Wet hand touch recognition method and device, electronic equipment and medium

Abstract

The present disclosure relates to a wet hand touch recognition method and device, electronic equipment and medium, especially to the field of device control technology. In the wet hand touch capacitive screen, the current frame capacitance data is obtained, wherein the current frame capacitance data includes the capacitance data of each detection point on the capacitive screen at the current time. In the scenario of wet hand touch, the liquid on the screen will affect the recognition of the touch position, and generally the touch operation is continuous, so the historical capacitance data is obtained, wherein the historical capacitance data includes the capacitance data corresponding to a plurality of continuous historical frames, and the capacitance data corresponding to each historical frame includes the capacitance data of each detection point on the capacitive screen at the time corresponding to the frame. Then, the correction data is obtained according to the current frame capacitance data and the historical capacitance data. Then, the current frame capacitance data is corrected by using the correction data to obtain touch data, and the accurate touch position is obtained by using the touch data.

Description

Technical Field

[0001] This disclosure relates to the field of equipment control technology, and in particular to wet-hand touch recognition methods, devices, electronic equipment and media. Background Technology

[0002] When users interact with electronic devices, they typically do so through the device's display screen. In daily life, capacitive touchscreens are a common type of display. When using a capacitive touchscreen, the user touches it with their finger. The finger and the screen act as capacitor plates, forming a coupling capacitance that allows the device to pinpoint the touch location. However, when a user touches a capacitive touchscreen with wet hands, the liquid's conductivity causes it to act as the other plate of the coupling capacitance, altering the original capacitance value. This makes it difficult for the electronic device to accurately locate the touch location when hands are wet, thus hindering the accurate recognition of user input. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a wet-hand touch recognition method, device, electronic device, and medium.

[0004] According to a first aspect of the present disclosure, a wet-hand touch recognition method is provided. The method includes: when touching a capacitive screen, acquiring current frame capacitance data, wherein the current frame capacitance data includes capacitance data of each detection point on the capacitive screen at the current time; acquiring historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the time corresponding to that frame; obtaining correction data based on the current frame capacitance data and the historical capacitance data; correcting the current frame capacitance data based on the correction data to obtain touch data; and obtaining the touch position based on the touch data.

[0005] Optionally, obtaining correction data based on the current frame capacitance data and the historical capacitance data includes: obtaining the average capacitance value of capacitance data from multiple consecutive historical frames based on the historical capacitance data; and obtaining the correction data based on the difference between the current frame capacitance data and the average capacitance value.

[0006] Optionally, the step of correcting the current frame capacitance data based on the correction data to obtain touch data includes: extracting target capacitance data from the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the finger position on the capacitive screen and the capacitance data corresponding to the liquid position; and correcting the target capacitance data based on the correction data to obtain the touch data.

[0007] Optionally, the step of correcting the target capacitance data based on the correction data to obtain the touch data includes: obtaining the influence factor corresponding to the correction data; and correcting the target capacitance data based on the correction data and the influence factor to obtain the touch data.

[0008] Alternatively, correction can be performed using the following formula:

[0009] u=p′+k*d

[0010] Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

[0011] Optionally, the method further includes: inputting the current frame capacitance data into a trained recognizer to obtain the recognition result output by the trained recognizer; if the recognition result indicates that there is liquid on the capacitive screen, entering the liquid touch mode;

[0012] The acquisition of historical capacitance data includes: acquiring the historical capacitance data in the liquid touch mode.

[0013] Optionally, the method further includes: if the recognition result indicates that there is no liquid on the capacitive screen, then entering a normal recognition mode; in the normal recognition mode, obtaining the touch position based on the current frame capacitance data.

[0014] Optionally, training the recognizer includes: acquiring training samples, wherein the training samples include capacitance data of a wet-handed touchscreen and capacitance data of a non-wet-handed touchscreen; and training the recognizer using the training samples to obtain a trained recognizer.

[0015] According to a second aspect of the present disclosure, a wet-hand touch recognition device is provided. The device includes: a current frame capacitance data acquisition module, configured to acquire current frame capacitance data when touching a capacitive screen, wherein the current frame capacitance data includes capacitance data of each detection point on the capacitive screen at the current moment; a historical capacitance data acquisition module, configured to acquire historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the moment corresponding to that frame; a correction data acquisition module, configured to obtain correction data based on the current frame capacitance data and the historical capacitance data; a touch data acquisition module, configured to correct the current frame capacitance data based on the correction data to obtain touch data; and a position recognition module, configured to obtain a touch position based on the touch data.

