Brightness detection method, computer device and readable medium

Abstract

A brightness detection method, computer equipment and readable medium, the brightness detection method comprises: each display module in a display module production line is individually taken as a test module, and the test module is provided with a light sensor (S01); for each test module, a brightness algorithm formula of the light sensor thereof is obtained (S02); and the ambient light is detected through the light sensor according to the brightness algorithm formula (S03). The brightness detection method, computer equipment and readable medium, by individually testing each display module on the display module production line to obtain a set of brightness algorithm formula of the light sensor belonging to itself, effectively avoid the problem of inter-piece difference, and avoid the problem of poor universality of the algorithm formula caused by the performance difference of the light sensor between the pieces; since one display module corresponds to its own set of algorithm formula, without the condition of inter-piece difference, the problem of "zero point" drift is well avoided.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of display, and particularly relates to a brightness detection method and device, a computer device and a readable medium. BACKGROUND

[0002] In the related art, handheld devices such as tablets and mobile phones are equipped with light sensors. The light sensor can automatically adjust the screen brightness of the handheld device according to the ambient light brightness of the handheld device, thereby saving power consumption while providing the best visual effect for the user. However, in the related art, due to the semiconductor characteristics of the light sensor, there are problems of low accuracy, chip-to-chip difference and "zero point" drift. SUMMARY

[0003] Embodiments of the present disclosure provide a brightness detection method, a computer device and a readable medium, which can greatly improve the brightness detection accuracy of the light sensor by improving the brightness algorithm of the light sensor.

[0004] The technical solutions provided by the embodiments of the present disclosure are as follows:

[0005] In one aspect, the embodiments of the present disclosure provide a brightness detection method, comprising:

[0006] Each display module in a display module production line is individually taken as a test module, and the test module is provided with a light sensor;

[0007] For each test module, a brightness algorithm formula of the light sensor thereof is obtained;

[0008] According to the brightness algorithm formula, ambient light detection is performed through the light sensor.

[0009] For each test module, the brightness algorithm of the light sensor is individually obtained, which specifically includes:

[0010] Multiple samplings are performed in a standard illuminance value interval to obtain multiple groups of sampling data, wherein each group of sampling data includes a standard illuminance value Y and a current parameter X fed back by the light sensor under the standard illuminance value Y;

[0011] According to the size of the standard illuminance value Y, the multiple groups of sampling data are divided into a low brightness zone, a medium brightness zone and a high brightness zone;

[0012] Segmented curve fitting is performed according to the sampling data of the low brightness zone, the medium brightness zone and the high brightness zone to obtain a first curve segment corresponding to the sampling data of the low brightness zone, a second curve segment corresponding to the sampling data of the medium brightness zone, and a third curve segment corresponding to the sampling data of the high brightness zone;

[0013] combining the first curve segment, the second curve segment and the third curve segment, a luminance fitting curve is obtained;

[0014] According to the luminance fitting curve, a preliminary luminance algorithm formula is output.

[0015] For example, the multiple sampling in the standard illuminance value interval is to obtain multiple groups of sampling data, wherein each group of the sampling data includes a standard illuminance value Y and a current parameter X fed back by the light sensor under the standard illuminance value Y, and specifically includes:

[0016] The light sensor includes a light-shielded light-shielded sensor and a non-light-shielded non-light-shielded sensor. In each sampling process, the illuminance value Y j as the standard illuminance value Y, and the non-light-shielded current L j of the non-light-shielded sensor and the light-shielded current I j of the light-shielded sensor are collected in real time.

[0017] The difference between the non-light-shielded current L j and the light-shielded current I j is taken as the current parameter X.

[0018] For example, the segmented curve fitting according to the sampling data of the low luminance region, the medium luminance region and the high luminance region obtains a first curve segment corresponding to the sampling data of the low luminance region, a second curve segment corresponding to the sampling data of the medium luminance region, and a third curve segment corresponding to the sampling data of the high luminance region, and specifically includes:

[0019] For the low luminance region, the luminance curve fitting of each group of the sampling data is performed to obtain the first curve segment.

[0020] For the medium luminance region, the luminance curve fitting of multiple groups of the sampling data is performed in intervals to obtain the second curve segment.

[0021] For the high luminance region, the luminance curve fitting of multiple groups of the sampling data is performed in intervals to obtain the third curve segment.

[0022] For example, the luminance curve fitting of multiple groups of the sampling data of the medium luminance region in intervals and / or the luminance curve fitting of multiple groups of the sampling data of the high luminance region in intervals, and specifically includes:

[0023] The change value of the current parameter X between each group of the sampling data is taken as a division fitting standard value D.

[0024] According to the division fitting standard value D, multiple groups of the sampling data are divided in intervals with a set interval step value.

[0025] According to the partition fitting standard value D, a plurality of groups of the sampling data are partitioned with a set interval step value, which specifically includes:

[0026] When D is less than a first threshold value, the interval step value is a first step value;

[0027] When D is greater than or equal to the first threshold value and less than a second threshold value, the interval step value is a second step value;

[0028] When D is greater than or equal to the second threshold value, the interval step value is a third step value;

[0029] Wherein, the first threshold value is less than the second threshold value, the first step value is less than the second step value, and the second step value is less than the third step value.

[0030] Exemplarily, the first threshold value is 1, the second threshold value is 3, the first step value is 0.2, the second step value is 0.5, and the third step value is 1.

[0031] Exemplarily, in the method, when the brightness fitting curve is fitted according to the sampling data, a brightness curve fitting algorithm formula called is a linear equation y a =a+bx, where a and b are to-be-determined parameters, a x is a current parameter X, and y is a standard illuminance value.

