CN117354494A - Testing method for night vision switching performance of intelligent camera - Google Patents
Testing method for night vision switching performance of intelligent camera Download PDFInfo
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Abstract
The invention relates to the technical field of image communication, in particular to a method for testing night vision switching performance of an intelligent camera, which comprises the following steps: the intelligent camera and the intelligent bulb are connected with each other and electrified, and the mobile phone apps live pictures; controlling the intelligent bulb to be directly switched on and off, recording the starting time of the intelligent bulb to be directly switched on and off, intercepting a live broadcast picture of the mobile phone app by a data processor, analyzing and judging whether the test is successful or not; controlling the intelligent bulb to be opened gradually, and intercepting a live broadcast picture of the mobile phone app by the data processor, analyzing and judging whether the test is successful or not; and (5) counting the success rate of the test, and judging whether the night vision switching speed and the sensitivity to light of the intelligent camera meet the requirements. The method provided by the invention can realize automatic test of night vision switching performance of the intelligent camera, and if the test is unsuccessful, whether the night vision switching speed of the intelligent camera is inconsistent or the sensitivity of the intelligent camera to light is inconsistent can be judged.
Description
Technical Field
The invention relates to the technical field of image communication, in particular to a testing method for night vision switching performance of an intelligent camera.
Background
Shooting and recording of shooting products at night becomes a common scene, and a night vision function becomes one of important functional modules of the intelligent camera. The conventional night vision scheme of the intelligent camera is to automatically switch on and off the night vision function, namely, automatically switch on the night vision function when the ambient light darkens to a threshold value; and when the ambient light lightens to a certain threshold value, automatically turning off the night vision function. If the night vision function cannot be switched correctly according to the ambient light, the night picture recording effect is black, and the day picture recording effect is black and white. Therefore, the stability of the night vision automatic switching function is also an important index for measuring the quality of products, and a testing method for switching the night vision function is very important.
One of the current night vision function test schemes for intelligent camera products is to adopt manual operation to manufacture darkening of the camera environment and simulate night scenes. The mobile phone app is manually operated to be connected with the picture of the intelligent camera to observe whether the night vision function is started or not, and whether the picture is in a normal night vision state or not. And then, manually manufacturing the night vision device to lighten ambient light, simulate a daytime scene, and check whether the night vision function is closed or not and whether the app picture is in a non-night vision state or not. The scene needs a large number of tests, and the night vision switching success rate is counted to test the functional stability. The scheme has the defects of complicated manual testing operation, higher cost, easy manual fatigue and inaccurate timing statistical data.
And the second scheme is to adopt a partial automation scheme, control the scene light by using a technical means and automatically trigger a night vision switching mechanism of the intelligent camera. The method has the defects that naked eye judgment is still needed to be carried out manually on a live image of the app, the degree of automation is not high, and whether the testing function is inconsistent is difficult to judge because the night vision switching speed of the intelligent camera is inconsistent or because the sensitivity of the intelligent camera to light is inconsistent.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a testing method for the night vision switching performance of the intelligent camera, which is characterized in that by controlling the direct on/off and gradual change on/off of an intelligent bulb and analyzing a live mobile phone app picture, whether the picture is in a night vision state or a non-night vision state is automatically judged, so that whether the test is successful is judged, if the test is unsuccessful, whether the night vision switching speed of the intelligent camera is not in accordance with the requirement or the sensitivity of the intelligent camera to light is not in accordance with the requirement is judged, and the improvement of the quality of the intelligent camera in the later stage is facilitated.
The invention is realized by the following technical scheme:
a testing method for night vision switching performance of an intelligent camera comprises the following steps:
s1: placing the intelligent camera and the intelligent bulb to be tested in a darkroom or a closed cassette, networking the intelligent camera and the intelligent bulb, and electrifying, wherein a mobile phone app is connected to a live broadcast picture of the intelligent camera;
s2: controlling the intelligent bulb to be directly turned on and turned off, recording the starting time of the intelligent bulb to be directly turned on and turned off, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture of the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture or a night vision picture, and recording the current time as the final switching time of the night vision picture;
s3: the data processor calculates the time required by night vision picture switching according to the direct on-off starting time and the final night vision picture switching time of the intelligent bulb, compares the time required by night vision picture switching with a preset time threshold, judges that the test is successful if the time required by night vision picture switching is within the preset time threshold range, and judges that the test fails if the time required by night vision picture switching is not within the preset time threshold range;
s4: controlling the intelligent bulb to be gradually opened, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture by the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture, recording the brightness of the current intelligent bulb, comparing the brightness of the current intelligent bulb with a threshold value of preset brightness, judging that the test is successful if the brightness of the current intelligent bulb is within the threshold value range of the preset brightness, and judging that the test is failed if the brightness of the current intelligent bulb is not within the threshold value range of the preset brightness;
s5: judging whether the preset test times are reached, if the preset test times are not reached, repeating the steps S2 to S4 until the preset test times are reached, counting the success rate of the direct opening and closing tests of the intelligent bulb and the success rate of the gradual opening test of the intelligent bulb, if the success rate of the direct opening and closing tests of the intelligent bulb is smaller than a preset value, judging that the night vision switching speed of the intelligent camera is not in accordance with the requirement, and if the success rate of the gradual opening test of the intelligent bulb is smaller than the preset value, judging that the sensitivity of the intelligent camera to light is not in accordance with the requirement.
