Intelligent selection system of key monitoring images for distance education

Abstract

The present invention relates to an intelligent selection system for key monitoring images for remote education, comprising: a signal identification mechanism, which is used to intelligently judge whether the nose and hands of a student overlap based on various visual information of the nose and hands in a directional blurred image; a compression transmission mechanism, which is used to wirelessly transmit the directional blurred image as a single-frame key monitoring image to a handheld mobile terminal of a guardian of a remote education student when judging that the nose and hands overlap in the directional blurred image. The intelligent selection system for key monitoring images for remote education of the present invention has compact logic and intelligent control. It can intelligently judge whether the nose and hands of a student overlap based on various visual information of the nose and hands, and wirelessly transmit the remote education monitoring image with overlapping nose and hands as a key monitoring image to the handheld mobile terminal of the guardian of the remote education student, thereby improving the visual monitoring effect and visual monitoring efficiency of remote education.

Description

Technical Field

[0001] The invention relates to the field of distance education, and in particular to a key monitoring image intelligent selection system for distance education. Background Art

[0002] Modern distance education can effectively play the characteristics of distance education. It is a teaching activity that is different from face-to-face education, which is separated from teachers and students and not organized face-to-face. It is an education system and teaching model that crosses schools and regions. Its characteristics are: students and teachers are separated; specific transmission systems and media are used for teaching; information is transmitted in a variety of ways; and learning places and forms are flexible and changeable. Compared with face-to-face education, the advantages of distance education are that it can break through the limitations of time and space; provide more learning opportunities; expand the scale of teaching; improve teaching quality; and reduce the cost of teaching.

[0003] However, distance education also has its inherent disadvantages. For example, because the distance classroom is far away, it is difficult to fully control the learning effect and learning discipline of local students. Although there are some video devices, they are not first-hand data. For example, during the distance education process, students often touch their noses with their hands, which is regarded as a behavior of not paying attention to the lectures. However, in the current distance education monitoring, there is a lack of targeted and high-precision detection solutions for touching the nose with hands. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides an intelligent selection system for key monitoring images for distance education, which can extract sub-images of nose and hands respectively as the first reference image and the second reference image based on the color imaging characteristics of the nose and the hands. When there are overlapping pixels in the first reference image and the second reference image, the overlapping pixels are taken as single overlapping pixels, and the number of overlapping pixels of the first reference image and the second reference image is determined as the identification representative number. When the identification representative number is greater than or equal to zero, it is judged that the nose and the hands overlap, and the distance education monitoring image with the overlapping nose and hands is compressed as the key monitoring image and wirelessly transmitted to the handheld mobile terminal of the guardian of the distance education recipient, thereby realizing the intelligent selection of key monitoring images for distance education and effectively deterring the behavior of the distance education recipient that affects the educational level.

[0005] According to the present invention, a system for intelligently selecting key monitoring images for remote education is provided, the system comprising:

[0006] A live video recording mechanism, used to perform live video recording operations on the remote education environment to obtain live video images corresponding to respective time stamps, wherein the respective time stamps are evenly spaced on the time axis;

[0007] A gamma correction device, connected to the live video recording mechanism, is used to perform gamma correction processing on the live video images corresponding to each received timestamp to obtain and output a corresponding gamma-corrected image;

[0008] a smoothing filter device connected to the gamma correction device, and configured to perform edge-preserving smoothing filtering on the received gamma-corrected image to obtain and output a corresponding smoothing filtered image;

[0009] A directional blurring device, connected to the smoothing filter device, for performing directional blurring processing on the received smoothing filter image to obtain and output a corresponding directional blurring image;

[0010] a signal identification mechanism connected to the directional blur device, and used for receiving the directional blur image, obtaining the sub-images where the nose and the hand are located in the directional blur image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hand overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hand do not overlap when the identification representative number is less than zero, wherein the sub-image where the nose is located is detected based on the color imaging characteristics of the nose, and the sub-image where the hand is located is detected based on the color imaging characteristics of the hand;

[0011] A compression transmission mechanism connected to the signal identification mechanism is used to, when it is determined that the nose and the hand overlap in the directional blurred image, perform compression processing on the directional blurred image as a single-frame key monitoring image and then wirelessly transmit it to a handheld mobile terminal of a guardian of the remote education student;

[0012] Wherein, determining the number of overlapping pixel points of the first reference image and the second reference image as the representative number for identification includes: when there are overlapping pixel points between the first reference image and the second reference image, treating the overlapping pixel points as single overlapping pixel points.

[0013] The key monitoring image intelligent selection system for remote education of the present invention has compact logic and intelligent control. Since it can intelligently judge whether the nose and hands of the trainee overlap based on various visual information of the nose and hands, and wirelessly transmit the remote education monitoring image with overlapping nose and hands as the key monitoring image to the handheld mobile terminal of the guardian of the remote education learner, the visual monitoring effect and visual monitoring efficiency of the remote education are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0015] Figure 1 The figure is a schematic diagram of the internal structure of a key monitoring image intelligent selection system for remote education according to a nose embodiment of the present invention.

