and exits the interface picture of the course by setting the starting time detection subunit and the ending time detection subunit to actually detect the user using interface, so that the time when the user watches the course can be accurately calculated, the pause time detection subunit is set to count the pause time of the user in the same picture after entering the interface picture of the course as the pause time, and the pause time of the user in the course of watching the course can be accurately acquired, so that the time when the user watches the course can be more accurately calculated, and the time when the user watches the course can be accurately calculated by setting the calculation subunit in a mode that the difference between the ending time and the starting time and the pause time continuously acts as the difference, thereby avoiding the one-sided property and the error of a single index and improving the accuracy and the reliability of calculation.
Specifically, the judging unit 13 includes a frequency comparing subunit and a duration comparing subunit, wherein,
the frequency comparison subunit is configured to compare the real-time viewing frequency with a preset viewing frequency, delete the course if the real-time viewing frequency is smaller than the preset viewing frequency, and send a duration comparison instruction if the real-time viewing frequency is greater than or equal to the preset viewing frequency;
the time length comparison subunit is connected with the frequency comparison subunit and is used for receiving the time length comparison instruction, comparing the real-time watching time length with the preset watching time length, deleting the course if the real-time watching time length is smaller than the preset watching time length, and sending a course detection instruction if the watching time length is larger than or equal to the preset watching time length.
Referring to fig. 3, the contrast comparing module 30 includes a gray level detecting unit 31, a contrast calculating unit 32, and a comparing unit 33, wherein,
the gray level detecting unit 31 is configured to detect gray level values of an image of the interface screen of the lesson by using image processing software, obtain a plurality of gray level values, and extract a maximum gray level value and a minimum gray level value of the plurality of gray level values;
The contrast calculating unit 32 is connected to the gray level detecting unit 31 to pass through the formula c= (H) max -H min )/H min Calculating the actual contrast, wherein C is the actual contrast, H max For the maximum gray value, H min Is the minimum gray value;
the comparing unit 33 is connected to the contrast calculating unit 32, and is configured to compare the actual contrast with the preset contrast, so as to obtain a comparison result.
Specifically, in the embodiment of the present invention, the gray level detection unit 31 is configured to detect the gray level value of the image of the interface picture of the course by using image processing software, so that the gray level information of the image can be accurately obtained, a basis is provided for the subsequent contrast calculation, the contrast calculation unit 32 is configured to calculate the actual contrast by using the formula c= (Hmax-Hmin)/Hmin, so that the actual contrast of the interface picture of the course can be accurately calculated, a basis is provided for the subsequent comparison, the comparison unit 33 is configured to compare the actual contrast with the preset contrast, a comparison result can be accurately obtained, and whether the contrast of the interface picture of the course meets the requirement is determined, a basis is provided for the subsequent course repair, and the accuracy and pertinence of the repair are improved.
Specifically, the audio comparing module 50 includes an audio acquisition unit, an audio separation unit, a noise calculation unit, a non-noise calculation unit, a signal-to-noise ratio calculation unit, and a comparing unit, wherein,
the audio acquisition unit is used for extracting the audio in the course through audio processing software and acquiring an audio signal of the course;
the audio separation unit is connected with the audio acquisition unit and used for separating a noise signal and a non-noise signal in the audio signal through a high-pass filter to acquire the noise signal and the non-noise signal;
the noise calculation unit is connected with the audio separation unit and used for extracting noise signals in a preset period, and the power spectrum density of the noise signals in the preset period is obtained by carrying out power spectrum density calculation on the noise signals;
the non-noise calculation unit is connected with the audio separation unit and used for extracting a non-noise signal in the same preset period, and the power spectrum density of the non-noise signal in the preset period is obtained by carrying out power spectrum density calculation on the non-noise signal;
the signal-to-noise ratio calculating unit is connected with the noise calculating unit and the non-noise calculating unit and is used for calculating the noise by the formula of X=P Non-noise /P Noise (S) Calculating the real-time signal-to-noise ratio, wherein X is the signal-to-noise ratio and P Non-noise Power spectral density for non-noise signalsDegree, P Noise (S) Power spectral density for noise signals;
the comparison unit is connected with the signal-to-noise ratio calculation unit and used for comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to obtain a comparison result.
