Filtering method and apparatus, display device, electronic device, and storage medium

Abstract

The present disclosure relates to a filtering method and device, a display device, an electronic device and a storage medium. The method comprises: determining a size of a filtering window and a filtering parameter; determining elements in the filtering window according to the filtering parameter; filtering sensor data according to the size of the filtering window and the elements in the filtering window to obtain a filtered sensor data array. According to the filtering method of the embodiments of the present disclosure, the determined elements in the filtering window can be determined based on the filtering size and the filtering parameter, so that the sensor data can be filtered according to the determined filtering window, the efficiency of the filtering process can be improved, the load of the operation resource can be reduced, the interference of the noise on the touch signal can be reduced, and the accuracy of detecting the touch event can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of display devices, and more particularly to a filtering method and apparatus, a display device, an electronic device, and a storage medium. Background Technology

[0002] In related technologies, display devices may include sensor arrays for acquiring touch data from users. However, the touch data collected by the sensors in the sensor array often contains environmental noise, which may affect subsequent touch event calculations. Therefore, after obtaining the data collected by the sensors, the data needs to be filtered to eliminate noise. Summary of the Invention

[0003] In view of this, the present disclosure provides a filtering method and apparatus, a display device, an electronic device and a storage medium.

[0004] According to one aspect of this disclosure, a filtering method is provided, comprising: determining the size and filtering parameters of a filtering window for filtering a sensor data array acquired by a sensor array, wherein the sensor array includes a plurality of touch sensors of a screen, the touch sensors being used to acquire sensor data in the sensor data array, and the filtering window being a matrix including a plurality of elements; determining the elements within the filtering window according to the filtering parameters; and filtering the plurality of sensor data in the sensor data array according to the size of the filtering window and the elements within the filtering window to obtain a filtered sensor data array.

[0005] In one possible implementation, determining the elements within the filtering window based on the filtering parameters includes: determining the elements within the filtering window based on the filtering parameters, a preset symmetry function, and the coordinates of the elements within the filtering window.

[0006] In one possible implementation, the preset symmetric function includes a bivariate normal distribution function.

[0007] In one possible implementation, filtering multiple sensor data in the sensor data array based on the size of the filtering window and the elements within the filtering window to obtain a filtered sensor data array includes: performing at least one of rounding and normalization on the elements within the filtering window to obtain a filtering matrix, wherein the size of the filtering window is equal to the size of the filtering matrix; determining neighborhood data of the sensor data based on the size of the filtering window; obtaining filtered data corresponding to the sensor data based on the sensor data, the neighborhood data, and the filtering matrix; and obtaining the filtered sensor data array based on the filtered data.

[0008] In one possible implementation, rounding the elements within the filtering window includes: magnifying each element within the filtering window by 10. n The integer part is multiplied by 1, and the decimal places are removed to obtain the rounded element, where n is a positive integer.

[0009] In one possible implementation, obtaining the filtered sensor data array based on the filtered data includes: reducing each of the filtered data sets by 10. n The first data is obtained by multiplying the data by a factor of 1 and removing the decimal places; based on the first data, the filtered sensor data array is obtained.

[0010] In one possible implementation, obtaining a filter matrix by performing at least one of rounding and normalization on the elements within the filter window includes: when the sensor data is located at the edge of the sensor data array, reducing the elements within the filter window according to the coordinates of the sensor data in the sensor data array, and performing at least one of rounding and normalization on the reduced elements to obtain a filter matrix corresponding to the sensor data located at the edge of the sensor data array.

[0011] In one possible implementation, obtaining filtered data corresponding to the sensor data based on the sensor data, the neighborhood data, and the filtering matrix includes: determining the neighborhood data of the sensor data located at the edge of the sensor data array based on the size of the filtering window after removing elements.

[0012] According to another aspect of this disclosure, a filtering device is provided, comprising: a parameter determining module, configured to determine the size of a filtering window and filtering parameters for filtering a sensor data array acquired by a sensor array, wherein the sensor array includes a plurality of touch sensors of a screen, the touch sensors being used to acquire sensor data in the sensor data array, and the filtering window being a matrix including a plurality of elements; an element determining module, configured to determine elements within the filtering window according to the filtering parameters; and a filtering module, configured to filter the plurality of sensor data in the sensor data array according to the size of the filtering window and the elements within the filtering window, to obtain a filtered sensor data array.

[0013] In one possible implementation, the element determination module is further configured to: determine the elements within the filtering window based on the filtering parameters, a preset symmetry function, and the coordinates of the elements within the filtering window.

[0014] In one possible implementation, the preset symmetric function includes a bivariate normal distribution function.