[0032] Exemplarily, after the initial version of the brightness algorithm formula is output according to the brightness fitting curve, the method further includes a step of checking the brightness fitting curve and the initial version of the brightness algorithm formula, which specifically includes:

[0033] An R value of a correlation coefficient or a relative error value is obtained when the brightness fitting curve is fitted;

[0034] When the R value of the correlation coefficient is greater than 0.99 or the relative error value is less than or equal to ±20%, it is determined that the brightness fitting curve satisfies an allowable condition, otherwise it is determined that the brightness fitting curve and the initial version of the brightness algorithm formula do not satisfy the allowable condition;

[0035] When the brightness fitting curve and the initial version of the brightness algorithm formula do not satisfy the allowable condition, bad points in a plurality of groups of the sampling data are removed, and / or the value of the interval step value is reduced, and then the brightness curve fitting is performed again until the brightness fitting curve and the initial version of the brightness algorithm formula satisfy the allowable condition.

[0036] ​For example, obtaining the brightness algorithm formula for the light sensor of each of the test modules specifically includes:

[0037] Multiple samples are taken within the standard illuminance value range to obtain multiple sets of sampling data. The light sensor includes a shaded sensor and an unshaded sensor. During each sampling process, the illuminance value Y is collected by the illuminance meter. j And in real time, the initial value L of the unshielded current of the unshielded sensor is collected. j and the initial value I of the light-shielding current of the light-shielding sensor j The initial value L of the unshielded current j Converting the count value to the current parameter X, the illuminance value Y collected by the illuminance meter... j The standard illuminance value Y is defined as follows: each set of sampling data includes the standard illuminance value Y and the initial value L of the unshielded current under the standard illuminance value Y. j and the initial value of the shading current I j ;

[0038] Based on the multiple sets of sampling data, the initial value L of the unshielded current is obtained. j A table showing the correspondence between the standard illuminance value Y and the standard illuminance value Y;

[0039] A brightness fitting curve is obtained by fitting multiple sets of the aforementioned sampling data;

[0040] The initial brightness algorithm formula is obtained based on the brightness fitting curve.

[0041] The initial brightness algorithm formula and the corresponding relationship table are stored as a backup database.

[0042] For example, the step of detecting ambient light using the light sensor according to the brightness algorithm formula specifically includes:

[0043] The real-time unshaded current value L fed back by the light sensor is acquired in real time. j 'and real-time shading current value I j ';

[0044] The real-time unshaded current value L j 'Substitute the current parameter X into the initial brightness algorithm formula in the backup database to obtain the predicted brightness value Y';

[0045] Based on the predicted brightness value Y', the initial value of the shading current I corresponding to the predicted brightness value Y' is retrieved from the corresponding relationship table. j ;

[0046] Calculate the real-time shading current value I j'Compared with the initial value of the light-blocking current I obtained from the query' j The difference Δ is used as the compensation value;

[0047] The real-time unshaded current value L j 'The difference between the compensation value and the target real-time current parameter X';

[0048] The target real-time current parameter X' is substituted into the initial brightness calculation formula as the current parameter X, and the target brightness value is obtained by reporting the point.

[0049] For example, the step of fitting a brightness fitting curve based on multiple sets of sampled data specifically includes: fitting a brightness fitting curve using a polynomial algorithm formula.

[0050] For example, the polynomial algorithm formula is as follows:

[0051] y = a0 + a1x + ... + a k x k ;

[0052] in, x is the current parameter X, and y is the standard illuminance value.

[0053] This disclosure also provides a computer device, including a memory and a processor; the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method described above.

[0054] This disclosure also provides a computer-readable medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method described above.

[0055] The beneficial effects of the embodiments disclosed herein are as follows:

[0056] This disclosure provides a brightness detection method, computer device, and readable medium. By individually testing each display module on the display module production line to obtain its own set of brightness algorithm formulas for light sensors, the inter-module difference problem can be effectively avoided. This avoids the problem of poor universality of algorithm formulas caused by the inconsistency of light sensor performance between different display modules, i.e., the difference in light sensor performance between modules. Furthermore, since each display module corresponds to its own set of algorithm formulas, the condition of inter-module difference is not required, which can effectively avoid the problem of "zero point" drift. Attached Figure Description

[0057] Figure 1 A flowchart illustrating the brightness detection method provided in this embodiment of the present disclosure;

[0058] Figure 2A flow chart representing the luminance detection method in an embodiment provided by the present disclosure;

[0059] Figure 3 A flow comparison chart of the luminance algorithm scheme in the related art and the luminance detection method provided by an embodiment of the present disclosure;

[0060] Figure 4 A comparison chart of the accuracy of the luminance algorithm formula of a display module in the related art and the luminance detection method provided by an embodiment of the present disclosure;

[0061] Figure 5 A comparison chart of the accuracy of the luminance algorithm formula of another display module in the related art and the luminance detection method provided by an embodiment of the present disclosure;

[0062] Figure 6 A flow chart representing the luminance detection method in an embodiment provided by the present disclosure;

[0063] Figure 7 A flow chart representing Figure 6 A flow chart representing the luminance algorithm in the callback calibration process in the embodiment shown;

[0064] Figure 8 A comparison chart of the accuracy of the luminance algorithm in the related art and the method in another embodiment of the present disclosure. DETAILED DESCRIPTION

[0065] In order to make the objectives, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by those of ordinary skill in the art without any creative effort fall within the scope of protection of the present disclosure.

[0066] Unless otherwise defined, technical terms and scientific terms used in the present disclosure shall have the same meaning as commonly understood by one of ordinary skill in the art to which this present disclosure belongs. Unless otherwise defined, technical terms and scientific terms used in the present disclosure shall have the same meaning as commonly understood by one of ordinary skill in the art to which this present disclosure belongs. The terms "first", "second" and similar terms in the present disclosure do not denote any order, quantity, or importance, but are used to distinguish different components. Similarly, the terms "one", "a" or "the" and similar terms do not denote a quantity of limitation, but denote the presence of at least one. The terms "include" or "contain" and similar terms mean that the elements or objects before the term encompass the elements or objects listed after the term and their equivalents, and do not exclude other elements or objects. The terms "connected" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0067] Before the brightness detection method, computer device and readable medium provided by the embodiments of the present disclosure are described in detail, it is necessary to make the following description of the related art:

[0068] In the related art, many handheld devices (such as tablets and mobile phones) are equipped with light sensors. The light sensor can detect the ambient light brightness of the handheld device, and the handheld device can automatically adjust the screen brightness according to the detected ambient light brightness, saving energy consumption while providing the best visual effect for the user.