Further, in step S2 and step S4, the screenshot is parsed according to the following steps:
d1: cutting the mobile phone app screenshot, and only reserving a live picture part of the intelligent camera;
d2: judging whether the picture is a pure black picture or a pure white picture, if the picture is the pure black picture or the pure white picture, directly judging the picture as a non-night vision picture or a night vision picture, and if the picture is not the pure black picture or the pure white picture, entering the next step;
d3: calculating three-color channel values of all pixels in a picture, and taking the difference between the maximum value and the minimum value in the three-color channel values of each pixel, if the difference is less than or equal to 15, recording the pixel as a night vision pixel, counting all the pixels of the picture, if the proportion of the total number of the night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as a night vision effect picture, if the difference is greater than 15, recording the pixel as an non-night vision pixel, counting all the pixels of the picture, and if the proportion of the total number of the non-night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as the non-night vision effect picture.
Further, in the step D2, the method for judging whether the frame is a pure black frame is as follows: and calculating the three-color channel value of each pixel point in the picture, recording the pixel point as a black pixel point if the three-color channel value of the pixel point is less than or equal to 5, carrying out black pixel point statistics on all the pixel points of the picture, and judging the picture as a pure black picture if the proportion of the total number of the black pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent.
Further, in the step D2, the method for judging whether the frame is a pure white frame is as follows: and calculating a three-color channel value of each pixel point in the picture, recording the pixel point as a white pixel point if the three-color channel value of the pixel point is more than or equal to 220, counting the white pixel points of all the pixel points of the picture, and judging the picture as a pure white picture if the proportion of the total number of the white pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent.
The invention has the beneficial effects that:
the testing method for the night vision switching performance of the intelligent camera has the following advantages:
1. the automation of the control of the ambient light is realized by controlling the intelligent bulb;
2. and automatically detecting the picture of the intelligent camera through a self-grinding analysis algorithm to judge whether the picture is in a night vision or non-night vision state. The manual operation is avoided, the automation of a higher degree is realized, a large number of tests can be performed, the test efficiency is improved, and compared with the manual operation, the timing acquisition is more accurate for the data statistics of timeliness;
3. through carrying out direct switch and gradual change luminance control to intelligent bulb, increased the variety and the controllability of test scene to can judge that the test function is unsatisfactory because intelligent camera night vision switching speed is unsatisfactory or because intelligent camera sensitivity to light is unsatisfactory, provide the reference for the direction of later stage intelligent camera quality improvement.
Drawings
FIG. 1 is a schematic flow chart of the method of the invention.
Fig. 2 is a schematic diagram of a process for parsing a screenshot according to the present invention.
Detailed Description
The invention relates to a testing method for night vision switching performance of an intelligent camera, a specific flow chart is shown in figure 1, and the testing method comprises the following steps:
s1: placing the intelligent camera and the intelligent bulb to be tested in a darkroom or a closed cassette, networking the intelligent camera and the intelligent bulb, and electrifying, wherein a mobile phone app is connected to a live broadcast picture of the intelligent camera;
the intelligent camera to be tested and the intelligent bulb are placed in a darkroom or a closed cassette, and the on-off control and the brightness of the bulb are adjusted by using a code program by calling an API (application program interface) of a cloud server to which the intelligent bulb belongs, so that the light intensity of the environment to which the intelligent camera belongs is automatically controlled, and the night vision switching function of the intelligent camera to be tested is triggered. The manual operation link is avoided, the testing efficiency is improved, and the method is simple and convenient and low in cost.
The method is suitable for the video camera product with gray-scale night vision and is not suitable for the video camera product with color night vision. Gray-scale color refers to pure white, pure black, and a series of transition colors from black to white in both.
S2: controlling the intelligent bulb to be directly turned on and turned off, recording the starting time of the intelligent bulb to be directly turned on and turned off, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture of the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture or a night vision picture, and recording the current time as the final switching time of the night vision picture; if the intelligent bulb is in the closed state to the open state, the analysis result is required to be a non-night vision picture, and the next time the intelligent bulb is in the open state to the closed state, the analysis result is required to be a night vision picture, and the two processes are repeatedly tested for a plurality of times.