[0015] In one possible implementation, the filtering module is further configured to: perform at least one of rounding and normalization processing on the elements within the filtering window to obtain a filtering matrix, wherein the size of the filtering window is equal to the size of the filtering matrix; determine the neighborhood data of the sensor data based on the size of the filtering window; obtain filtered data corresponding to the sensor data based on the sensor data, the neighborhood data, and the filtering matrix; and obtain the filtered sensor data array based on the filtered data.

[0016] In one possible implementation, the filtering module is further configured to: magnify each element within the filtering window by 10. n The integer part is multiplied by 1, and the decimal places are removed to obtain the rounded element, where n is a positive integer.

[0017] In one possible implementation, the filtering module is further configured to: reduce each of the filtered data by 10. n The first data is obtained by multiplying the data by a factor of 1 and removing the decimal places; based on the first data, the filtered sensor data array is obtained.

[0018] In one possible implementation, the filtering module is further configured to: when the sensor data is located at the edge of the sensor data array, reduce the elements in the filtering window according to the coordinates of the sensor data in the sensor data array, and perform at least one of rounding and normalization processing on the reduced elements to obtain a filtering matrix corresponding to the sensor data located at the edge of the sensor data array.

[0019] In one possible implementation, the filtering module is further configured to: determine the neighborhood data of the sensor data located at the edge of the sensor data array based on the size of the filtering window after element removal.

[0020] According to another aspect of this disclosure, a display device is provided, including a plurality of display units and a processor, wherein the display units include a sensor array, and the processor is configured to implement the above-described method by executing instructions.

[0021] In one possible implementation, the display unit includes a display panel, which includes at least one of a liquid crystal display panel, a micro light-emitting diode display panel, a light-emitting diode display panel, a mini light-emitting diode display panel, a quantum dot light-emitting diode display panel, an organic light-emitting diode display panel, a cathode ray tube display panel, a digital light processing display panel, a field emission display panel, a plasma display panel, an electrophoretic display panel, an electrowetting display panel, and a small-pitch display panel.

[0022] According to another aspect of this disclosure, an electronic device is provided, including the aforementioned display device.

[0023] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided that stores computer program instructions thereon, wherein the computer program instructions, when executed by a processor, implement the above-described method.

[0024] According to another aspect of this disclosure, a computer program product is provided, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.

[0025] According to another aspect of this disclosure, a driver chip is provided for performing the filtering method.

[0026] According to the filtering method of the embodiments of the present disclosure, certain elements within a filtering window can be determined based on the filtering size and filtering parameters. This allows sensor data to be filtered according to the determined filtering window, thereby improving the efficiency of filtering, reducing the load on computing resources, reducing noise interference to touch signals, and improving the accuracy of touch event detection.

[0027] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0028] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0029] Figure 1 A flowchart of a filtering method according to an embodiment of the present disclosure is shown;

[0030] Figure 2 A schematic diagram of a filtering process according to an embodiment of the present disclosure is shown;

[0031] Figure 3A , Figure 3B , Figure 3C and Figure 3D A schematic diagram illustrating the application of a filtering method according to an embodiment of the present disclosure is shown.

[0032] Figure 4 A block diagram of a filtering device according to an embodiment of the present disclosure is shown;

[0033] Figure 5 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0034] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0035] In the description of this disclosure, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this disclosure and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0036] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise expressly specified.

[0037] In this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0038] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0039] Figure 1 A flowchart illustrating a filtering method according to an embodiment of the present disclosure is shown. Figure 1 As shown, the filtering method includes:

[0040] In step S11, the size and filtering parameters of the filtering window for filtering the sensor data array acquired by the sensor array are determined. The sensor array includes multiple touch sensors of the screen, the touch sensors are used to acquire sensor data in the sensor data array, and the filtering window is a matrix including multiple elements.

[0041] In step S12, the elements within the filtering window are determined based on the filtering parameters;

[0042] In step S13, multiple sensor data in the sensor data array are filtered according to the size of the filtering window and the elements within the filtering window to obtain a filtered sensor data array.

[0043] According to the filtering method of the embodiments of the present disclosure, certain elements within a filtering window can be determined based on the filtering size and filtering parameters. This allows sensor data to be filtered according to the determined filtering window, thereby improving the efficiency of filtering, reducing the load on computing resources, reducing noise interference to touch signals, and improving the accuracy of touch event detection.