[0069] Based on the necessity of ambient light sensing, integrating a light sensor on a display module can save costs and facilitate the realization of a full-screen display, increasing the competitiveness of display products. The basic principle of ambient light detection by a light sensor is based on the photosensitive characteristics of the light sensor. Under different light irradiation, the carrier transition state in the PN junction of the light sensor is different. By detecting the output current size of the PN junction, the current ambient light brightness can be calculated.

[0070] However, in the related art, the light sensor uses a TFT (Thin Film Transistor) device. Due to its semiconductor characteristics, the following problems are difficult to solve:

[0071] (1) Inter-chip difference:

[0072] In the related art, the display module production line is through the sampling of several display modules, the luminance algorithm of the several display modules is established, and the algorithm is applied to the display modules which are not sampled. However, the process difference of the light sensor in the display module will cause the inter-chip difference between the performances of the light sensor, that is, the performances of the light sensor between different display modules are different. For the TFT device, if the TFT device is a display TFT, the difference is within the Spec (standard) range, but for the photosensitive performance of the light sensor, such difference will affect the applicability of the luminance calculation formula on each module;

[0073] (2) "zero point" drift:

[0074] In the related art, the luminance algorithm of the light sensor needs to remove the inter-chip difference and calibrate the "zero point" according to the difference between the light shielding current and the non-light shielding current of each display module in the Dark state (dark state). However, the data feedback light sensor tested in the related art has the problem of "zero point" drift, that is, the difference between the non-light shielding current and the light shielding current obtained in the Dark state of the same display module is unstable each time.

[0075] In order to solve the above problems, the present disclosure provides a luminance detection method, a computer device and a readable medium, which can greatly improve the luminance detection accuracy of the light sensor by improving the luminance algorithm of the light sensor.

[0076] The luminance detection method provided by the present disclosure comprises the following steps:

[0077] Step S01, each display module in the display module production line is individually taken as a test module, and the test module is provided with a light sensor;

[0078] The light sensor can be integrated on the display module.

[0079] Step S02, for each test module, the luminance algorithm formula of the light sensor thereof is obtained;

[0080] That is, a corresponding luminance algorithm formula belonging to each test module is individually established;

[0081] Step S03, according to the luminance algorithm formula, the ambient light is detected by the light sensor.

[0082] Step S01 and step S02 can be completed on the display module production line, and the luminance algorithm formula is stored in the display module after being obtained. Step S03 can be performed when the client is used. The light sensor detects the ambient light brightness according to the luminance algorithm formula to achieve the purpose of automatically adjusting the screen brightness.

[0083] The above scheme, by testing each display module on the display module production line to obtain a set of luminance algorithm formula of the light sensor belonging to itself, so that even if there are differences between the light sensors in different display modules, since each display module has its own corresponding set of luminance algorithm formula, the inter-piece difference problem can be effectively avoided, and the problem of poor universality of the algorithm formula caused by inconsistent performance of the light sensor between pieces can be avoided.

[0084] Moreover, the reason for the "zero point" drift problem is that in the related art, the luminance algorithm of the light sensor needs to remove the inter-piece difference according to the difference between the light shielding current and the unshielded current of each display module in the Dark state (dark state), that is, to calibrate the "zero point". However, when calibrating the "zero point" for each test module, for a single test module, due to the drift of its semiconductor characteristics, the mathematical relationship between the unshielded current X and the illumination value Y of each test feedback changes, the current is unstable, that is, there is a "zero point" drift problem. However, in the luminance detection method provided by the embodiments of the present disclosure, each display module is equipped with its own set of luminance algorithm formula, and there is no need to remove the inter-piece difference, that is, there is no need to calibrate the "zero point" for the inter-piece difference, so the influence of the "zero point" drift in the related art can be avoided.

[0085] In addition, in the related art, the luminance algorithm of the light sensor does not support the luminance calculation of the high brightness area (for example, the luminance area with a light intensity of 10001-3000 LUX), and the accuracy of the low brightness area (for example, the luminance area with a light intensity of 0-20 LUX) and the medium brightness area (for example, the luminance area with a light intensity of 21-10000 LUX) is difficult to control within ±20%. In this way, because the light sensor is usually a TFT device, its semiconductor characteristics cause it to be too sensitive in the low brightness area and too insensitive in the high brightness area, which further leads to the fact that neither the low brightness area nor the high brightness area is suitable for the existing luminance algorithm, thereby directly affecting the accuracy of the luminance detection. Therefore, in order to further solve the problem that the luminance algorithm of the light sensor in the display module in the related art is not suitable for low brightness and high brightness luminance detection, resulting in low accuracy of the luminance detection, the luminance detection method provided in some embodiments of the present disclosure can also be applicable to the low brightness area and the high brightness area, thereby improving the accuracy.

[0086] As shown in Figure 1 the luminance detection method provided by some embodiments of the present disclosure can specifically include the following steps:

[0087] Step S01, each display module in the display module production line is individually taken as a test module, and the test module is provided with a light sensor;

[0088] Step S02, for each test module, obtaining the brightness algorithm formula of the light sensor thereof;

[0089] Step S03, detecting the ambient light through the light sensor according to the brightness algorithm formula.

[0090] For example, the step S02 specifically includes the following steps:

[0091] Step S021, sampling multiple times in a standard illuminance value interval to obtain multiple groups of sampling data, wherein each group of sampling data includes a standard illuminance value Y and a current parameter X fed back by the light sensor under the standard illuminance value Y;

[0092] Step S022, dividing the multiple groups of sampling data into a low brightness area, a medium brightness area and a high brightness area according to the size of the standard illuminance value Y;

[0093] Step S023, performing piecewise curve fitting according to the sampling data of the low brightness area, the medium brightness area and the high brightness area to obtain a first curve segment corresponding to the sampling data of the low brightness area, a second curve segment corresponding to the sampling data of the medium brightness area, and a third curve segment corresponding to the sampling data of the high brightness area;

[0094] Step S024, combining the first curve segment, the second curve segment and the third curve segment to obtain a brightness fitting curve, and outputting a preliminary version of the brightness algorithm formula according to the brightness fitting curve.