Specifically, the embodiment of the invention can accurately acquire the audio signal of the course by setting the audio acquisition unit to extract the audio in the course by adopting audio processing software, provide basis for subsequent audio separation and signal-to-noise ratio calculation, accurately acquire the noise signal and the non-noise signal by setting the audio separation unit to separate the noise signal from the non-noise signal by adopting a high-pass filter, provide basis for subsequent noise and non-noise signal power spectrum density calculation, extract the noise signal in a preset time period by setting the noise calculation unit, accurately acquire the power spectrum density of the noise signal in the preset time period by carrying out power spectrum density calculation on the noise signal, provide basis for subsequent signal-to-noise ratio calculation, extract the non-noise signal in the same preset time period by setting the non-noise calculation unit, accurately acquire the power spectrum density of the non-noise signal in the preset time period by carrying out power spectrum density calculation on the non-noise signal, provide basis for subsequent signal-to-noise ratio calculation, accurately acquire the signal-to-noise ratio by setting the signal-to-noise ratio calculation unit to-noise signal in the preset time period, accurately compare the signal-to-noise ratio with the subsequent course, and accurately compare the signal-to-noise ratio with the real-time course, and accurately provide basis for the subsequent course.
Referring to fig. 4, the course repair module 60 includes a picture repair unit 61 and an audio repair unit 62, wherein,
the picture repairing unit 61 is configured to receive the picture repairing instruction, and perform contrast repairing on the interface picture of the course by using a contrast enhancement algorithm, so as to obtain a repaired image;
the audio repairing unit 62 is configured to receive the audio repairing instruction, and repair noise of the audio of the lesson through a noise reduction algorithm.
Specifically, the picture restoration unit 61 includes a picture extraction subunit and a picture restoration subunit, wherein,
the picture extraction subunit is configured to extract a picture corresponding to the actual contrast smaller than the preset contrast in the interface picture of the course as a picture to be repaired;
the picture repairing subunit is connected with the picture extracting subunit and used for obtaining an image gray level histogram of the picture to be repaired through image processing software, calculating a cumulative distribution function of each gray level according to the image gray level histogram result, and mapping the gray level value of each pixel point in the image of the picture to be repaired to a new gray level to obtain a repaired image.
Specifically, the obtaining, by the picture repairing subunit, the image gray-scale histogram of the picture to be repaired by using image processing software includes:
Converting the picture to be repaired into a gray level image, and obtaining the gray level image to be repaired;
acquiring a plurality of pixel values in the gray level image to be repaired through image processing software;
acquiring a plurality of gray value levels corresponding to a plurality of pixel values by searching a gray value level database;
establishing a rectangular coordinate system with an X axis as a gray level and a Y axis as the number of pixels corresponding to each gray level, and drawing the gray levels corresponding to a plurality of pixel values and the number of pixels corresponding to each gray level in the rectangular coordinate system to obtain an image gray histogram of the picture to be repaired.