[0044] In one possible implementation, the display device, such as a screen (e.g., a touchscreen), may include a sensor array. This sensor array may include multiple touch sensors capable of detecting touch signals from a user on the screen (e.g., pressure applied to a location on the screen, induced charge, etc.) to determine the touch location. The sensor array may be distributed across the underside of the screen to detect touch signals from various locations on the screen. The sensor array may be refreshed at a set frequency (i.e., the sensors reacquire new data). During refresh, the sensor data array obtained at the set frequency does not need to be refreshed entirely at once; it can be grouped by row or column, and each group of sensor data can be refreshed sequentially. The sensor data in the sensor data array corresponds to the touch sensors in the sensor array; that is, each sensor data point is acquired by a touch sensor.

[0045] In one possible implementation, the sensor data may carry ambient noise, such as high-frequency noise. Therefore, the sensor data can be filtered to improve the accuracy of touch signal detection.

[0046] In one possible implementation, a matrix containing defined elements can be used as a filtering window to filter the data from each sensor in the sensor array, thereby obtaining a filtered sensor array, which reduces computational complexity and improves the efficiency of filtering.

[0047] In one possible implementation, the size of the filtering window and the filtering parameters can be determined in step S11. In this example, the filtering window can be a matrix containing multiple elements; for example, the matrix can be a square matrix, i.e., a matrix where the number of rows equals the number of columns, thereby simplifying the calculations in the filtering process. For example, the size of the filtering window can be 2×2, 3×3, 4×4, etc., and this disclosure does not limit the specific value of the filtering window size.

[0048] In one possible implementation, filtering parameters can also be determined, which may be related to the specific values ​​of the elements within the filtering window. For example, the filtering parameters can be used as one of the parameters for solving each element within the filtering window. This disclosure does not limit the specific values ​​of the filtering parameters.

[0049] In one possible implementation, in step S12, the elements within the filtering window can be calculated based on the filtering parameters determined above. Step S12 may include: determining the elements within the filtering window according to the filtering parameters, a preset symmetry function, and the coordinates of the elements within the filtering window.

[0050] In one possible implementation, the coordinates of the elements within the filtering window may include the row and column numbers of the elements. For example, the coordinates of the element in the first row and first column are (1, 1). This disclosure does not limit the specific form of the coordinates.

[0051] In one possible implementation, to simplify the calculation process, a symmetric function can be used in the process of calculating each element within the filtering window. That is, a function that makes the graph of the function symmetric when the number of rows and columns are used as input parameters of the symmetric function. For example, the preset symmetric function includes the bivariate normal distribution function.

[0052] In the example, the symmetric function can be determined according to the following formula (1):

[0053]

[0054] Where x is the number of rows, y is the number of columns, σ is the filtering parameter, and G is the element in the filtering window, that is, the element with x as the number of rows and y as the number of columns. Using the value obtained by this function as the element at row x and column y in the filtering window makes the filtering window a symmetric matrix, thereby simplifying the calculation process in filtering and improving the calculation efficiency.

[0055] In the example, a 3×3 matrix is ​​used as the filter window, and the coordinates of the elements are made symmetrical. For example, the row number x can be -1, 0, or 1, and the column number y can also be -1, 0, or 1. Since the number of rows and columns are squared in the above symmetric function (1), the symmetry of the elements in the filter window can be further improved, simplifying the calculation process in the filtering process and improving the calculation efficiency. This disclosure does not restrict the value of the number of rows, the value of the number of columns, or the size of the filter window. For example, the number of rows and columns of the filter window can be odd, and the values ​​of the number of rows and columns can be two or more values ​​that are opposites of each other, as well as 0. For example, the values ​​of the number of rows and columns can be -m, -m+1, ..., 0...m-1, m, where m is a positive integer.

[0056] In the example, taking a 3×3 matrix as the filter window, the filter window can be expressed in the form of the following formula (2):

[0057]

[0058] In one possible implementation, the filter window determined above is a fixed filter window, that is, no matter which data in the sensor data array is filtered, the value of the element in the filter window will not change, thereby improving the efficiency of the operation and reducing the load on the computing resources.

[0059] In one possible implementation, having obtained the elements within the filtering window, multiple sensor data in the sensor data array can be filtered in step S13 based on the filtering window to obtain the filtered sensor data array.

[0060] In one possible implementation, the elements of the filter window obtained above may have decimal places. For example, in formula (2), the elements determined by the binary normal distribution function may have decimal places. Therefore, when performing filtering based on the filter window, the elements in the filter window can be rounded down, or the data after filtering can be processed to make the filtered data obtained after filtering an integer.

[0061] In one possible implementation, step S13 may include: performing at least one of rounding and normalization on the elements within the filtering window to obtain a filtering matrix, wherein the size of the filtering window is equal to the size of the filtering matrix; determining the neighborhood data of the sensor data based on the size of the filtering window; obtaining filtered data corresponding to the sensor data based on the sensor data, the neighborhood data, and the filtering matrix; and obtaining the filtered sensor data array based on the filtered data.