[0016] Optionally, the correction data acquisition module includes: a mean acquisition submodule and a correction data acquisition submodule; the mean acquisition submodule is used to obtain the mean capacitance of capacitance data of multiple consecutive historical frames based on historical capacitance data; the correction data acquisition submodule is used to obtain the correction data based on the difference between the current frame capacitance data and the mean capacitance.

[0017] Optionally, the touch data acquisition module includes: an extraction submodule and a touch data acquisition submodule; the extraction submodule is used to extract target capacitance data from the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the finger position on the capacitive screen and the capacitance data corresponding to the liquid position; the touch data acquisition submodule is used to correct the target capacitance data according to the correction data to obtain the touch data.

[0018] Optionally, the touch data acquisition submodule includes: an influence factor acquisition submodule and a correction submodule; the influence factor acquisition submodule is used to acquire the influence factor corresponding to the correction data; the correction submodule is used to correct the target capacitance data according to the correction data and the influence factor to obtain the touch data.

[0019] Alternatively, correction can be performed using the following formula:

[0020] u=p′+k*d

[0021] Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

[0022] Optionally, the wet-hand touch recognition device further includes: a recognition module and a first mode control module; the recognition module is used to input the current frame capacitance data into a trained recognizer to obtain the recognition result output by the trained recognizer; the first mode control module is used to enter a liquid touch mode if the recognition result indicates that there is liquid on the capacitive screen; the historical capacitance data acquisition module includes: a historical capacitance data acquisition submodule; the historical capacitance data acquisition submodule is used to acquire the historical capacitance data in the liquid touch mode.

[0023] Optionally, the wet-hand touch recognition device further includes: a second mode control module and a touch position acquisition module; the second mode control module is used to enter a normal recognition mode if the recognition result indicates that there is no liquid on the capacitive screen; the touch position acquisition module is used to obtain the touch position based on the current frame capacitance data in the normal recognition mode.

[0024] Optionally, the wet-hand touch recognition device further includes: a sample acquisition module and a training module; the sample acquisition module is used to acquire training samples, wherein the training samples include capacitance data of wet-hand touch capacitive screens and capacitance data of non-wet-hand touch capacitive screens; the training module is used to train the recognizer through the training samples to obtain a trained recognizer.

[0025] According to a third aspect of the present disclosure, an electronic device is provided, the electronic device comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the steps of the wet-hand touch recognition method described in the first aspect.

[0026] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, having stored thereon computer program instructions that, when executed by a processor, implement the steps of the wet-hand touch recognition method provided in the first aspect of the present disclosure.

[0027] The wet-hand touch recognition method, apparatus, electronic device, and medium disclosed herein acquire current frame capacitance data when a capacitive screen is touched with wet hands. This current frame capacitance data includes capacitance data at each detection point on the capacitive screen at the current moment. In wet-hand touch scenarios, liquid on the screen can affect touch position recognition. Since touch operations are generally continuous, historical capacitance data is acquired. This historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, with each historical frame including capacitance data at each detection point on the capacitive screen at the corresponding moment. Then, correction data is obtained based on the current frame capacitance data and the historical capacitance data. The current frame capacitance data is then corrected using the correction data to obtain touch data, and the accurate touch position is obtained using the touch data.

[0028] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0029] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0030] Figure 1 A schematic flowchart of a wet-hand touch recognition method according to an embodiment of the present disclosure is shown;

[0031] Figure 2 This is a schematic diagram of the touch position;

[0032] Figure 3 This disclosure illustrates Figure 1 A flowchart illustrating step S130 of the wet-hand touch recognition method is shown.

[0033] Figure 4 This disclosure illustrates Figure 1 A flowchart illustrating step S140 of the wet-hand touch recognition method is shown.