[0016] Figure 2 It is a schematic diagram of the internal structure of a key monitoring image intelligent selection system for remote education according to a hand embodiment of the present invention.

[0017] Figure 3 It is a schematic diagram of the internal structure of the key monitoring image intelligent selection system for remote education according to Embodiment C of the present invention. DETAILED DESCRIPTION

[0018] The following will describe in detail an embodiment of the intelligent selection system of key monitoring images for distance education according to the present invention with reference to the accompanying drawings.

[0019] Figure 1 The internal structure diagram of the key monitoring image intelligent selection system for remote education according to the nose embodiment of the present invention is shown, and the system includes:

[0020] A live video recording mechanism, used to perform live video recording operations on the remote education environment to obtain live video images corresponding to respective time stamps, wherein the respective time stamps are evenly spaced on the time axis;

[0021] Specifically, the on-site video recording mechanism includes a timing processing component, a video recording execution component and a picture output component, which are used to collaboratively complete the on-site video recording operation on the remote education environment to obtain the on-site video pictures corresponding to the respective time stamps;

[0022] A gamma correction device, connected to the live video recording mechanism, is used to perform gamma correction processing on the live video images corresponding to each received timestamp to obtain and output a corresponding gamma-corrected image;

[0023] For example, the gamma correction device is connected to the live video recording mechanism and is used to perform gamma correction processing on the live video picture corresponding to each received timestamp to obtain and output the corresponding gamma-corrected image, including: an FPGA chip can be selected to implement the gamma correction device, which is connected to the live video recording mechanism and is used to perform gamma correction processing on the live video picture corresponding to each received timestamp to obtain and output the corresponding gamma-corrected image;

[0024] a smoothing filter device connected to the gamma correction device, and configured to perform edge-preserving smoothing filtering on the received gamma-corrected image to obtain and output a corresponding smoothing filtered image;

[0025] A directional blurring device, connected to the smoothing filter device, for performing directional blurring processing on the received smoothing filter image to obtain and output a corresponding directional blurring image;

[0026] a signal identification mechanism connected to the directional blur device, and used for receiving the directional blur image, obtaining the sub-images where the nose and the hand are located in the directional blur image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hand overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hand do not overlap when the identification representative number is less than zero, wherein the sub-image where the nose is located is detected based on the color imaging characteristics of the nose, and the sub-image where the hand is located is detected based on the color imaging characteristics of the hand;

[0027] A compression transmission mechanism connected to the signal identification mechanism is used to, when it is determined that the nose and the hand overlap in the directional blurred image, perform compression processing on the directional blurred image as a single-frame key monitoring image and then wirelessly transmit it to a handheld mobile terminal of a guardian of the remote education student;

[0028] Wherein, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number includes: when there are overlapping pixel points in the first reference image and the second reference image, treating the overlapping pixel points in the first reference image and the second reference image as single overlapping pixel points;

[0029] Wherein, the compression transmission mechanism is also used for treating the directional blurred image as a single-frame non-key monitoring image without performing compression processing when it is determined that the nose and the hand in the directional blurred image do not overlap;

[0030] Wherein, when it is determined that the nose and the hand overlap in the directional blurred image, the directional blurred image is used as a single-frame key monitoring image and then compressed and wirelessly transmitted to the handheld mobile terminal of the guardian of the distance education learner, including: using HEVC compression encoding format to compress the directional blurred image;

[0031] Among them, obtaining sub-images where the nose and the hands are respectively located in the directional blurred image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hands overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hands do not overlap when the identification representative number is less than zero, includes: using MATLAB toolbox to simulate the data processing of obtaining sub-images where the nose and the hands are respectively located in the directional blurred image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hands overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hands do not overlap when the identification representative number is less than zero.

[0032] Figure 2 It is a schematic diagram of the internal structure of a key monitoring image intelligent selection system for remote education according to a hand embodiment of the present invention.

[0033] and Figure 1 different, Figure 2 The key monitoring image intelligent selection system for distance education may also include the following components:

[0034] A parameter configuration device, connected to the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism, respectively, for providing the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism with the parameter configuration services required by each of them;

[0035] The parameter configuration device is connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively, and is used to provide the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism with the parameter configuration services required by each of them, including: the parameter configuration device can be realized by using an SOC device, and is used to provide the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism with the parameter configuration services required by each of them;

[0036] Wherein, the parameter configuration device is respectively connected to the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism, and is used to provide the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism with the parameter configuration services required by each of them, and further comprises: the parameter configuration device uses an IIC configuration bus to provide the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism with the parameter configuration services required by each of them;

[0037] The parameter configuration device uses an IIC configuration bus to provide the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism with the required parameter configuration services, including: the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism have different IIC configuration addresses respectively;

[0038] The gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism respectively have different IIC configuration addresses, including: the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism respectively have different IIC configuration addresses in a binary value representation mode;

[0039] Among them, the different IIC configuration addresses respectively possessed by the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism are in a binary numerical representation mode, including: the byte lengths of the different IIC configuration addresses respectively possessed by the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism are equal.