[0062] In one possible implementation, if the elements within the filtering window have decimal places (i.e., are non-integers), the elements within the filtering window can be rounded down to remove the decimal places and retain the integer parts. However, this approach may result in a large number of zero elements, affecting the filtering process. The rounding down of the elements within the filtering window includes: magnifying each element within the filtering window by 10. n The integer part is multiplied by 1, and the decimal places are removed to obtain the rounded element, where n is a positive integer.

[0063] In one possible implementation, all elements within the filter window can be magnified by 10. n The magnification factor can be multiplied by a factor of 1000 or 10000, and no limit is placed on the magnification factor. Removing decimal places after magnification reduces the probability of obtaining zero elements, thus minimizing the impact on the filtering process. In subsequent filtering processes, the filtered data can be reduced by a corresponding factor, and decimal places can be removed after reduction.

[0064] In one possible implementation, the elements within the filtering window can be normalized. After normalization, non-integer elements may still be obtained. These normalized elements can then be rounded down to obtain integer elements, and filtering can be performed based on these normalized and rounded elements. Alternatively, rounding can be omitted; instead, the normalized elements can be used for filtering, and the resulting filtered data can be rounded down. This disclosure does not restrict whether normalization is performed or when rounding is performed.

[0065] In one possible implementation, after at least one of the above rounding and normalization processes, a filtering matrix can be obtained. The elements in the filtering matrix are the elements after at least one rounding and normalization process. Sensor data can be filtered based on the filtering matrix. In the example, the sensor data can be filtered using a convolutional processing method, where the filtering matrix can serve as the convolution kernel, and the elements in the filtering matrix can serve as the kernel parameters. During the filtering of a particular sensor data point, the neighborhood data of the sensor data can be determined based on the size of the filtering window. Then, the filtering matrix can be used to filter both the neighborhood data and the sensor data (e.g., through convolution) to obtain the filtered sensor data.

[0066] In the example, the size of the matrix formed by the sensor data and its neighborhood data is equal to the size of the filter window. For example, if the filter window is a 3×3 matrix, then the sensor data and its neighborhood data form a 3×3 matrix. In the example, the elements of the filter window are generated based on their coordinates, and the elements are symmetrical. For example, in a 2×2 filter window, the elements are generated based on four coordinates: (0, 0), (1, 1), (0, 1), and (1, 0). Furthermore, a symmetric function is used in the calculation, thus ensuring symmetry between the elements of the filter window. When determining the neighborhood data of the sensor data to be filtered, since the size of the matrix formed by the sensor data and its neighborhood data is equal to the size of the filtering window, the element with coordinate (0, 0) can be used as the reference. That is, the sensor data corresponds to the element with coordinate (0, 0), the adjacent data to the right of the sensor data corresponds to the element with coordinate (0, 1), the adjacent data below the sensor data corresponds to the element with coordinate (1, 0), and the adjacent data to the lower right of the sensor data corresponds to the element with coordinate (1, 1). In other words, the sensor data and its neighborhood data also form a 2×2 matrix, and the sensor data is the first element of the 2×2 matrix. For example, in a 3×3 filter window, the elements of the filter window are generated based on nine coordinates: (0, 0), (1, 1), (0, 1), (1, 0), (-1, 0), (-1, -1), (0, -1), (1, -1), and (-1, 1). Furthermore, a symmetric function is used during the calculation, so the elements of the filter window are symmetric. When determining the neighborhood data of the sensor data to be filtered, since the size of the matrix formed by the sensor data and its neighborhood data is equal to the size of the filtering window, the element with coordinate (0, 0) can be used as the reference. That is, the sensor data corresponds to the element with coordinate (0, 0), the adjacent data to the right of the sensor data corresponds to the element with coordinate (0, 1), the adjacent data below the sensor data corresponds to the element with coordinate (1, 0), the adjacent data to the lower right of the sensor data corresponds to the element with coordinate (1, 1), the adjacent data to the upper left of the sensor data corresponds to the element with coordinate (-1, -1), the adjacent data to the left of the sensor data corresponds to the element with coordinate (-1, 0), the adjacent data to the lower left of the sensor data corresponds to the element with coordinate (1, -1), the adjacent data above the sensor data corresponds to the element with coordinate (-1, 0), and the adjacent data to the upper right of the sensor data corresponds to the element with coordinate (-1, 1). In other words, the sensor data and its neighborhood data also form a 3×3 matrix, and the 3×3 matrix is ​​centered on the sensor data.

