KR20170026974A - Prediction method and system for predicting a luminance decline of display device - Google Patents

Abstract

The present invention relates to a method and a system for predicting a decrease in brightness of a display device. The method comprises the steps of: converting a pixel value in an image photographed by a camera into brightness to convert the pixel value into surface brightness; storing surface brightness for each hour in a memory by repeatedly converting the pixel value for a predetermined time period; and deriving a bright decrease estimation model for each pixel based on the surface brightness for each hour.

Description

TECHNICAL FIELD [0001] The present invention relates to a method and a system for predicting a decrease in luminance of a display device,

The present invention relates to a method and system for predicting luminance degradation of a display device through camera surface-based surface luminance modeling.

Since the organic light emitting diode display device is a self-luminous device, power consumption is lower than that of a liquid crystal display device requiring a backlight, and thus the organic light emitting diode display device can be made thinner. In addition, the organic light emitting diode display device has a wide viewing angle and a high response speed. Organic light emitting diode (OLED) display devices are expanding their market by competing with liquid crystal display devices by developing process technology up to the level of large-screen mass production technology.

The pixels of the organic light emitting diode display include organic light emitting diodes (OLEDs), which are self-luminous elements. In the OLED, a hole injection layer (HIL), a hole transport layer (HTL), an emission layer (EML), and an electron transport layer (ETL) are formed between an anode and a cathode. And an electron injection layer (EIL) are laminated on the substrate. The organic light emitting diode display reproduces an input image by using a phenomenon in which electrons and holes are emitted from an organic layer in a pixel OLED through a current flow in a fluorescent or phosphorescent organic thin film.

The organic light emitting diode display device can be divided into various types according to kinds of light emitting materials, light emitting systems, light emitting structures, driving systems, and the like. The organic light emitting diode display device is classified into a fluorescent emission and a phosphorescent emission according to a light emission method, and can be divided into a top emission structure and a bottom emission structure according to a light emission structure. In addition, the organic light emitting diode display device can be divided into PMOLED (Passive Matrix OLED) and AMOLED (Active Matrix OLED) according to the driving method.

The pixels of the OLED display device include a driving TFT (Thin Film Transistor) that adjusts the driving current flowing in the OLED according to the data of the input image.

The TFTs of the pixels are fabricated by MOSFET (Metal Oxide Semiconductor Field Effect Transistor) structure. Though the characteristics of a driving TFT such as a threshold voltage, a mobility, and the like must be designed to be the same in all pixels, characteristics of a driving TFT are not uniform in accordance with a process variation, a driving time, a driving environment and the like. Therefore, a technique for compensating for the change in the characteristics of the driving TFT is applied to the OLED display device. The change in the characteristics of the drive TFT means a change in characteristics of the drive TFT, such as threshold voltage and mobility of the drive TFT.

The compensation method for compensating the change of the driving characteristic of the pixel in the OLED display is divided into an internal compensation method and an external compensation method.

The internal compensation method automatically compensates the threshold voltage deviation between the driving TFTs within the pixel circuit. In order to perform internal compensation, the current flowing in the OLED must be determined regardless of the threshold voltage of the driving TFT, so that the configuration of the pixel circuit becomes complicated. Furthermore, the internal compensation method is difficult to compensate for the mobility deviation between the driving TFTs.

The external compensation method senses the electrical characteristics (threshold voltage, mobility) of the driving TFTs and compensates the electrical characteristic deviation by modulating the pixel data in the compensation circuit outside the display panel based on the sensing result. In recent years, research on such external compensation methods has been actively conducted. A conventional external compensation method receives a sensing voltage directly from each pixel through a sensing line connected to pixels in a display panel, converts the sensed voltage to digital sensing data, and transmits the sensed voltage to a timing controller. The timing controller modulates the digital video data of the input image based on the digital sensing data to compensate for the electrical characteristic deviation of the driving TFT.

In order to implement the existing internal compensation method and external compensation method, the pixel structure and operation become complicated. The complicated pixel structure increases the defect rate of the display panel to lower the yield and to secure the aperture ratio of the pixel, which makes it difficult to improve the resolution of the display panel.