[0095] In the above scheme, current sampling is performed on the test module under different illuminance values to obtain multiple groups of sampling data; then the multiple groups of sampling data are grouped into a low brightness area, a medium brightness area and a high brightness area according to the size of the illuminance value, for example, the illuminance of the low brightness area is between (0-20) LUX, the illuminance of the medium brightness area is between (21-10000) LUX, and the illuminance of the high brightness area is between (10001-30000) LUX. The brightness curve fitting is performed separately for the low brightness area, the medium brightness area and the high brightness area, that is, the brightness curve is fitted in sections, so that the accuracy of the brightness algorithm of the low brightness area and the high brightness area is greatly improved.

[0096] It should be noted that in step S021, the standard illuminance value Y of the light sensor on the test module can be collected by an illuminometer and uploaded to the upper computer detection system. The light sensor outputs a current signal to the upper computer detection system in real time at different standard illuminance values Y to obtain the corresponding current parameter X under different standard illuminance values Y.

[0097] For example, step S021 specifically includes:

[0098] The light sensor includes a shaded light sensor and an unshaded light sensor, and in each sampling process, the illuminance value Y is collected by the illuminometer j As the standard illuminance value Y, and the unshaded current L of the unshaded light sensor is collected in real time j And the shaded current I of the shaded light sensor j ;

[0099] The difference X between the unshaded current L j And the shaded current I j j As the current parameter X.

[0100] In the above scheme, the light sensor can be designed by two groups of TFT sensors, one group of TFT is designed as a shaded light sensor (for example, the shaded light sensor can be blocked by a black matrix), which can be used as a reference group TFT, and the output current I j To the host computer detection system; the other group is designed as an unshaded light sensor, which is used as a light sensing group TFT, and the output current L j To the host computer detection system.

[0101] Wherein, the standard illuminance value interval can refer to a full illuminance value interval covering low brightness value, medium brightness value and high brightness value. In multiple sampling, the standard illuminometer value Y of the light sensor on the test module is collected by the illuminometer j To the host computer detection system, in order to ensure the accuracy and application range of the subsequent fitting formula, in some embodiments, the standard illuminance value interval can be between 0 and 30000LUX, and the sampling number can be 100, so as to obtain the current parameter X value corresponding to 100 sampling LUX of the standard illuminance value between 0 and 30000LUX. For example, the standard illuminance value is in the interval of 0-20LUX, and 20 sampling is performed to obtain 20 current parameters X values; the standard illuminance value is in the interval of 21-1000LUX, and 60 sampling is performed to obtain 60 current parameters X values; the standard illuminance value is in the interval of 1001-10000LUX, and 10 sampling is performed to obtain 10 current parameters X values; the standard illuminance value is in the interval of 10001-30000LUX, and 10 sampling is performed to obtain 10 current parameters X values.

[0102] Of course, it can be understood that the above is only an example, and the above is only an example of the division of the size interval of the standard illuminance value and the sampling number in each interval. In actual application, the interval division of the standard illuminance value and the sampling number in each interval are not limited to this.

[0103] And due to the semiconductor characteristics of the light sensor, there will be characteristic drift, and in the above embodiments, the unshaded current L j ​With the light-blocking current I j The difference is used as the current parameter X value for subsequent curve fitting and brightness calculation, which can reduce the characteristic drift caused by the semiconductor characteristics of the light sensor.

[0104] It should be noted that, in some other embodiments, the current parameter X may also be the unshielded current L. j The unshielded current L j and the light-blocking current I j The difference is used as the current parameter X, compared to using the unshielded current L. j As a current parameter X, the characteristic drift effect is smaller, resulting in higher brightness detection accuracy.

[0105] For example, step S023 above specifically includes the following steps:

[0106] For the low-brightness area, a brightness curve is fitted to each set of the sampled data to obtain a first curve segment; for the medium-brightness area, a brightness curve is fitted to multiple sets of the sampled data in intervals to obtain a second curve segment; for the high-brightness area, a brightness curve is fitted to multiple sets of the sampled data in intervals to obtain a third curve segment.

[0107] In the above scheme, the light sensor is relatively sensitive in the low-brightness area and changes slowly in the high-brightness area. Multiple sets of sampled data can be grouped according to the standard illuminance value into low-brightness, medium-brightness, and high-brightness areas. The low-brightness area can be fitted with a brightness curve separately. Preferredly, brightness curve fitting can be performed on each set of sampled data in the low-brightness area. That is, when fitting the brightness curve in the low-brightness area, it is refined to each set of sampled data corresponding to a brightness formula for curve fitting, so as to better ensure the accuracy of the brightness curve in the low-brightness area.

[0108] For the sampling data in the medium and high brightness areas, interval fitting can be performed. For details, please refer to... Figure 2 As shown, exemplarily, step S023 above may include:

[0109] For the medium brightness region and the high brightness region, the change value of the current parameter X between each group of the sampled data is... The partition fitting standard value D is used as the partition fitting standard value D. Based on the partition fitting standard value D, the multiple sets of sampled data are partitioned with a set interval step value.

[0110] In the above scheme, the medium brightness area and the high brightness area can both be partitioned according to the D value, that is, the D value is equal to the change in the current difference between each group of sampled data: The D value is used as a partition fitting criterion, and different step lengths are applied for fitting between partitions according to the size of the D value.

[0111] For example, when the D value is less than a first threshold value, the interval step length value is a first step length value; when the D value is greater than or equal to the first threshold value and less than a second threshold value, the interval step length value is a second step length value; and when the D value is greater than or equal to the second threshold value, the interval step length value is a third step length value; wherein the first threshold value is less than the second threshold value, the first step length value is less than the second step length value, and the second step length value is less than the third step length value.