[0067] In one possible implementation, after determining the neighborhood data of the sensor data to be filtered, filtering can be performed based on the sensor data, its neighborhood data, and the filtering matrix. For example, convolution operations can be performed in a similar manner to obtain the filtered sensor data. For instance, filtering can be performed according to the following formula (3):

[0068] g(i,j)=∑ x,y f(ix,jy)h(x,y) (3)

[0069] Where f(i,j) is the sensor data with coordinate (i,j) in the sensor array, and g(i,j) is the filtered data after filtering the sensor data with coordinate (i,j).

[0070] Figure 2 A schematic diagram of a filtering process according to an embodiment of the present disclosure is shown. Figure 2 As shown, Figure 2 The left side shows multiple sensor data to be filtered. For example, sensor data with coordinates (1,1), (1,2), (1,3), (2,1), (2,2), (2,3), (3,1), (3,2), (3,3) in a sensor data array. Among them, the sensor data with coordinates (1,1), (1,2), (1,3) and the sensor data with coordinates (2,1), (3,1) are the edges of the sensor data array. The number of rows and columns of the sensor data array can be greater than 3. Figure 2 The right side is a 3×3 filtering matrix, and the row number x takes the values ​​of -1, 0, and 1, and the column number y also takes the values ​​of -1, 0, and 1. The sensor data can be filtered using the above formula (3). For example, when filtering the sensor data at coordinate (2,2), based on formula (3), the filtered data g(2,2) after filtering the sensor data at coordinate (2,2) is f(1,1)*h(1,1)+f(1,2)*h(1,0)+f(1,3)*h(1,-1)+f(2,1)*h(0,1)+f(2,2)*h(0,0)+f(2,3)*h(0,-1)+f(3,1)*h(-1,1)+f(3,2)*h(-1,0)+f(3,3)*h(-1,-1). Sensor data with coordinates (2, 3), (3, 2), (3, 3) can also be filtered in a similar way.

[0071] In one possible implementation, during the filtering process, a situation may arise where the sensor data to be filtered and the neighborhood data cannot form a matrix of the same size as the filtering matrix. For example, the sensor data may be located at the edge of the sensor data array, such as data with coordinates (1, 1), (2, 1), etc. In this case, the sensor data array or the filtering window can be processed to enable filtering.

[0072] In one possible implementation, the sensor data array can be processed, for example, by adding a row and column 0 to the sensor data array and setting the data in the row and column 0 to values ​​such as 0, 1, or random numbers. This disclosure does not limit the specific values ​​of the added data. Thus, when the sensor data located at the edge of the original sensor data is filtered using the above formula (3), it can obtain sufficient neighborhood data, thereby enabling filtering and obtaining filtered data.

[0073] In one possible implementation, the filtering window can be processed to change its size, allowing sensor data located at the edge of the sensor data array to form a matrix with its neighboring data that matches the size of the filtering window. Obtaining the filtering matrix involves performing at least one of rounding and normalization on the elements within the filtering window, including: when the sensor data is located at the edge of the sensor data array, reducing the elements within the filtering window according to the coordinates of the sensor data in the sensor data array, and then performing at least one of rounding and normalization on the reduced elements to obtain the filtering matrix corresponding to the sensor data located at the edge of the sensor data array.

[0074] In the example, if the sensor data to be filtered is the sensor data at coordinate (1, 1), then its neighboring data are the sensor data at coordinates (1, 2), (2, 1), and (2, 2). Correspondingly, the filtering window can be reduced to retain elements at coordinates (0, 0), (1, 1), (0, 1), and (1, 0). Then, either rounding or normalization is performed based on these four elements. For example, during normalization, any element is divided by the difference between the maximum and minimum values ​​of these four elements, instead of the original difference between the maximum and minimum values ​​of the nine elements. After the reduction and either rounding or normalization, the filtering matrix for the sensor data at coordinate (1, 1) can be obtained.

[0075] In one possible implementation, after obtaining the reduced filtering matrix, filtering can be performed using the reduced filtering matrix. Based on the sensor data, the neighborhood data, and the filtering matrix, filtered data corresponding to the sensor data can be obtained, including: determining the neighborhood data of the sensor data located at the edge of the sensor data array based on the size of the filtering window after element reduction.

[0076] In the example, during the filtering process, formula (3) can also be reduced. For example, terms containing h(-1,-1), h(-1,0), h(0,-1), h(1,-1), and h(-1,1) can be removed. That is, the neighborhood of the sensor data determined by the size of the filter window after the removal of elements, and the formula (3) after the removal of terms are used to calculate the filtered data of the sensor data.