S3: the data processor calculates the time required by night vision picture switching according to the direct on-off starting time and the final night vision picture switching time of the intelligent bulb, compares the time required by night vision picture switching with a preset time threshold, judges that the test is successful if the time required by night vision picture switching is within the preset time threshold range, and judges that the test fails if the time required by night vision picture switching is not within the preset time threshold range;
s4: controlling the intelligent bulb to be gradually opened, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture by the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture, recording the brightness of the current intelligent bulb, comparing the brightness of the current intelligent bulb with a threshold value of preset brightness, judging that the test is successful if the brightness of the current intelligent bulb is within the threshold value range of the preset brightness, and judging that the test is failed if the brightness of the current intelligent bulb is not within the threshold value range of the preset brightness;
s5: judging whether the preset test times are reached, if the preset test times are not reached, repeating the steps S2 to S4 until the preset test times are reached, counting the success rate of the direct opening and closing tests of the intelligent bulb and the success rate of the gradual opening test of the intelligent bulb, if the success rate of the direct opening and closing tests of the intelligent bulb is smaller than a preset value, judging that the night vision switching speed of the intelligent camera is not in accordance with the requirement, and if the success rate of the gradual opening test of the intelligent bulb is smaller than the preset value, judging that the sensitivity of the intelligent camera to light is not in accordance with the requirement.
By adopting the method to test the night vision switching performance of the intelligent camera, the automation of the control of the ambient light is realized, and the picture of the intelligent camera is automatically detected by a self-grinding analysis algorithm to judge whether the picture is in a night vision or non-night vision state. The manual operation is avoided, the automation of a higher degree is realized, a large number of tests can be performed, the test efficiency is improved, and compared with the manual operation, the timing acquisition is more accurate for the data statistics of timeliness; meanwhile, the intelligent bulb is directly switched on and switched off and gradually-changed brightness is controlled, so that the diversity and controllability of a test scene are improved, whether the test function is inconsistent with the requirement is judged accurately through testing, and a reference basis is provided for the quality improvement direction of the intelligent camera in the later stage because of the problem of night vision switching speed of the intelligent camera or the problem of sensitivity of the intelligent camera to light.
Further, in step S2 and step S4, the screenshot is parsed according to the following steps: the flow chart is shown in fig. 2:
d1: cutting the mobile phone app screenshot, and only reserving a live picture part of the intelligent camera;
d2: judging whether the picture is a pure black picture or a pure white picture, if the picture is the pure black picture or the pure white picture, directly judging the picture as a non-night vision picture or a night vision picture, and if the picture is not the pure black picture or the pure white picture, entering the next step;
whether the picture is a pure black picture or a pure white picture or not is judged in advance, and then the next step of analysis of the non-night vision effect picture or the night vision effect picture is carried out, so that the calculation amount of later analysis is simplified, the analysis method is simpler and quicker, and the test efficiency is improved.
D3: calculating three-color channel values of all pixels in a picture, and taking the difference between the maximum value and the minimum value in the three-color channel values of each pixel, if the difference is less than or equal to 15, recording the pixel as a night vision pixel, counting all the pixels of the picture, if the proportion of the total number of the night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as a night vision effect picture, if the difference is greater than 15, recording the pixel as an non-night vision pixel, counting all the pixels of the picture, and if the proportion of the total number of the non-night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as the non-night vision effect picture.
The method can detect whether the live image of the intelligent camera on the mobile phone app page is in a night vision mode or a non-night vision mode, so that manual naked eye judgment is avoided, automation of a verification link is realized, and a test result is more accurate.
Further, in the step D2, the method for judging whether the frame is a pure black frame is as follows: and calculating the three-color channel value of each pixel point in the picture, recording the pixel point as a black pixel point if the three-color channel value of the pixel point is less than or equal to 5, carrying out black pixel point statistics on all the pixel points of the picture, and judging the picture as a pure black picture if the proportion of the total number of the black pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent.
Further, in the step D2, the method for judging whether the frame is a pure white frame is as follows: and calculating a three-color channel value of each pixel point in the picture, recording the pixel point as a white pixel point if the three-color channel value of the pixel point is more than or equal to 220, counting the white pixel points of all the pixel points of the picture, and judging the picture as a pure white picture if the proportion of the total number of the white pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent. By adopting the method, whether the picture is a pure black picture or a pure white picture can be accurately judged.