[0040] Figure 3 It is a schematic diagram of the internal structure of the key monitoring image intelligent selection system for remote education according to Embodiment C of the present invention.

[0041] and Figure 1 different, Figure 3 The key monitoring image intelligent selection system for distance education may also include the following components:

[0042] A positioning operation device, connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism, respectively, for providing positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism, respectively;

[0043] Wherein, the positioning operation device is connected to the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism respectively, and is used to provide positioning services for the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism respectively, including: the positioning operation device adopts the GPS positioning mechanism to provide GPS positioning services for the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism respectively;

[0044] Among them, the positioning operation device is respectively connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism, and is used to provide positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively, including: the positioning operation device adopts the Beidou positioning mechanism to provide Beidou positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively.

[0045] In addition, in the key monitoring image intelligent selection system for distance education, the sub-image where the nose is located is detected based on the color imaging characteristics of the nose, and the sub-image where the hand is located is detected based on the color imaging characteristics of the hand, including: the color imaging characteristics of the nose are the value distribution intervals of each color channel of the nose in the RGB color space, and the color imaging characteristics of the hand are the value distribution intervals of each color channel of the hand in the RGB color space;

[0046] And wherein, detecting the sub-image where the nose is located based on the color imaging characteristics of the nose, and detecting the sub-image where the hand is located based on the color imaging characteristics of the hand further include: the color imaging characteristics of the nose are the R color channel value distribution interval, the G color channel value distribution interval and the B color channel value distribution interval of the nose in the RGB color space, and the color imaging characteristics of the hand are the R color channel value distribution interval, the G color channel value distribution interval and the B color channel value distribution interval of the hand in the RGB color space, wherein the value range of any color channel value distribution interval is between 0-255, and at the same time, the color imaging characteristics of the nose are different from the color imaging characteristics of the hand, which is specifically manifested in that the specific value ranges of any type of color channel value distribution intervals are different;

[0047] For example, the R color channel value distribution interval corresponding to the nose and the R color channel value distribution interval corresponding to the hand have different specific value ranges.

[0048] The present invention has at least the following three beneficial technical effects:

[0049] First, based on the color imaging characteristics of the nose and the hand, the sub-images of the nose and the hand are respectively extracted as the first reference image and the second reference image. When there are overlapping pixels between the first reference image and the second reference image, the overlapping pixels are regarded as single overlapping pixels.

[0050] Second step: determining the number of overlapping pixels of the first reference image and the second reference image as the identification representative number, and when the identification representative number is greater than or equal to zero, determining that the nose and the hand overlap;

[0051] Third: The remote education monitoring images with overlapping noses and hands are treated as key monitoring images and then compressed and wirelessly transmitted to the handheld mobile terminal of the guardian of the remote education recipients, thereby realizing the intelligent selection of key monitoring images for remote education and effectively deterring behaviors that affect the educational level of the remote education recipients.

[0052] Those skilled in the art will readily appreciate the additional advantages and changes. Therefore, the present invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Therefore, various changes may be made without departing from the spirit or scope of the general inventive concept defined by the appended claims and their equivalents.