[0077] In one possible implementation, the sensor data at coordinate (1, 1) above is only an example. Other sensor data located at the edge of the sensor data array can also be reduced in a similar way. For example, the neighboring data of the sensor data at coordinate (2, 1) has coordinates (1, 1), (3, 1), (1, 2), (2, 2), and (2, 3). Elements with coordinates (-1, -1), (0, -1), and (1, -1) in the filtering window can be reduced. The filtering matrix can be obtained by normalization or rounding based on the reduced elements. The corresponding terms in formula (3) are then reduced. The filtered data of the sensor data at coordinate (2, 1) is solved based on the reduced formula (3). The operation methods for other sensor data located at the edge can be used in a similar way, and will not be listed here.

[0078] In one possible implementation, filtered data from each sensor can be obtained according to the above method. Further, the filtered data is obtained by filtering a filter matrix after either rounding or normalization. During the rounding or normalization process, the elements within the filtering window can be magnified by 10. n The elements of the filter matrix are obtained by multiplying by 10 and removing decimal places. Therefore, if the value is multiplied by 10 during the rounding process... n If the filtered data is reduced by 10 times, then the data will be reduced by 10 times. n The filtered sensor data array is obtained by reducing each filtered data point by 10 times. n The filtered data is then multiplied by 10, and decimal places are removed to obtain first data corresponding to each of the filtered data sets. Based on the first data, the filtered sensor data array is obtained. That is, the filtered data can be reduced by 10. nThe filtered data can be multiplied by a factor of 1, but the reduced data may be non-integer, meaning it contains decimal places. In this case, the decimal places can be removed to obtain the first data. The first data corresponding to each filtered data point can be combined to form a filtered sensor data array.

[0079] According to the filtering method of the embodiments of this disclosure, specific elements within a filtering window can be determined based on the filtering size and filtering parameters. The elements within the filtering window are obtained based on a symmetry function, ensuring symmetry and simplifying filtering operations while reducing processing resource load. Furthermore, either rounding or normalization can be applied to the elements within the filtering window to ensure that the elements in the obtained filtering matrix are integers, further simplifying filtering operations and reducing processing resource load. Moreover, during the filtering of sensor data located at the edge of the sensor data array, the filtering window can be reduced, allowing the sensor data to be filtered using the reduced filtering window and neighboring data, improving the feasibility of filtering. During the filtering process, filtering can be performed using a filtering matrix with specific elements, improving filtering efficiency, reducing computational resource load, minimizing noise interference with touch signals, and enhancing the accuracy of touch event detection.

[0080] Figure 3A , Figure 3B , Figure 3C and Figure 3D This diagram illustrates an application of a filtering method according to an embodiment of the present disclosure, such as... Figure 3A The image shows sensor data from a 32×18 sensor data array. This sensor data is unfiltered and may contain noise signals. For example, a user's touch signal can be detected in the area from row 17, column 11 to row 22, column 17. That is, the sensor data in this area is significantly greater than the sensor data in other areas. The sensor data in each area may carry noise signals, which may affect the detection of touch signals.

[0081] In one possible implementation, such as Figure 3C As shown, Figure 3C Each broken line in the text can represent Figure 3A A column of data, with the column number indicated on the line. Figure 3C The vertical axis represents the numerical value of the sensor data. Figure 3C The x-axis represents the row number. For example... Figure 3CAs shown, although a large sensor data can be clearly detected in the area from row 17, column 11 to row 22, column 17, abnormal increases in sensor signals may be detected in other areas due to noise signals. For example, abnormal increases in sensor signals are detected in the area from row 8, column 1 to row 7, column 14, or in the areas from row 15, column 9 and row 30, column 8. These abnormal increases may be caused by noise signals and may affect the detection of touch signals.

[0082] In one possible implementation, such as Figure 3B As shown, it can be used for Figure 3A The sensor data in the sensor data array is filtered. In the example, a 3×3 filtering window can be used for filtering, and the row and column numbers are all -1, 0, 1, so that the values ​​of each element of the filtering window are determined based on the bivariate normal distribution function (i.e., formula (1)). Furthermore, each element in the filtering window can be magnified by 10. n The decimal places are removed and the integer places are retained for rounding. Based on the rounded filtering matrix, the data of each sensor in the sensor data array is filtered according to formula (3) to obtain filtered data. If the sensor data is located at the edge of the sensor data array, the filtering window can be reduced according to the position of the sensor data, and the corresponding terms in formula (3) can be reduced to obtain the filtering matrix through the reduced filtering window. The sensor data is then filtered based on the filtering matrix and the reduced formula (3). After obtaining the filtered data of each sensor data, the filtered data can be reduced by 10. n By multiplying the result by a factor of 1 and removing the decimal places, the filtered sensor data array can be obtained.