In summary, the method for testing the night vision switching performance of the intelligent camera provided by the invention realizes the automation of the control of the ambient light, and automatically detects the picture of the intelligent camera through the self-grinding analysis algorithm to judge whether the picture is in a night vision or non-night vision state. The automatic night vision switching device has the advantages that manual operation is avoided, higher degree of automation is realized, whether a picture is in a night vision state or not is judged automatically, so that whether the test is successful is judged, whether the night vision switching speed of the intelligent camera is not satisfactory or the sensitivity of the intelligent camera to light is not satisfactory can be judged if the test is unsuccessful, and the improvement of the quality of the intelligent camera in the later stage is facilitated.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by 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 (4)
1. A testing method for night vision switching performance of an intelligent camera is characterized by comprising the following steps of: the method comprises the following steps:
s1: placing the intelligent camera and the intelligent bulb to be tested in a darkroom or a closed cassette, networking the intelligent camera and the intelligent bulb, and electrifying, wherein a mobile phone app is connected to a live broadcast picture of the intelligent camera;
s2: controlling the intelligent bulb to be directly turned on and turned off, recording the starting time of the intelligent bulb to be directly turned on and turned off, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture of the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture or a night vision picture, and recording the current time as the final switching time of the night vision picture;
s3: the data processor calculates the time required by night vision picture switching according to the direct on-off starting time and the final night vision picture switching time of the intelligent bulb, compares the time required by night vision picture switching with a preset time threshold, judges that the test is successful if the time required by night vision picture switching is within the preset time threshold range, and judges that the test fails if the time required by night vision picture switching is not within the preset time threshold range;
s4: controlling the intelligent bulb to be gradually opened, transmitting a live broadcast picture to a data processor by the mobile phone app, intercepting the live broadcast picture by the mobile phone app by the data processor, analyzing the screenshot until the analysis result is a non-night vision picture, recording the brightness of the current intelligent bulb, comparing the brightness of the current intelligent bulb with a threshold value of preset brightness, judging that the test is successful if the brightness of the current intelligent bulb is within the threshold value range of the preset brightness, and judging that the test is failed if the brightness of the current intelligent bulb is not within the threshold value range of the preset brightness;
s5: judging whether the preset test times are reached, if the preset test times are not reached, repeating the steps S2 to S4 until the preset test times are reached, counting the success rate of the direct opening and closing tests of the intelligent bulb and the success rate of the gradual opening test of the intelligent bulb, if the success rate of the direct opening and closing tests of the intelligent bulb is smaller than a preset value, judging that the night vision switching speed of the intelligent camera is not in accordance with the requirement, and if the success rate of the gradual opening test of the intelligent bulb is smaller than the preset value, judging that the sensitivity of the intelligent camera to light is not in accordance with the requirement.
2. The method for testing night vision switching performance of an intelligent camera according to claim 1, wherein the method comprises the following steps: in step S2 and step S4, the screenshot is analyzed according to the following steps:
d1: cutting the mobile phone app screenshot, and only reserving a live picture part of the intelligent camera;
d2: judging whether the picture is a pure black picture or a pure white picture, if the picture is the pure black picture or the pure white picture, directly judging the picture as a non-night vision picture or a night vision picture, and if the picture is not the pure black picture or the pure white picture, entering the next step;
d3: calculating three-color channel values of all pixels in a picture, and taking the difference between the maximum value and the minimum value in the three-color channel values of each pixel, if the difference is less than or equal to 15, recording the pixel as a night vision pixel, counting all the pixels of the picture, if the proportion of the total number of the night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as a night vision effect picture, if the difference is greater than 15, recording the pixel as an non-night vision pixel, counting all the pixels of the picture, and if the proportion of the total number of the non-night vision pixels to the number of all the pixels of the picture is greater than or equal to 99%, judging the picture as the non-night vision effect picture.
3. The method for testing night vision switching performance of an intelligent camera according to claim 2, wherein the method comprises the following steps: in the step D2, the method for judging whether the frame is a pure black frame is as follows: and calculating the three-color channel value of each pixel point in the picture, recording the pixel point as a black pixel point if the three-color channel value of the pixel point is less than or equal to 5, carrying out black pixel point statistics on all the pixel points of the picture, and judging the picture as a pure black picture if the proportion of the total number of the black pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent.
4. The method for testing night vision switching performance of an intelligent camera according to claim 2, wherein the method comprises the following steps: in the step D2, the method for judging whether the frame is a pure white frame is as follows: and calculating a three-color channel value of each pixel point in the picture, recording the pixel point as a white pixel point if the three-color channel value of the pixel point is more than or equal to 220, counting the white pixel points of all the pixel points of the picture, and judging the picture as a pure white picture if the proportion of the total number of the white pixel points to the total number of all the pixel points of the picture is more than or equal to 95 percent.
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