[0112] For example, the first threshold value is 1, the second threshold value is 3, the first step length value is 0.2, the second step length value is 0.5, and the third step length value is 1.

[0113] In the above scheme, the entire standard illuminance value interval is segmented for luminance curve fitting. When fitting between partitions in the medium luminance region and the high luminance region, the size of the D value and the selection of the step length can be: when D < 1, 0.2 / Step; when 1 ≤ D < 3, 0.5 / Step; and when D ≥ 3, 1 / Step. This partition fitting scheme can ensure the accuracy of the luminance curve fitting in the medium luminance region and the high luminance region. It should be understood that the above selection of the size of the D value and the step length is an example embodiment, which can be obtained according to the experience value of the luminance algorithm fitting. In other embodiments, the selection of the size of the D value and the step length is not limited to this.

[0114] In addition, in step S024, the method, the luminance fitting curve is fitted according to the sampling data, and the formula of the luminance curve fitting algorithm called is y a = a + bx, wherein a and b are both undetermined parameters, X is the current parameter X, and y a is the standard illuminance value.

[0115] In the above scheme, according to the partition of the low luminance region, the medium luminance region, and the high luminance region, the luminance curve fitting algorithm is called to fit the luminance curve according to the collected illuminometer Y value and current parameter X value. The mathematical basis of the luminance curve fitting algorithm is that the sum of squared deviations between actual values and trend values is minimum, that is, the least squares method, and the luminance curve is fitted according to this algorithm.

[0116] Specifically, assuming that the linear equation is y a = a + bx, wherein a and b are both undetermined parameters. Given the independent variable x, the estimated dependent variable y can be obtained by substituting the above equation. The dependent variable y is not a certain number, but a possible value, which is the average of multiple y. Therefore, y aWhen x takes a certain value, y has multiple possible values. Therefore, the value of y obtained after substituting a given independent variable x value into the equation can be regarded as an average or expected value.

[0117] The specific method of fitting the linear equation is as follows:

[0118] Q = ∑(y-y a ) 2 = minimum value (I)

[0119] Substitute the linear equation y a = a + bx into equation (I):

[0120] Q = ∑(y-a-bx) 2 = minimum value (II)

[0121] Take the partial derivative of Q with respect to a and the partial derivative of Q with respect to b, respectively, and set them equal to 0:

[0122]

[0123] After rearranging equation (III), the following system of equations is obtained:

[0124]

[0125] Substitute the known x and y into equation (IV) to obtain the two parameters a and b:

[0126]

[0127] In the brightness fitting, the independent variable x is the current parameter X, which is the difference between the unshielded current L j and the shielded current I j ; the dependent variable y is the standard illuminance value Y.

[0128] The above scheme uses the difference between the unshielded current L j and the shielded current I j as the independent variable x in the formula, which can avoid errors caused by characteristic drift to a certain extent and greatly improve accuracy to ensure the accuracy of the brightness detection of the photosensitive unit.

[0129] For example, referring to Figure 2 , the method further includes, after step S024, a step S025 of verifying the brightness fitting curve and the preliminary brightness algorithm formula.

[0130] Please refer to Figure 2 , step S025 can specifically include:

[0131] Obtain the correlation coefficient R value or calculate the relative error value during fitting of the brightness fitting curve.

[0132] When the correlation coefficient R value is greater than 0.99 or the relative error value is less than or equal to ±20%, it is judged that the luminance fitting curve meets the allowable condition, otherwise it is judged that the luminance fitting curve and the preliminary version luminance algorithm formula do not meet the allowable condition.

[0133] When the luminance fitting curve and the preliminary version luminance algorithm formula do not meet the allowable condition, remove bad points in multiple groups of sampling data and / or reduce the value of the interval step value (i.e. further refine the partition), and then re-perform the luminance curve fitting until the luminance fitting curve and the preliminary version luminance algorithm formula meet the allowable condition, and output the final luminance algorithm formula.

[0134] In the above scheme, the correlation coefficient R value can be obtained at the same time as the luminance curve fitting; or the relative error is calculated, when R>0.99 or the accuracy is ≤±20%, it is judged to meet the Spec (allowable range) standard, and the preliminary version luminance algorithm formula can be output, and the FW is burned into the display module; when the Spec standard is not met, the preliminary version luminance algorithm formula needs to be corrected. If there is a single bad point, the bad point can be removed; if there is a segmented trend, the interval is refined in the existing interval to re-perform the algorithm formula fitting until the Spec standard is met. In this way, by checking the preliminary version luminance algorithm formula and setting the Spec standard, the luminance algorithm accuracy is greatly improved.

[0135] Figure 3 The figure shows the flow comparison of the luminance algorithm scheme in the related art and the luminance detection method provided by the embodiment of the present disclosure, wherein (a) shows the flowchart of the luminance algorithm scheme in the related art; (b) shows the flowchart of the luminance detection method provided by the embodiment of the present disclosure.

[0136] As shown in (a), the acquisition stage flow of the luminance algorithm formula in the related art is as follows: Figure 3 (a) shows the acquisition stage flow of the luminance algorithm formula in the related art is as follows:

[0137] Step S1, in the display module production line, the luminance algorithm fitting is performed in the laboratory:

[0138] Among them, at least 10 display modules are selected as test modules, and multiple groups of sampling data are obtained by sampling multiple times under different luminance environments, and the electronic spreadsheet algorithm (such as the least square method) is called to fit the curve according to the multiple groups of sampling data;

[0139] Step S2, remove inter-panel differences:

[0140] Among them, a dark environment is created on the display module production line, and the difference between the light shielding current and the unshielded current data of the light sensor is collected to remove the inter-panel difference;

[0141] Step S3, generating the FW:

[0142] Wherein after removing the inter-chip difference, the luminance algorithm formula is obtained according to the fitting curve, and the luminance algorithm formula is burned into each display module.