Specifically, calculating the cumulative distribution function of each gray level from the image gray histogram result includes calculating the cumulative distribution function of each gray level, starting from gray level 0, adding the number of pixels of each gray level to the number of pixels of the previous gray level, and normalizing the cumulative distribution function to have a value ranging from 0 to 1.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An online course management system based on a cloud platform, comprising:
the judging module is used for detecting user behavior data, judging whether the course is deleted or not according to the user behavior data, and sending a course detection instruction when the course is not deleted, wherein the user behavior data comprises the watching frequency of a user watching the course and the watching duration of the user watching the course;
the cloud storage module is used for storing preset contrast of the interface picture of the course and preset signal-to-noise ratio of the audio corresponding to the course;
the contrast comparison module is connected with the judging module and the cloud storage module and is used for receiving the course detection instruction, carrying out contrast detection on interface pictures of the courses to obtain actual contrast, and comparing the actual contrast with the preset contrast to obtain a comparison result;
The instruction sending module is connected with the contrast comparison module and used for sending a picture repair instruction when the contrast is smaller than the preset contrast;
or alternatively, the first and second heat exchangers may be,
when the contrast is larger than or equal to the preset contrast, sending an audio detection instruction;
the audio comparison module is connected with the cloud storage module and the instruction sending module and is used for receiving the audio detection instruction, detecting the audio of the course in real time, acquiring the real-time signal-to-noise ratio of the audio of the course, and comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to acquire a comparison result;
the course repairing module is connected with the instruction sending module and used for repairing the contrast of the pictures of the courses according to the picture repairing instruction when receiving the picture repairing instruction;
or alternatively, the first and second heat exchangers may be,
and repairing the audio of the course when the real-time signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio.
2. The online class management system based on the cloud platform as recited in claim 1, wherein the determination module includes a frequency detection unit, a duration detection unit, and a determination unit, wherein,
the frequency detection unit is used for counting the times of clicking interface pictures entering courses by a user to obtain the real-time watching frequency of the user watching the courses;
The time length detection unit is used for detecting and calculating the starting time, the ending time and the pause period of the course watched by the user to obtain the real-time watching time length of the course watched by the user;
the judging unit is connected with the frequency detecting unit and the duration detecting unit and is used for judging whether the courses are deleted or not according to comparison of the real-time watching frequency and the preset watching frequency and/or the comparison of the real-time watching duration and the preset watching duration.
3. The cloud platform based online curriculum management system of claim 2, wherein said frequency detection unit comprises an interface detection subunit, an interface discrimination subunit and a statistics subunit, wherein,
the interface detection subunit is used for detecting a user interface in real time to acquire a plurality of real-time images;
the interface judging subunit is connected with the interface detecting subunit and is used for extracting edge contour features in a plurality of real-time images through an edge detecting algorithm, carrying out similarity calculation on the edge contour features and the edge contour features of the interface pictures of the courses, and if the similarity calculation result is greater than or equal to a preset similarity, using an interface by the user as the interface picture of the courses;
The statistics subunit is connected with the interface discrimination subunit and is used for counting the times of using an interface by the user as an interface picture of the course, namely the real-time watching frequency.
4. The online class management system based on the cloud platform as recited in claim 3, wherein the duration detection unit includes a start time detection subunit, a stop time detection subunit, a pause period detection subunit, and a calculation subunit, wherein,
the starting time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface enters the interface picture of the course as the starting time;
the termination time detection subunit is used for actually detecting the user use interface and acquiring the time when the user use interface exits from the interface picture of the course as the termination time;
the pause period detection subunit is used for counting the pause period of the user in the same picture after entering the interface picture of the course;
the calculating subunit is configured to obtain the final difference value as the viewing duration by continuously making a difference between the difference value between the ending time and the starting time and the pause period.
5. The online class management system based on the cloud platform as recited in claim 4, wherein the determination unit includes a frequency comparison subunit and a duration comparison subunit, wherein,
the frequency comparison subunit is configured to compare the real-time viewing frequency with a preset viewing frequency, delete the course if the real-time viewing frequency is smaller than the preset viewing frequency, and send a duration comparison instruction if the real-time viewing frequency is greater than or equal to the preset viewing frequency;
the time length comparison subunit is connected with the frequency comparison subunit and is used for receiving the time length comparison instruction, comparing the real-time watching time length with the preset watching time length, deleting the course if the real-time watching time length is smaller than the preset watching time length, and sending a course detection instruction if the watching time length is larger than or equal to the preset watching time length.