Recently, a life predicting model of an organic light emitting diode (OLED) device has been developed, and a method of compensating for degradation of pixels based on a predictive model by storing the predictive model in an OLED display has been proposed. In this method, the luminance of each display panel is measured by a luminance meter at the center of the display panel at a predetermined time interval to derive a luminance decrease trend in an aging process of the display panel, And approximates it to a predictive model and stores it in memory.

However, since this method measures luminance only at one point of the display panel, it is very inaccurate because it is different from the degradation progress of the actual pixels in predicting the luminance decrease trend. Luminance can be measured at various points on the display panel. However, if a high-order point luminance meter and a multi-probe are required, a probe fixing arm for maintaining measurement accuracy is additionally required, which increases the cost of constructing the system .

Although the point luminance system can accurately measure the pixel luminance in real time, it is possible to measure the luminance only for pixels at a specific position in the display panel, so that measuring the luminance of the display panel at various positions increases the measurement time and increases the system construction cost . Even if the luminance is measured at the point luminance meter at a plurality of points, since the luminance is measured for only a few sample points, the degradation progress difference in each of the pixels of the display panel can not be accurately reflected in the prediction model.

The present invention provides a method and system for predicting a luminance degradation of a display device which improves the modeling accuracy of luminance degradation for all pixels of a display panel.

The luminance degradation prediction method of the present invention displays an image on a pixel array of a display panel and measures the luminance of some pixels spaced apart at a predetermined interval on the pixel array by using a luminance meter, The method of claim 1, further comprising the steps of: calculating luminance; displaying an image on a pixel array of the display panel and photographing the pixel array with a camera; The method of claim 1, further comprising: storing in memory a pixel value of each pixel in a predetermined time period; deriving a pixel-by-pixel luminance degradation prediction model based on the luminance per unit time; And storing the data as data.

The method of deriving the luminance degradation prediction model of the present invention comprises the steps of: deriving an approximated straight line connecting luminance values by extracting luminance values on a pixel-by-pixel basis in the time-dependent surface luminance, calculating a difference between the luminance values and the approximated straight line, Extracting and removing the large outlier, and deriving the per-pixel luminance degradation prediction model by approximating the straight line connecting the luminance values from which the outlier is removed.

The luminance degradation prediction system of the present invention comprises a luminance meter for displaying an image on a pixel array of a display panel and measuring the luminance of some pixels spaced apart at a predetermined interval on the pixel array, A pixel for displaying an image on the pixel array of the display panel and for photographing the pixel array; and a controller for setting a pixel value in the image photographed by the camera with a predetermined period of time, And a luminance degradation prediction model deriving unit for deriving a luminance degradation prediction model for each pixel based on the temporal surface luminance, The parameters of the luminance degradation prediction model for each pixel are extracted and stored as the lookup table data It shall include a permanent meter extraction.

According to the present invention, a display panel is photographed by a camera, a pixel value of the photographed image is converted into luminance, a surface luminance is generated, and a luminance degradation prediction model of each pixel is derived based on the surface luminance. As a result, the present invention can improve the degradation modeling accuracy for all the pixels of the display panel. Furthermore, the present invention can further improve the accuracy of the luminance resistance model for each pixel by removing the outliers from the luminance values used when calculating the luminance degradation prediction model.

According to the present invention, a luminance degradation model for each pixel derived from the aging process is stored in a display device, and the luminance degradation of the pixels is compensated based on the degradation model. Thus, the luminance degradation of the pixels can be compensated without an internal compensation circuit or an external compensation circuit.

The display device of the present invention includes a memory for storing a parameter defining a luminance degradation prediction model for each pixel derived through the luminance degradation prediction system and a memory for compensating for the luminance degradation of the pixels based on the parameter of the luminance degradation prediction model per pixel Compensation circuit.

BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a diagram briefly showing a method for predicting a luminance drop of a display device according to an embodiment of the present invention; FIG.
2 is a diagram showing a luminance degradation prediction system of a display apparatus according to an embodiment of the present invention.
3 is a detailed block diagram of the prediction model processing unit of the central processing unit shown in FIG.
4 is a diagram illustrating brightness uniformity and luminance uniformity of a camera image when measuring brightness of a display panel.
FIGS. 5 and 6 are diagrams illustrating a method of converting a pixel value of a camera image into an actual luminance value.
7 is a diagram showing a luminance degradation prediction model.
8 is a diagram showing a method for increasing the accuracy of the luminance degradation prediction model.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Like reference numerals throughout the specification denote substantially identical components. In the following description, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear. The component name used in the following description may be selected in consideration of easiness of specification, and may be different from the actual product name.

The present invention predicts the deterioration of the organic light emitting diode for each display panel based on the surface luminance obtained by photographing the luminance of the display panel with the camera in the pre-shipment aging step of the display panel. Here, deterioration refers to deterioration resulting in a variation in lifetime due to a difference in characteristics of each device regardless of a pixel thin film transistor (hereinafter referred to as "TFT"). The conventional external compensation circuit compensates for the TFT driving characteristic change of the pixel obtained through real-time sensing after the product is shipped from the display panel. TFT deterioration of the pixel can be compensated relatively accurately in real time by an existing external compensation circuit or an internal compensation circuit. The deterioration of the organic light emitting diode can not be compensated by the external compensation circuit or the internal compensation circuit.

The present invention does not compensate for TFT deterioration of a pixel through real-time sensing but stores a parameter of a predictive model which predicts a decrease in brightness of all pixels in a display panel of a display panel before shipping the product, in a memory of a display device. The present invention compensates for the deterioration of pixels based on the luminance degradation prediction model of each pixel according to the use time of the organic light emitting diode display. The deterioration can be compensated by applying the luminance degradation prediction model to all the pixels without the internal compensation circuit or the external compensation circuit of the present invention. If the luminance degradation prediction model is accurate, the lifetime of the organic light emitting diode display device can be extended by compensating the deterioration of the pixel without using an internal compensation circuit or an external compensation circuit.

The predictive method for predicting the degradation of the luminance of an image on a pixel array of a display panel and measuring the luminance of some pixels spaced apart at a predetermined interval on the pixel array and using the luminance measurement values of the pixels, A second step of displaying an image on a pixel array of a display panel and photographing a pixel array with a camera; A third step of converting the pixel value into the brightness and converting the pixel value into the surface luminance in the photographed image of the camera, a fourth step of repeating the second and third steps at predetermined time intervals to store the surface luminance per time into the memory, And a sixth step of storing parameters of the per-pixel brightness degradation prediction model as look-up table data. The surface luminance includes luminance information of all the pixels.

FIG. 1 and FIG. 2 are views showing a method and system for predicting lifetime tendency of an organic light emitting diode device according to an embodiment of the present invention.

Referring to FIGS. 1 and 2, the prediction model system 100 of the present invention includes a camera 10, a memory 12, and a central processing unit (hereinafter referred to as a " CPU ").

The predictive model system 100 displays red, green, blue, and white on the display panel 300 in the pre-shipment aging process of the organic light emitting diode display device in step S1, Is photographed by the camera (10) to obtain luminance data of all the pixels. The red, green, blue, and white data are degradation accelerated pattern images for lifelike tendency analysis of pixels. The lowering of the luminance tends to accelerate in the order of blue> red> green> white.

The camera 10 photographs the pixel array of the display panel on which the deterioration acceleration pattern image of each color is displayed at a predetermined time interval, and transmits the captured image to the memory 12 for storage. The predetermined period of time may be 24 hours, but is not limited thereto.

Since the photographed image of the camera 10 is 8-bit data representing the pixel intensity, the brightness can not be accurately expressed. The pixel data of the camera photographed image is a relative value. On the other hand, the luminance meter accurately measures the luminance of the pixel. The luminance measured by the luminance meter is an absolute value.