[0034] Figure 5 A schematic flowchart of a wet-hand touch recognition method according to an embodiment of the present disclosure is shown;

[0035] Figure 6 A block diagram of a wet-hand touch recognition device according to an embodiment of the present disclosure is shown;

[0036] Figure 7 A block diagram of an electronic device for performing a wet-hand touch recognition method according to an embodiment of the present disclosure is shown. Detailed Implementation

[0037] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0038] Users typically interact with electronic devices through their displays, with capacitive touchscreens being a common type. When using a capacitive touchscreen, the user touches it with their finger. The finger and the screen act as capacitor plates, forming a coupling capacitor. Because the screen receives high-frequency signals, the finger absorbs a small current, which flows out from electrodes at the four corners of the screen. This current indicates the location of the finger's touch on the screen. With the increasing prevalence of IP67 / 68 waterproof ratings, this feature allows electronic devices to function in humid environments such as swimming, handwashing, rain, and bathrooms, or even when the user's hands are sweaty. However, when a user touches a capacitive touchscreen with wet hands, the liquid's conductivity allows it to act as another capacitor plate, altering the original capacitance and causing capacitance data distortion. Therefore, with wet hands, electronic devices are prone to reporting incorrect touch locations, making it difficult to accurately pinpoint the finger's touch position. This results in unresponsive scrolling and a poor user experience.

[0039] Existing technologies address the aforementioned problem by amplifying the filtering in conventional algorithms. However, this approach only works when there is a small amount of liquid on the screen. For slightly larger liquids, the filtering technology struggles to remove the interference. It is understandable that the filtering method is designed to remove interference from smaller areas, and existing methods cannot identify interference from larger areas. Therefore, existing technologies still cannot solve the aforementioned problem.

[0040] To address the aforementioned issues and accurately identify the user's touch position on the capacitive touchscreen of an electronic device when the user's hands are wet, this disclosure provides a wet-hand touch recognition method. This wet-hand touch recognition method can be applied to... Figure 6 The wet hand touch recognition device 100 shown Figure 7 The illustrated electronic device 800 and computer-readable storage medium are shown below. The following example uses a wet-hand touch recognition method applied to an electronic device. The electronic device can be a device with a capacitive screen, such as a smartphone, tablet, wearable device, or a navigation robot in a shopping mall. Please refer to [link to relevant documentation]. Figure 1 The wet-hand touch recognition method may include the following steps:

[0041] Step S110: When touching the capacitive screen, obtain the current frame capacitance data, wherein the current frame capacitance data includes the capacitance data of each detection point on the capacitive screen at the current moment.

[0042] In this system, the capacitive touchscreen of the electronic device is divided into multiple detection points. A frame of capacitance data can be understood as the data from all detection points on the touchscreen at the same time. Optionally, a frame of capacitance data can exist in the form of a matrix, for example, a 18*40 matrix or a 15*35 matrix, where each element in the matrix corresponds to the capacitance data at a specific location.

[0043] When a user uses an electronic device, they touch the controls on the capacitive touchscreen with their finger or slide it anywhere, obtaining the current frame capacitance data. This current frame capacitance data includes the capacitance data of all detection points on the capacitive touchscreen at the current moment, which can be understood as the moment the user touches the touchscreen. At detection points that are not touched by the finger or are dry, the sensed capacitance data is the capacitance value borne by the capacitive electrodes, which can be understood as the capacitance value of the screen itself, and this capacitance value is taken as the first capacitance value. At detection points touched by a dry finger, due to the human body's electric field, the user's finger and the screen surface form a coupling capacitor. The sensed capacitance data is the sum of the capacitance value borne by the capacitive electrodes and the capacitance value of this coupling capacitor, and this sum is taken as the second capacitance data. At detection points touched by wet hands, due to the conductivity of the liquid, the finger, screen, and liquid surface each form a coupling capacitor. The sensed capacitance data is the sum of the capacitance value borne by the capacitive electrodes and the capacitance value of the aforementioned coupling capacitor, and this sum is taken as the third capacitance data.

[0044] In the wet-hands scenario of this embodiment, the current frame capacitance data includes third capacitance data. In some scenarios, the current frame capacitance data also includes first capacitance data and / or second capacitance data.

[0045] If the touch position is identified solely based on the current frame's capacitance data, the maximum value among multiple capacitance values ​​in the current frame is determined, and the position corresponding to this maximum value is used as the touch position. For example, ... Figure 2 As shown, the touch position on the screen is point p1. However, when a user touches the capacitive screen with wet hands, the liquid on the screen affects the coupling capacitance, thus affecting the determination of the actual touch position, causing the electronic device to not respond or to the user's touch operation incorrectly. Therefore, it is necessary to continue with the following steps to obtain the actual touch position of the user's finger on the screen.

[0046] Step S120: Obtain historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the time corresponding to that frame.

[0047] The electronic device stores each frame of capacitance data generated during user operation as historical capacitance data, arranged chronologically by generation. The electronic device can directly retrieve this historical capacitance data from the storage location. This historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames; for example, it may include six frames of capacitance data.