[0143] As shown in Figure 3 (b), the acquisition stage of the luminance algorithm formula in the luminance detection method provided by the embodiment of the present disclosure is as follows:

[0144] In the production line, sampling data is collected at different luminance values for each display module;

[0145] The host computer processes the sampling data, calls the luminance curve fitting algorithm to perform luminance curve fitting, and obtains a preliminary luminance algorithm formula according to the luminance curve;

[0146] The luminance algorithm formula obtained after the preliminary luminance algorithm formula is verified is burned into the display module.

[0147] As shown in Figure 3 The acquisition stage (i.e., step S02) of the luminance algorithm formula of the display module in the method provided by the embodiment and the luminance algorithm formula of the display module in related technologies is completed before the display module is output in the display module production line. In combination with Figure 3 and the above content, it can be known that the luminance detection method provided by the embodiment of the present disclosure saves the laboratory step compared with the luminance algorithm of the light sensor in related technologies.

[0148] Figure 4 As shown in the figure, the accuracy comparison between the luminance algorithm formula of a display module in related technologies and the luminance algorithm formula in the luminance detection method provided by the embodiment of the present disclosure, wherein the abscissa is the standard illuminance value, the ordinate is the relative error value, the a curve is the relative error value curve of the luminance algorithm formula in related technologies, and the b curve is the relative error value curve of the luminance algorithm formula in the method provided by the embodiment.

[0149] Figure 5 As shown in the figure, the accuracy comparison between the luminance algorithm formula of a display module in related technologies and the luminance algorithm formula in the luminance detection method provided by the embodiment of the present disclosure, wherein the abscissa is the standard illuminance value, the ordinate is the relative error value, the c curve is the relative error value curve of the luminance algorithm formula in related technologies, and the d curve is the relative error value curve of the luminance algorithm formula in the method provided by the embodiment.

[0150] In combination with Figure 4 and Figure 5 It can be known that the luminance detection method provided by the embodiment of the present disclosure can greatly improve the luminance detection accuracy compared with the luminance algorithm of the light sensor in related technologies.

[0151] In addition, in the above embodiment, the sampling data is divided into different zones according to the size of the standard illuminance value, and the brightness curve fitting is performed in different zones to obtain the initial brightness algorithm formula. In this way, the brightness curve fitting is performed for the data in different zones, and the brightness curve fitting algorithm formula is relatively complicated in different zones. If the display module has a jump point, the limited sampling data will be removed as a bad point, resulting in inaccurate fitting results.

[0152] To improve the above problems, the present disclosure further provides a brightness detection method in some embodiments, which uses polynomial fitting to describe the brightness, avoiding using multiple straight lines to fit the relationship in the entire standard illuminance interval, and eliminating the segmentation process, so that the algorithm fitting is more concise and does not need to consider the connection problem of the segmentation points. The following will be described in more detail.

[0153] In this embodiment, the brightness detection method comprises the following steps:

[0154] Step S01, each display module in the display module production line is taken as a test module, and the test module is provided with a light sensor;

[0155] The light sensor can be integrated on the display module.

[0156] Step S02, for each test module, the brightness algorithm formula of the light sensor thereof is obtained;

[0157] That is, the corresponding brightness algorithm formula of each test module is established separately;

[0158] Step S03, detecting the ambient light through the light sensor according to the brightness algorithm formula.

[0159] Figure 6 The flowchart of the brightness detection method in this embodiment is shown.

[0160] Please refer to Figure 6 In this embodiment, the above step S02 can specifically comprise the following steps:

[0161] Step S021', sampling multiple times in the standard illuminance value interval to obtain multiple groups of sampling data, wherein the light sensor comprises a light-shielded light-shielded sensor and a non-light-shielded non-light-shielded sensor, and in each sampling process, the illuminance value Y j is collected by an illuminometer, and the non-light-shielded initial current L j of the non-light-shielded sensor and the light-shielded initial current I j of the light-shielded sensor are collected in real time. jconverting the current parameter X into a count value, the illuminometer acquiring an illuminance value Y j For the standard illuminance value Y, each set of the sampling data includes a standard illuminance value Y and a corresponding unshaded current initial value L under the standard illuminance value Y j and a shaded current initial value I j ;

[0162] Step S022', according to the multiple sets of the sampling data, obtaining a corresponding relationship table of the corresponding relationship between the unshaded current initial value L j and the standard illuminance value Y;

[0163] Step S023', fitting a brightness fitting curve according to the multiple sets of the sampling data;

[0164] Step S024', obtaining a preliminary brightness algorithm formula according to the brightness fitting curve;

[0165] Step S025', storing the preliminary brightness algorithm formula and the corresponding relationship table as a backup database.

[0166] Exemplarily, the step S03 can specifically include:

[0167] Step S031, obtaining a real-time unshaded current value L j ' and a real-time shaded current value I j ' fed back by the light sensor in real time;

[0168] Step S032, substituting the real-time unshaded current value L j ' as the current parameter X into the preliminary brightness algorithm formula in the backup database to obtain a predicted brightness value Y';

[0169] Step S033, according to the predicted brightness value Y', querying the corresponding shaded current initial value I j corresponding to the predicted brightness value Y' in the corresponding relationship table;

[0170] Step S034, calculating a difference value Δ between the real-time shaded current value I j ' and the queried shaded current initial value I j as a compensation value;

[0171] Step S035, taking a difference value between the real-time unshaded current value L j ' and the compensation value as a target real-time current parameter X';

[0172] Step S036, substituting the target real-time current parameter X' as the current parameter X into the preliminary brightness calculation formula to obtain a target brightness value.

[0173] In the above scheme, multiple sets of sampling data can be fitted without partitioning, and a single fitting formula is applied to the multiple sets of sampling data in the entire standard illuminance value interval for luminance curve fitting, without calling different formulas for multi-segment curve fitting, simplifying the curve fitting process, thereby avoiding the complexity of segmented fitting and the errors caused by the segmented process. The improved algorithm has high accuracy and a wider range of applications.