[0083] In one possible implementation, such as Figure 3D As shown, after filtering, the sensor data in the region from row 17, column 11 to row 22, column 17 is still accurately detected, indicating a touch signal. However, in the regions from row 8, column 1 to row 7, column 14, as well as in the regions from row 15, column 9 and row 30, column 8, the lines are relatively flat, which filters out abnormally amplified noise signals from the sensor signal, reducing their impact on touch signal detection.

[0084] In one possible implementation, the filtering method can be used in scenarios where sensor signals from a touchscreen are filtered, thereby filtering sensor data with high efficiency under a relatively small computational resource load, thus improving the accuracy of touch signal detection. This disclosure does not limit the application field of the filtering method; for example, the filtering method can also be used in fields where touch sensor signals from other fields are filtered, or in fields where other types of data arrays are filtered. This disclosure does not impose any limitations on these applications.

[0085] Figure 4 A block diagram of a filtering device according to an embodiment of the present disclosure is shown, such as Figure 4 As shown, the device includes: a parameter determination module 11, used to determine the size and filtering parameters of a filtering window for filtering sensor data arrays acquired by a sensor array, wherein the sensor array includes multiple touch sensors of a screen, the touch sensors are used to acquire sensor data in the sensor data array, and the filtering window is a matrix including multiple elements; an element determination module 12, used to determine the elements in the filtering window according to the filtering parameters; and a filtering module 13, used to filter the multiple sensor data in the sensor data array according to the size of the filtering window and the elements in the filtering window to obtain a filtered sensor data array.

[0086] In one possible implementation, the element determination module is further configured to: determine the elements within the filtering window based on the filtering parameters, a preset symmetry function, and the coordinates of the elements within the filtering window.

[0087] In one possible implementation, the preset symmetric function includes a bivariate normal distribution function.

[0088] In one possible implementation, the filtering module is further configured to: perform at least one of rounding and normalization processing on the elements within the filtering window to obtain a filtering matrix, wherein the size of the filtering window is equal to the size of the filtering matrix; determine the neighborhood data of the sensor data based on the size of the filtering window; obtain filtered data corresponding to the sensor data based on the sensor data, the neighborhood data, and the filtering matrix; and obtain the filtered sensor data array based on the filtered data.

[0089] In one possible implementation, the filtering module is further configured to: magnify each element within the filtering window by 10. n The integer part is multiplied by 1, and the decimal places are removed to obtain the rounded element, where n is a positive integer.

[0090] In one possible implementation, the filtering module is further configured to: reduce each of the filtered data by 10. n The first data is obtained by multiplying the data by a factor of 1 and removing the decimal places; based on the first data, the filtered sensor data array is obtained.

[0091] In one possible implementation, the filtering module is further configured to: when the sensor data is located at the edge of the sensor data array, reduce the elements in the filtering window according to the coordinates of the sensor data in the sensor data array, and perform at least one of rounding and normalization processing on the reduced elements to obtain a filtering matrix corresponding to the sensor data located at the edge of the sensor data array.

[0092] In one possible implementation, the filtering module is further configured to: determine the neighborhood data of the sensor data located at the edge of the sensor data array based on the size of the filtering window after element removal.

[0093] This disclosure also provides a display device, including a plurality of display units and a processor, wherein the display units include a sensor array, and the processor is configured to implement the filtering method by executing instructions.

[0094] In one possible implementation, the display unit includes a display panel, which includes at least one of a liquid crystal display panel, a micro light-emitting diode display panel, a light-emitting diode display panel, a mini light-emitting diode display panel, a quantum dot light-emitting diode display panel, an organic light-emitting diode display panel, a cathode ray tube display panel, a digital light processing display panel, a field emission display panel, a plasma display panel, an electrophoretic display panel, an electrowetting display panel, and a small-pitch display panel.

[0095] This disclosure also provides an electronic device, which includes the aforementioned display device. Exemplarily, the electronic device in this embodiment includes, but is not limited to, desktop computers, televisions, mobile devices with large screens such as mobile phones and tablets, and other common electronic devices that require multiple chips to be cascaded for operation.

[0096] For example, electronic devices can also be user equipment (UE), mobile devices, user terminals, terminals, handheld devices, computing devices, or in-vehicle devices, etc. Examples of terminals include: displays, smartphones or portable devices, mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, and wireless terminals in vehicle-to-everything (V2X) networks, etc. For example, a server can be a local server or a cloud server.