The CPU 14 executes the preset I2L (Intensity to Luminance) algorithm in step S1. The I2L algorithm converts the pixel data of the camera photographed image read from the memory 12 into luminance, The luminance of all the pixels is measured at the luminance. The CPU 14 performs the I2L algorithm to convert the pixel intensity of the camera image to brightness without camera optical distortion (vignetting) phenomenon.

In step S2, the CPU 10 derives a luminance degradation prediction model based on the luminance measured in each of all the pixels, and calculates a parameter of the prediction model. The CPU 10 sets this parameter as look-up table (LUT) data, extracts a look-up table stored with a pixel-by-pixel luminance degradation prediction model, and stores it in the memory 12 (S3). An example of the luminance degradation prediction model is shown in Fig. The parameters defining the luminance degradation prediction model y = ax + b include a and b.

An organic light emitting diode display according to an embodiment of the present invention includes a compensation system 200. The compensation system 200 includes a memory 22 connected to a timing controller (T-CON) The memory 22 receives and stores a look-up table that defines the luminance degradation prediction model for each pixel of each pixel from the prediction model system 100.

The timing controller 20 may include a compensation circuit. The compensation circuit compensates the deterioration of each pixel by modulating the data of the input image received from the external host system through the interface board 24 based on the pixel-by-pixel luminance degradation prediction model. The compensation circuit generates a compensation value for compensating for the luminance drop of the pixel based on the parameters (a, b) of the pixel-by-pixel luminance degradation prediction model, and adds or multiplies the compensation value to the data of the input image, can do.

The OLED display of the present invention can predict the degradation level of all the pixels when the usage time has elapsed as a prediction model of luminance degradation for each pixel. Therefore, the present invention can generate a compensation value for compensating the deterioration level of a pixel without real time sensing the driving characteristics of the pixels.

FIG. 3 is a detailed diagram of the prediction model processing unit of the CPU 14 shown in FIG.

3, the prediction model processing unit includes a camera image acquisition unit 31, a calibration unit 32, a luminance conversion map calculation unit 33, an I2L performing unit 34, a pixel luminance mapping unit 35, An outlier removing unit 36, a luminance lowering prediction model deriving unit 37, and a prediction model parameter extracting unit 38.

The camera image acquisition section 31 receives the photographed image data of the camera 10 and transmits the photographed image data to the calibration section 32. The calibration (32) compensates the camera photographed image data by a radially symmetric polynomial modeling and model parameter estimation method based on Weighted Least Square for camera optical distortion correction.

The present invention can be applied to a predetermined number (for example, the number of pixels) of the display panel 300 on the pixel array of the display panel 300 by using a luminance meter, for example, CA-310 in order to calculate the ratio R for converting the camera image I into surface luminance L : 9-points, and 25-points), and then approximate the brightness of the pixels at the specified positions by the least squares method (Least Square) To calculate the ratio (R = C / I). This process is performed by the luminance conversion map calculation unit 33. [ The luminance conversion map calculator 33 generates a luminance conversion map (Calibration Map) for converting the pixel value (I, pixel intensity) of the camera photographed image into luminance. The luminance conversion map calculator 33 calculates the luminance of the display panel 300 using the luminance meter CA-310 and then divides the data C modeled by the Least Square-based polynomial equation into pixel values I (R = C / I), and this process is performed only once during camera setup.

The I2L performing unit 34 multiplies the pixel value of the camera photographed image by the data of the I2L luminance conversion map (calibration map), converts each pixel value into luminance, separates the surface luminance data including the luminance of all pixels by time, (12). The data of the I2L luminance conversion map is the ratio of pixel value to luminance conversion (R = C / I) in each of the pixels.

The pixel luminance mapping unit 35 converts the resolution (e.g., 8176 x 6132) of the camera image to the resolution of the display panel (e.g., 3840 x 2160) and stores the luminance data of each hour divided into predetermined time periods in the memory 12 do. The outlier removing unit 36 removes outliers excessively out of the luminance (actual value) obtained in each of the pixels in each of the pixels as shown in FIG.