[0174] Moreover, in step S03, a callback calibration scheme is sampled in the display module use stage. The flow of the specific callback calibration process is as shown in Figure 7 : multiple sets of sampling data are stored during the sampling process on the production line; in actual use of the client, a predicted luminance value Y' is obtained by substituting the collected real-time unshaded current value into the formula, the corresponding shading initial value is found in the stored multiple sets of sampling data according to the predicted luminance value Y', the difference between the collected real-time shading value and the shading initial value is taken as the Δ value, the real-time unshaded value is updated by applying the Δ value, and the updated real-time unshaded value is substituted into the initial version of the luminance algorithm formula to calculate the target luminance value Y. Thus, there is a callback calibration scheme. Since the light sensor itself on each display module has semiconductor characteristics that cause it to have a characteristic drift problem, the above callback calibration scheme can be used to calibrate the difference between the real-time shading current value and the shading current initial value stored in the predicted luminance value, so as to compensate for the drift value, thereby solving the problem of characteristic drift of the light sensor itself.

[0175] It should be noted that in step S021', in the data sampling process, the light sensor can be designed by two sets of TFT sensors, one set of TFT is designed as a shaded shading sensor (for example, the shading sensor can be blocked by a black matrix), which can be used as a reference group TFT, and outputs the current I j to the host computer detection system; the other set is designed as an unshaded unshaded sensor, which is used as a light sensing group TFT, and outputs the current L j to the host computer detection system.

[0176] The standard illuminance value interval can refer to an illuminance value interval covering low luminance values, medium luminance values, and high luminance values. In multiple sampling, the standard illuminance meter value Y j of the light sensor on the test module is collected by the illuminance meter and input to the host computer detection system. To ensure the accuracy and application range of the subsequent fitting formula, in some embodiments, the standard illuminance value interval can be between 0 and 30000 LUX, and the sampling number can be 100, so as to obtain the current parameter X value corresponding to 100 LUX in the illuminance value between 0 and 30000 LUX. The unshaded current value, i.e., the unshaded current initial value L j is taken as the X value for subsequent calculation. Moreover, the unshaded current values L in the 100 sets of sampling data need to be stored.j to call when making a predictive callback during subsequent use.

[0177] In addition, in the embodiment, the luminance fitting curve is fitted according to the multiple sets of sampling data, and specifically, the luminance fitting curve can be fitted by using a polynomial algorithm formula.

[0178] Specifically, the un-shielded light current initial value is taken as X, the luminance collected by the illuminometer is taken as Y, the luminance fitting is performed according to the collected multiple sets of sampling data, the fitting curve is selected according to the principle of minimum deviation square sum, and the polynomial equation is taken as the luminance curve fitting formula, which is called the least square method.

[0179] The specific derivation process of the polynomial algorithm formula is as follows:

[0180] Suppose the fitting polynomial is: y=a0+a1x+…+a k x k (I’);

[0181] The sum of the distances of each point to the curve, i.e., the deviation square sum, is:

[0182]

[0183] The partial derivative of the right side of equation (II’) with respect to a i is obtained, and equation (II’) is simplified into the form of a matrix, and the following Vandermonde matrix is obtained:

[0184]

[0185] After simplifying the above formula (III’), the following formula is obtained:

[0186]

[0187] That is, X·A=Y, then A=(X′·X) -1 ·(X′·Y), so that the coefficient matrix A is obtained, and the luminance fitting curve is obtained.

[0188] In an exemplary embodiment, the luminance curve fitting formula can be selected as a quintic formula, which can be as follows:

[0189] Y=A·E-30*X 5 -B·E-25*X 4 +C·E-20*X 3 -D·E-15*X 2 +F·E5*X-G·E8

[0190] or

[0191] Y = A·E-25*X 5 -B·E-20*X 4 +C·E-15*X 3 -D·E-10*X 2 +F·E5*X-G·E8

[0192] wherein the specific values of the coefficients A, B, C, D, E, F and G need to ensure the accuracy of 25 digits after the decimal point, for example, in an exemplary embodiment, the quintic formula can be:

[0193] Y = 3.69739288898211E-15*X 5 -5.14282149625985E-10*X 4 +0.0000286067944720879*X 3 -0.795339546546083*X 2 +11051.0866402269*X-61387251.952073

[0194] Figure 8 is a schematic diagram of the luminance curve corresponding to the entire standard illuminance value range fitted by the quintic formula described above in an embodiment, wherein the abscissa is the reported luminance value, and the ordinate is the standard illuminance value collected by the illuminometer, and the e curve in the figure is the curve obtained by the luminance algorithm in the related art, and the f curve is the curve obtained by the luminance detection method provided in the embodiment. It can be seen from Figure 8 that the luminance detection method provided in the embodiment can effectively improve the accuracy.

[0195] In addition, it needs to be explained that in the embodiment, the initial version of the luminance algorithm formula and the sampling data are stored in the host computer, and the hardware support thereof can be as follows:

[0196] The data can be integrated in TDDI (Touch and Display Driver Integration, touch and display driver integration), and the main storage module position and specification of TDDI can be as shown in the figure. Taking the COG (chip on glass, chip bonded on substrate) package of TDDI as an example, the driving circuit (IC) is located on the display panel, the Flash is on the FPC (flexible circuit board) or PCB (printed circuit board), and the RAM and Flash are both storage modules, including the coefficients of the luminance curve fitting formula, the initial version of the luminance algorithm formula and the sampling data, etc. The role of the MCU (Microcontroller Unit, microcontroller unit) is mainly to calculate and read the data in the storage module, and the MCU and the RAM can be integrated in the TDDI.

[0197] In addition, it should be noted that, as shown in Figure 6 and Figure 7 In the embodiment, the process of curve fitting of the multiple sets of sampling data to obtain the brightness curve and storing the preliminary brightness algorithm formula, etc. (i.e., step S02) can be completed by the production line before the display module is shipped. The recall calibration process can be completed when the brightness is detected in the actual application of the customer.

[0198] In summary, the brightness detection method provided by the embodiment can apply a single formula to all brightness intervals and add a recall calibration mechanism, which can avoid the problems of zero drift, inter-chip difference and low accuracy caused by semiconductor characteristics, and make the brightness algorithm fitting simple and convenient.