[0097] Figure 5 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. For example, the electronic device 1900 may be provided as a server or a terminal device. (Refer to...) Figure 5 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0098] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output (I / O) interface 1958. Electronic device 1900 can operate on an operating system stored in memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0099] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of an electronic device 1900 to perform the above-described method.

[0100] This disclosure also provides a driver chip for performing the filtering method.

[0101] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

[0102] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0103] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0104] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0105] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A filtering method, characterized by, The method comprises: determining a size of a filter window and filter parameters for filtering a sensor data array acquired by a sensor array, wherein the sensor array comprises a plurality of touch sensors of a screen, the touch sensors are used to acquire sensor data in the sensor data array, and the filter window is a matrix comprising a plurality of elements; determining an element in the filter window according to the filter parameters; filtering a plurality of sensor data in the sensor data array according to the size of the filter window and the element in the filter window, to obtain a filtered sensor data array; wherein determining the element in the filter window according to the filter parameters comprises: determining the element in the filter window according to the filter parameters, a preset symmetric function, and coordinates of the element in the filter window.

2. The method of claim 1, wherein, The preset symmetric function comprises a bivariate normal distribution function.

3. The method of claim 1, wherein, Filtering a plurality of sensor data in the sensor data array according to the size of the filter window and the element in the filter window, to obtain a filtered sensor data array, comprises: performing at least one of rounding and normalization processing on the element in the filter window to obtain a filter matrix, wherein the size of the filter window is equal to the size of the filter matrix; determining neighborhood data of the sensor data according to the size of the filter window; obtaining filter data corresponding to the sensor data according to the sensor data, the neighborhood data, and the filter matrix; obtaining the filtered sensor data array according to the filter data.

4. The method of claim 3, wherein, The rounding of the element in the filter window comprises: Each element in the filter window is enlarged by 10 n times, and the decimal places are removed to obtain an integral element, wherein n is a positive integer.

5. The method of claim 3, wherein, obtaining the filtered sensor data array according to the filter data, comprises: each of the filter data is reduced by 10 n times, and the decimal places are removed, to obtain first data corresponding to each of the filter data; obtaining the filtered sensor data array according to the first data.

6. The method of claim 3, wherein, The at least one of rounding and normalization processing on the element in the filter window to obtain a filter matrix comprises: in a case where the sensor data is located at an edge of the sensor data array, performing pruning on the element in the filter window according to coordinates of the sensor data in the sensor data array, and performing at least one of rounding and normalization processing on the pruned element to obtain a filter matrix corresponding to the sensor data located at the edge of the sensor data array.

7. The method of claim 6, wherein, Obtaining filter data corresponding to the sensor data according to the sensor data, the neighborhood data, and the filter matrix comprises: determining neighborhood data of the sensor data located at the edge of the sensor data array according to the size of the filter window after the pruning.

8. A filtering device, characterized in that The method comprises: a parameter determination module configured to determine a size of a filter window and filter parameters for filtering a sensor data array acquired by a sensor array, wherein the sensor array comprises a plurality of touch sensors of a screen, the touch sensors are used to acquire sensor data in the sensor data array, and the filter window is a matrix comprising a plurality of elements; an element determination module configured to determine an element in the filter window according to the filter parameters; filtering a plurality of sensor data in the sensor data array according to a size of the filter window and the elements within the filter window, to obtain a filtered sensor data array; The element determination module is further configured to determine the elements within the filter window according to the filter parameter, a preset symmetric function, and coordinates of the elements within the filter window.

9. A display device, characterized by The display unit comprises a display panel, and the display panel comprises at least one of a liquid crystal display panel, a micro light-emitting diode display panel, a light-emitting diode display panel, a mini light-emitting diode display panel, a quantum dot light-emitting diode display panel, an organic light-emitting diode display panel, a cathode ray tube display panel, a digital light processing display panel, a field emission display panel, a plasma display panel, an electrophoretic display panel, an electrowetting display panel, and a small-pitch display panel.

10. The display device of claim 9, wherein, The display unit comprises a display panel, and the display panel comprises at least one of a liquid crystal display panel, a micro light-emitting diode display panel, a light-emitting diode display panel, a mini light-emitting diode display panel, a quantum dot light-emitting diode display panel, an organic light-emitting diode display panel, a cathode ray tube display panel, a digital light processing display panel, a field emission display panel, a plasma display panel, an electrophoretic display panel, an electrowetting display panel, and a small-pitch display panel.

11. An electronic device comprising the display device according to claim 9 or 10.

12. A driver chip, characterized by comprising: The driving chip is configured to perform the filtering method according to any one of claims 1-7.

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