[0048] To reduce storage pressure on electronic devices, in one implementation, the electronic device only stores historical capacitance data generated during the user's current usage cycle. Here, the period from the last screen activation to the current screen deactivation is considered one usage cycle; the current moment is understood as a single moment within that cycle. For example, if the electronic device activates its screen at 12:02 and deactivates it at 12:06, and the screen remains on between 12:02 and 12:06, this period is considered one usage cycle. During this cycle, historical capacitance data needs to be stored as long as the screen deactivation is not detected. When the screen deactivation is detected, the stored capacitance data is deleted to free up storage space for capacitance data generated in the next usage cycle.

[0049] In another approach, the electronic device stores the capacitance data sequentially into a storage location according to the generation time of each frame. When the number of capacitance data frames stored in the storage location exceeds M frames, the N frames of capacitance data preceding the M frames are deleted to free up space for the newly generated historical capacitance data. Here, M and N are both positive integers, and M is greater than N. For example, M is 50 frames and N is 30 frames.

[0050] Step S130: Obtain correction data based on the current frame capacitance data and the historical capacitance data.

[0051] When a user touches a capacitive touchscreen with a dry finger, the touch position can be directly determined using the collected capacitance data. However, when a user touches a capacitive touchscreen with wet hands, the liquid on the screen affects the coupling capacitance. The sensed capacitance data in this case differs from that sensed with dry hands, making the current frame capacitance data potentially inaccurate in reflecting the user's finger position. This can easily lead to touch operation failures or misoperations. Therefore, correction data is obtained based on the current frame capacitance data and historical capacitance data. This correction data is essentially the capacitance value. The correction data reflects the difference between the touch position represented by the current frame capacitance data and the actual touch position.

[0052] Step S140: Correct the current frame capacitance data according to the correction data to obtain touch data.

[0053] The capacitance data of the current frame is corrected based on the correction data to obtain touch data, which can be in matrix form. The obtained touch data reflects the actual position of the user's finger at the current moment.

[0054] Step S150: Obtain the touch position based on the touch data.

[0055] Touch data includes capacitance values ​​from multiple detection points. The maximum capacitance value is selected from these values, and the location corresponding to this maximum capacitance value on the screen is the touch position. For example, the touch position is... Figure 2 Point p2 in the middle.

[0056] After obtaining the touch location, the electronic device obtains the control corresponding to the touch location and responds to the user's touch on the control by executing the corresponding function.

[0057] The wet-hand touch recognition method provided in this embodiment acquires current frame capacitance data when a capacitive screen is touched with wet hands. This current frame capacitance data includes capacitance data at each detection point on the capacitive screen at the current moment. In wet-hand touch scenarios, liquid on the screen can affect touch position recognition. Since touch operations are generally continuous, historical capacitance data is acquired. This historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, with each historical frame including capacitance data at each detection point on the capacitive screen at the corresponding moment. Then, correction data is obtained based on the current frame capacitance data and the historical capacitance data. The current frame capacitance data is then corrected using the correction data to obtain touch data. The accurate touch position is then obtained using the touch data. Compared to existing filtering algorithms, this method can accurately identify the touch position even when the liquid area is relatively large, thus accurately responding to user touch operations and avoiding issues such as choppy or laggy operation, ensuring a better user experience.

[0058] In one implementation, such as Figure 3 As shown, step S130 above includes the following sub-steps:

[0059] Sub-step S131: Based on historical capacitance data, obtain the average capacitance value of capacitance data from multiple consecutive historical frames.

[0060] The acquired historical capacitance data includes multiple consecutive historical frames; for example, the historical capacitance data includes six consecutive historical frames. Each historical frame includes multiple capacitance data points. Optionally, each historical frame can be in the form of a matrix, where each element of the matrix represents the capacitance data at a location. For example, a historical frame can be an 18*40 matrix.

[0061] Calculate the average capacitance value from the capacitance data of multiple historical frames. For example, based on the capacitance data corresponding to each of the multiple historical frames, calculate the average capacitance data at the same position on the screen, and use the average values ​​of all positions as the total capacitance value. In the example above, since the multiple historical frames form an 18*40 matrix, the average capacitance value calculated in this step is also an 18*40 matrix.

[0062] Sub-step S132: Obtain the correction data based on the difference between the current frame capacitance data and the average capacitance value.