The luminance degradation prediction model derivation unit 37 derives the luminance degradation prediction model by a straight line approximated as shown in FIG. 6 based on the luminance of each pixel in which the outlier is removed in each of the pixels. The predictive model parameter extracting unit 38 extracts the parameters (a, b) of the luminance degradation prediction model derived from each of the pixels, and stores the extracted parameters as the lookup table data in the memory 12.

Since the relationship between the pixel value of the image and the actual luminance of the pixels is unclear only with the camera image, measuring the luminance of the pixel using only the camera image is inaccurate. In addition, due to the optical distortion due to the characteristics of the camera, it is impossible to measure the accurate luminance with the camera. A difference between the maximum luminance and the minimum luminance may occur due to the pixel deviation when displaying the same gray level in all the pixels of the display panel. For example, as shown in FIG. 4, the luminance uniformity may be 0.8 when displaying the gray level 128 in all the pixels of the display panel. The luminance uniformity of the image data obtained by photographing the pixel array of the display panel with the camera may be 0.5. Therefore, the difference between the actual luminance of the pixels and the pixel value of the camera photographed image is large.

FIGS. 5 and 6 are diagrams illustrating a method of converting a pixel value of a camera image into an actual luminance value.

Referring to FIGS. 5 and 6, the present invention provides a method of displaying an accelerated pattern image on a display panel 300 and displaying the accelerated pattern image on pixels located at nine sample points spaced apart from each other by a predetermined interval in the display panel 300 The luminance is measured by a luminance meter (CA-310). The luminance of the pixels at positions other than the sample point is calculated by the interpolation circuit using the luminance measurements of the sample point.

In the aging process, a deterioration accelerating pattern image is displayed on the display panel 300 and a pixel array of the display panel is photographed by the camera 10 at predetermined time intervals. The camera photographed image consists of pixel values (I) for each of the pixels.

The present invention relates to an I2L luminance transformation map that defines a ratio (R = C / I) of a pixel value (I) to a luminance (C) for each of pixels to convert a pixel value (I) ). The present invention generates a plane luminance transformed image by multiplying the pixel value (I) of the camera photographed image by R = C / I of the luminance transformation map and converting the pixel value (I) of all pixels into luminance.

The step of measuring the luminance of the display panel 300 with the luminance meter CA-310 and the step of preparing the luminance conversion map are performed only once at the time of camera setup and stored as a look-up table (LUT). After that, the present invention can input the pixel value I of the camera photographed image into the lookup table (LUT), and automatically generate the surface luminance using only the camera photographed image. When the lookup table is set, the pixel value I of the photographed image is input to the lookup table, and the pixel-by-pixel luminance conversion ratio R is automatically selected in the lookup table. When the pixel value I is multiplied by the luminance conversion ratio R, the pixel value I is converted to the luminance L. [

In the aging process, the display panel 300 displaying the deterioration accelerating pattern images is photographed by the camera 10 at predetermined time intervals, for example, at intervals of 24 hours, and is converted into surface luminance, divided by time, and stored in the memory.

7 is a diagram showing a luminance degradation prediction model. 8 is a diagram showing a method for increasing the accuracy of the luminance degradation prediction model. 7 and 8, the x-axis is time and y is luminance.

7 and 8, the approximated straight line (the red straight line in FIG. 7 and the blue straight line IRLS in FIG. 8) obtained by extracting the luminance values for each pixel in the time-dependent surface luminance and connecting the luminance values is derived, (Outlier) in which the difference between the actual value (actual value) and the approximated straight line (predicted value) is larger than the standard deviation is extracted and removed. Further, according to the present invention, more accurate luminance degradation can be predicted by deriving a pixel-by-pixel luminance degradation prediction model (red straight line LS in FIG. 8) by approximating straight lines connecting the luminance values of the outliers.

Referring to FIGS. 7 and 8, when the surface luminance measured on the basis of a camera is obtained, the present invention extracts luminance measured at a predetermined time interval for each pixel in the surface luminance.