Claims

1. A key monitoring image intelligent selection system for distance education, characterized in that: The system comprises: A live video recording mechanism, used to perform live video recording operations on the remote education environment to obtain live video images corresponding to respective time stamps, wherein the respective time stamps are evenly spaced on the time axis; A gamma correction device, connected to the live video recording mechanism, is used to perform gamma correction processing on the live video images corresponding to each received timestamp to obtain and output a corresponding gamma-corrected image; a smoothing filter device connected to the gamma correction device, and configured to perform edge-preserving smoothing filtering on the received gamma-corrected image to obtain and output a corresponding smoothing filtered image; A directional blurring device, connected to the smoothing filter device, for performing directional blurring processing on the received smoothing filter image to obtain and output a corresponding directional blurring image; a signal identification mechanism connected to the directional blur device, and used for receiving the directional blur image, obtaining the sub-images where the nose and the hand are located in the directional blur image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hand overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hand do not overlap when the identification representative number is less than zero, wherein the sub-image where the nose is located is detected based on the color imaging characteristics of the nose, and the sub-image where the hand is located is detected based on the color imaging characteristics of the hand; A compression transmission mechanism connected to the signal identification mechanism is used to, when it is determined that the nose and the hand overlap in the directional blurred image, perform compression processing on the directional blurred image as a single-frame key monitoring image and then wirelessly transmit it to a handheld mobile terminal of a guardian of the remote education student; Wherein, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number includes: when there are overlapping pixel points in the first reference image and the second reference image, treating the overlapping pixel points in the first reference image and the second reference image as single overlapping pixel points; The compression transmission mechanism is also used for treating the directional blurred image as a single-frame non-emphasis monitoring image and not performing compression processing when it is determined that the nose and the hand in the directional blurred image do not overlap; Wherein, when it is determined that the nose and the hand overlap in the directional blurred image, the directional blurred image is used as a single-frame key monitoring image and then compressed and wirelessly transmitted to the handheld mobile terminal of the guardian of the distance education learner, including: using HEVC compression encoding format to compress the directional blurred image; Wherein, obtaining the sub-images where the nose and the hand are respectively located in the directional blurred image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hand overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hand do not overlap when the identification representative number is less than zero, comprises: using MATLAB toolbox to simulate and implement data processing of obtaining the sub-images where the nose and the hand are respectively located in the directional blurred image as the first reference image and the second reference image, determining the number of overlapping pixel points of the first reference image and the second reference image as the identification representative number, and judging that the nose and the hand overlap when the identification representative number is greater than or equal to zero, and judging that the nose and the hand do not overlap when the identification representative number is less than zero; Among them, detecting the sub-image where the nose is located based on the color imaging characteristics of the nose, and detecting the sub-image where the hand is located based on the color imaging characteristics of the hand includes: the color imaging characteristics of the nose are the value distribution intervals of each color channel of the nose in the RGB color space, and the color imaging characteristics of the hand are the value distribution intervals of each color channel of the hand in the RGB color space; and wherein, detecting the sub-image where the nose is located based on the color imaging characteristics of the nose, and detecting the sub-image where the hand is located based on the color imaging characteristics of the hand also include: the color imaging characteristics of the nose are the R color channel value distribution interval, the G color channel value distribution interval and the B color channel value distribution interval of the nose in the RGB color space, and the color imaging characteristics of the hand are the R color channel value distribution interval, the G color channel value distribution interval and the B color channel value distribution interval of the hand in the RGB color space, wherein the value range of any color channel value distribution interval is between 0-255, and at the same time, the color imaging characteristics of the nose are different from the color imaging characteristics of the hand, which is specifically manifested in that the specific value ranges of any type of color channel value distribution interval are different.

2. The key monitoring image intelligent selection system for remote education according to claim 1, characterized in that: The system further comprises: A parameter configuration device, connected to the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism, respectively, for providing the gamma correction device, the smoothing filter device, the directional blur device and the signal identification mechanism with the parameter configuration services required by each of them; Among them, the parameter configuration device is respectively connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism, and is used to provide the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism with the parameter configuration services they need respectively, including: the parameter configuration device uses the IIC configuration bus to provide the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism with the parameter configuration services they need respectively.

3. The key monitoring image intelligent selection system for remote education as claimed in claim 2, characterized in that: The parameter configuration device uses the IIC configuration bus to provide the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism with the required parameter configuration services, including: the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism have different IIC configuration addresses respectively.

4. The key monitoring image intelligent selection system for remote education as claimed in claim 3, characterized in that: The gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively have different IIC configuration addresses, including: the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively have different IIC configuration addresses in binary numerical representation mode.

5. The key monitoring image intelligent selection system for remote education as claimed in claim 4, characterized in that: The different IIC configuration addresses respectively possessed by the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism are in a binary numerical representation mode, including: the byte lengths of the different IIC configuration addresses respectively possessed by the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism are equal.

6. The key monitoring image intelligent selection system for remote education according to claim 1, characterized in that: The system further comprises: The positioning operation device is connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively, and is used to provide positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively.

7. The key monitoring image intelligent selection system for remote education as claimed in claim 6, characterized in that: The positioning operation device is respectively connected to the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism, and is used to provide positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively, including: the positioning operation device adopts the GPS positioning mechanism to provide GPS positioning services for the gamma correction device, the smoothing filter device, the directional blurring device and the signal identification mechanism respectively.

8. The key monitoring image intelligent selection system for remote education as claimed in claim 6, characterized in that: The positioning operation device is respectively connected to the gamma correction device, the smoothing filter device, the directional defocusing device and the signal identification mechanism, and is used to provide positioning services for the gamma correction device, the smoothing filter device, the directional defocusing device and the signal identification mechanism respectively, including: the positioning operation device adopts the Beidou positioning mechanism to provide Beidou positioning services for the gamma correction device, the smoothing filter device, the directional defocusing device and the signal identification mechanism respectively.

Images