6. The online class management system based on the cloud platform of claim 5, wherein the contrast comparison module comprises a gray level detection unit, a contrast calculation unit, and a comparison unit, wherein,
the gray level detection unit is used for detecting gray level values of images of interface pictures of the courses through image processing software, obtaining a plurality of gray level values, and extracting the maximum gray level value and the minimum gray level value in the gray level values;
The contrast calculating unit is connected with the gray level detecting unit and is used for calculating the contrast of the image according to the formula C= (H) max -H min )/H min Calculating the actual contrast, wherein C is the actual contrast, H max For the maximum gray value, H min Is the minimum gray value;
the comparison unit is connected with the contrast calculating unit and used for comparing the actual contrast with the preset contrast to obtain a comparison result.
7. The online class management system based on the cloud platform of claim 6, wherein the audio comparison module comprises an audio acquisition unit, an audio separation unit, a noise calculation unit, a non-noise calculation unit, a signal to noise ratio calculation unit, and a comparison unit, wherein,
the audio acquisition unit is used for extracting the audio in the course through audio processing software and acquiring an audio signal of the course;
the audio separation unit is connected with the audio acquisition unit and used for separating a noise signal and a non-noise signal in the audio signal through a high-pass filter to acquire the noise signal and the non-noise signal;
the noise calculation unit is connected with the audio separation unit and used for extracting noise signals in a preset period, and the power spectrum density of the noise signals in the preset period is obtained by carrying out power spectrum density calculation on the noise signals;
The non-noise calculation unit is connected with the audio separation unit and used for extracting a non-noise signal in the same preset period, and the power spectrum density of the non-noise signal in the preset period is obtained by carrying out power spectrum density calculation on the non-noise signal;
the signal-to-noise ratio calculating unit is connected with the noise calculating unit and the non-noise calculating unit and is used for calculating the noise by the formula of X=P Non-noise /P Noise (S) Calculating the real-time signal-to-noise ratio, wherein X is the signal-to-noise ratio and P Non-noise Power spectral density, P, of non-noise signals Noise (S) Power spectral density for noise signals;
the comparison unit is connected with the signal-to-noise ratio calculation unit and used for comparing the real-time signal-to-noise ratio with the preset signal-to-noise ratio to obtain a comparison result.
8. The online class management system based on the cloud platform as recited in claim 7, wherein the class restoration module comprises a picture restoration unit and an audio restoration unit, wherein,
the picture repairing unit is used for receiving the picture repairing instruction, and performing contrast repairing on the interface picture of the course through a contrast enhancement algorithm to obtain a repairing image;
the audio repairing unit is used for receiving the audio repairing instruction and repairing noise of the audio of the lesson through a noise reduction algorithm.
9. The online class management system based on the cloud platform of claim 8, wherein the picture repair unit comprises a picture extraction sub-unit and a picture repair sub-unit, wherein,
the picture extraction subunit is configured to extract a picture corresponding to the actual contrast smaller than the preset contrast in the interface picture of the course as a picture to be repaired;
the picture repairing subunit is connected with the picture extracting subunit and used for obtaining an image gray level histogram of the picture to be repaired through image processing software, calculating a cumulative distribution function of each gray level according to the image gray level histogram result, and mapping the gray level value of each pixel point in the image of the picture to be repaired to a new gray level to obtain a repaired image.
10. The cloud platform based online lesson management system of claim 9, wherein said picture restoration subunit obtaining an image gray-scale histogram of said picture to be restored by image processing software comprises:
converting the picture to be repaired into a gray level image, and obtaining the gray level image to be repaired;
acquiring a plurality of pixel values in the gray level image to be repaired through image processing software;
Acquiring a plurality of gray value levels corresponding to a plurality of pixel values by searching a gray value level database;
establishing a rectangular coordinate system with an X axis as a gray level and a Y axis as the number of pixels corresponding to each gray level, and drawing the gray levels corresponding to a plurality of pixel values and the number of pixels corresponding to each gray level in the rectangular coordinate system to obtain an image gray histogram of the picture to be repaired.
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