The present invention derives a luminance degradation prediction model by calculating an approximated straight line (predicted value) connecting luminance (actual value) measured at predetermined time intervals. It should be noted that the luminance degradation prediction model is not limited to FIG. 7, but a known luminance degradation prediction algorithm can be applied. The parameters (a, b) of the luminance degradation prediction model derived for each pixel are stored as a lookup table and utilized as basic data when modulating data to compensate for deterioration of pixels.

In order for the luminance decay to be accurately predicted, there may be an outlier whose luminance measurement value is accurate but which is different from other measured values due to measurement errors or external environment. These outliers inaccurate the luminance degradation prediction. Therefore, the present invention compares the standard deviation of the difference between the actual value and the predicted value ("r" in FIG. 7), extracts outliers larger than the standard deviation, lowers the weight to be multiplied by the outliers, Increase the accuracy of the prediction model. The actual value is the green point in FIG. 7 as the surface luminance measurement value obtained from the camera photographed image. The predicted value is an approximated straight line connecting the actual values and is a red straight line in FIG.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Therefore, the present invention should not be limited to the details described in the detailed description, but should be defined by the claims.

10: camera 12, 22: memory
14: CPU 20: Timing controller
31: camera image acquisition unit 32:
33: luminance conversion map calculating unit 34: I2L performing unit
35: pixel luminance mapping unit 36: outlier removal
37: luminance lowering prediction model deriving unit 38: prediction model parameter extracting unit
100: prediction model system 200: compensation system
300: Display panel

Claims (5)

A first step of displaying an image on a pixel array of a display panel, measuring luminance of some pixels spaced apart at a predetermined interval on the pixel array by using a luminance meter, and calculating luminance of other pixels using luminance measurement values of the pixels;
A second step of displaying an image on a pixel array of the display panel and photographing the pixel array with a camera;
A third step of converting the pixel value into the brightness and converting the pixel value into the surface luminance in the photographed image of the camera;
A fourth step of repeating the second and third steps in a predetermined time period and storing the surface luminance per time in a memory;
A fifth step of deriving a luminance degradation prediction model for each pixel based on the temporal surface luminance; And
And a sixth step of extracting the parameters of the per-pixel luminance degradation prediction model and storing the extracted parameters as the lookup table data. The method according to claim 1,
In the fifth step,
Deriving an approximated straight line connecting brightness values by extracting brightness values on a pixel-by-pixel basis in the time-dependent surface brightness;
Extracting and removing an outlier whose difference between the luminance values and the approximated straight line is larger than a standard deviation; And
And deriving the per-pixel luminance degradation prediction model by approximating a straight line connecting the luminance values from which the outlier is removed. A luminance meter for displaying an image on a pixel array of the display panel and measuring the luminance of some pixels spaced apart at a predetermined interval on the pixel array;
An interpolator for calculating the luminance of the other pixels using the luminance measured value of the pixels measured through the luminance meter;
A camera for displaying an image on a pixel array of the display panel and photographing the pixel array;
A luminance conversion map processing unit for generating a surface luminance by changing a pixel value to the luminance in an image photographed by the camera at a predetermined time period, separating the surface luminance by time and storing it in a memory;
A luminance degradation prediction model deriving unit for deriving a luminance degradation prediction model for each pixel based on the temporal luminance; And
And a parametric extractor for extracting the parameters of the per-pixel luminance degradation prediction model and storing the extracted parameters as the lookup table data. The method of claim 3,
Extracting luminance values for each pixel in the time-dependent surface luminance, deriving an approximated straight line connecting luminance values, extracting an outlier having a difference between the luminance values and the approximated straight line greater than a standard deviation, and removing the outlier Further,
The luminance degradation prediction model deriving unit
And derives the pixel-by-pixel luminance degradation prediction model by approximating the straight line connecting the luminance values from which the outlier is removed. A memory for storing a parameter defining a luminance degradation prediction model for each pixel derived by the luminance degradation prediction system according to claim 3 or 4; And
And a compensation circuit for compensating for a decrease in luminance of the pixels based on the parameters of the per-pixel luminance degradation prediction model.

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