[0199] In addition, the disclosure embodiment further provides a computer device, comprising a memory and a processor; the memory stores a computer program which can run on the processor; when the processor executes the computer program, the method as described above is realized.

[0200] In addition, the disclosure embodiment further provides a computer readable medium which stores a computer program, characterized in that the computer program is executed by the processor to realize the method as described above.

[0201] The following points need to be explained:

[0202] (1) The drawings of the disclosure embodiment only involve the structures involved in the disclosure embodiment, and other structures can be referred to the usual design.

[0203] (2) For the sake of clarity, in the drawings used to describe the embodiments of the disclosure, the thickness of the layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual proportion. It can be understood that when an element such as a layer, film, region or substrate is referred to as being located "on" or "under" another element, the element can be "directly" located on or under another element or there can be an intermediate element.

[0204] (3) In the case of no conflict, the embodiments of the disclosure and the features in the embodiments can be combined with each other to obtain new embodiments.

[0205] The above is only a specific embodiment of the disclosure, but the protection scope of the disclosure is not limited thereto, and the protection scope of the disclosure should be subject to the protection scope of the claims.

Claims

1. A luminance detection method characterized by, The method comprises the steps of: including: Each display module in the display module production line is individually taken as a test module, and the test module is provided with a light sensor; For each test module, the brightness algorithm formula of the light sensor thereof is obtained; According to the brightness algorithm formula, the ambient light is detected through the light sensor; The brightness algorithm of the light sensor is individually obtained for each test module, specifically including: Multiple sampling is performed in a standard illuminance value interval to obtain multiple groups of sampling data, wherein each group of sampling data includes a standard illuminance value Y and a current parameter X fed back by the light sensor under the standard illuminance value Y; According to the size of the standard illuminance value Y, the multiple groups of sampling data are divided into a low brightness area, a medium brightness area and a high brightness area; According to the sampling data of the low brightness area, the medium brightness area and the high brightness area, segmented curve fitting is performed to obtain a first curve segment corresponding to the sampling data of the low brightness area, a second curve segment corresponding to the sampling data of the medium brightness area, and a third curve segment corresponding to the sampling data of the high brightness area; The first curve segment, the second curve segment and the third curve segment are combined to obtain a brightness fitting curve; 2. The method of claim 1, wherein, According to the brightness fitting curve, an initial version of the brightness algorithm formula is output. The light sensing sensor comprises a shaded light sensor and an unshaded light sensor, and in each sampling process, the illumination value Y is collected by the luxmeter j As the standard illumination value Y, and the unshaded light current of the unshaded light sensor is collected in real time And the shaded light current of the shaded light sensor ; The difference between the unshaded current and the shaded current is taken as the current parameter X.

3. The method of claim 2, wherein, The multiple sampling in the standard illuminance value interval to obtain multiple groups of sampling data, wherein each group of sampling data includes a standard illuminance value Y and a current parameter X fed back by the light sensor under the standard illuminance value Y, specifically includes: The segmented curve fitting according to the sampling data of the low brightness area, the medium brightness area and the high brightness area to obtain the first curve segment corresponding to the sampling data of the low brightness area, the second curve segment corresponding to the sampling data of the medium brightness area, and the third curve segment corresponding to the sampling data of the high brightness area, specifically includes: For the low brightness area, each group of sampling data is subjected to brightness curve fitting to obtain a first curve segment; For the medium brightness area, the multiple groups of sampling data are subjected to brightness curve fitting in intervals to obtain a second curve segment; 4. The method of claim 3, wherein, For the high brightness area, the multiple groups of sampling data are subjected to brightness curve fitting in intervals to obtain a third curve segment. the change value of the current parameter X between each set of the sampling data as a partition fitting criterion value D; The brightness curve fitting of the multiple groups of sampling data in the medium brightness area in intervals and / or the brightness curve fitting of the multiple groups of sampling data in the high brightness area in intervals, specifically includes:

5. The method of claim 4, wherein, According to the interval fitting standard value D, the multiple groups of sampling data are divided into intervals at a set interval step value. According to the interval fitting standard value D, the multiple groups of sampling data are divided into intervals at a set interval step value, specifically including: When D is less than a first threshold value, the interval step value is a first step value; When D is greater than or equal to the first threshold value and less than a second threshold value, the interval step value is a second step value; When D is greater than or equal to the second threshold value, the interval step value is a third step value; Wherein, the first threshold value is less than the second threshold value, the first step value is less than the second step value, and the second step value is less than the third step value.

6. The method of claim 5, wherein, The first threshold value is 1, the second threshold value is 3; the first step value is 0.2, the second step value is 0.5, and the third step value is 1.

7. The method of claim 1, wherein, In the method, a formula of a brightness curve fitting algorithm called when brightness fitting curve is performed according to the sampling data is a straight line equation , wherein a and b are both undetermined parameters, , x is a current parameter X, y a is a standard illuminance value calculated by the formula of the brightness curve fitting algorithm, n represents a number of sampling data points participating in fitting, and y represents an actually measured standard illuminance value.

8. The method of claim 4, wherein, After outputting the preliminary brightness algorithm formula according to the brightness fitting curve, the method further comprises a step of checking the brightness fitting curve and the preliminary brightness algorithm formula, which specifically comprises: acquiring a correlation coefficient R value or calculating a relative error value during fitting of the brightness fitting curve; when the correlation coefficient R value is greater than 0.99 or the relative error value is less than or equal to ±20%, it is determined that the brightness fitting curve meets the allowable condition, otherwise it is determined that the brightness fitting curve and the preliminary brightness algorithm formula do not meet the allowable condition; when the brightness fitting curve and the preliminary brightness algorithm formula do not meet the allowable condition, bad points in multiple groups of the sampling data are removed and / or the interval step value is reduced, and then the brightness curve fitting is performed again until the brightness fitting curve and the preliminary brightness algorithm formula meet the allowable condition.

9. A computer device, comprising: The computer program is executed by the processor to implement the method of any one of claims 1-8.

10. A computer readable medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1-8.

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