[0063] Calculate the difference between the current frame capacitance data and the average capacitance value, and use this difference as the correction data d.

[0064] In this embodiment, the user's swipe operation on the capacitive screen is generally continuous. Therefore, the capacitance data of historical frames and the current frame are related. The capacitance data of multiple consecutive historical frames are obtained, and their average value is calculated to obtain the capacitance average value. Based on the difference between the capacitance data of the current frame and the capacitance average value, correction data is obtained. The capacitance data of the current frame can be corrected using this correction data.

[0065] In one implementation, such as Figure 4 As shown, step S140 above includes the following sub-steps:

[0066] Sub-step S141: Extract the target capacitance data from the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the position of the finger on the capacitive screen and the capacitance data corresponding to the position of the liquid.

[0067] Extract the target capacitance data from the current frame capacitance data. The location of the target capacitance data can be understood as the location on the screen where the user's finger touches or where there is liquid.

[0068] As one approach, the electronic device uses a breadth-first search algorithm to find connected components in the current frame's capacitance data. These connected components can be understood as the location of the target capacitance data. Then, a masking algorithm is used to block out data outside the connected components in the current frame's capacitance data, thus extracting the target capacitance data. Specifically, the masking algorithm multiplies the data outside the connected components in the current frame's capacitance data by 0 to eliminate this data. Conversely, it multiplies the data within the connected components by 1 to retain the data within those components.

[0069] Sub-step S142: Correct the target capacitance data according to the correction data to obtain the touch data.

[0070] One approach is to obtain the influence factor k corresponding to the correction data d. Optionally, the influence factor k may be related to factors such as the magnitude of the correction data d, the material of the capacitive screen, and the sensitivity of the capacitive screen. Then, the target capacitance data is corrected based on the correction data and the influence factor to obtain the touch data.

[0071] Alternatively, correction can be performed using the following formula:

[0072] u=p′+k*d

[0073] Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

[0074] Based on the above embodiments, the electronic device's operating modes include a liquid touch mode and a normal mode. When touching the capacitive screen in a dry condition, the electronic device operates in normal mode. When touching the capacitive screen with wet hands, the electronic device operates in liquid touch mode. This embodiment also provides a wet-hand touch recognition method, such as... Figure 5 As shown, the wet-hand touch recognition method may include the following steps:

[0075] Step S210: When touching the capacitive screen, obtain the current frame capacitance data, wherein the current frame capacitance data includes the capacitance data of each detection point on the capacitive screen at the current moment.

[0076] In this embodiment, the specific description of step S210 can be referred to step S110 in the above embodiment, and will not be repeated here.

[0077] Step S220: Input the current frame capacitance data into the trained recognizer to obtain the recognition result output by the trained recognizer.

[0078] The pre-trained recognizer can be trained using the following methods to obtain training samples, wherein the training samples include capacitance data of a wet-handed touchscreen and capacitance data of a non-wet-handed touchscreen. The recognizer is then trained using these training samples to obtain a trained recognizer. For example, the recognizer can be iteratively trained using training samples according to a preset number of iterations to obtain a trained recognizer. Another example is to calculate a loss function during training and iteratively train the recognizer using training samples until the loss function converges to obtain a trained recognizer.

[0079] The current frame's capacitance data is input into a trained recognizer to obtain the recognition result output by the trained recognizer. Optionally, the recognition result can be 0 or 1. When the recognition result is 0, it indicates that there is no liquid on the capacitive screen. Alternatively, when the recognition result is 1, it indicates that there is liquid on the capacitive screen.

[0080] If the recognition result indicates that there is no liquid on the capacitive screen, then the system enters the normal recognition mode. In the normal recognition mode, interference from liquid is not considered, and the touch position is obtained directly based on the current frame capacitance data.

[0081] Step S230: If the recognition result indicates that there is liquid on the capacitive screen, enter the liquid touch mode.

[0082] If the recognition result indicates the presence of liquid on the capacitive screen, the system enters liquid touch mode. Position correction is required in liquid touch mode.

[0083] Step S240: In the liquid touch mode, acquire the historical capacitance data.

[0084] The electronic device stores each frame of capacitance data generated during user operation as historical capacitance data, arranged chronologically by generation. In liquid touch mode, the electronic device can directly retrieve the historical capacitance data from the storage location. This historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames; for example, it may include six frames of capacitance data.

[0085] Step S250: Obtain correction data based on the current frame capacitance data and the historical capacitance data.

[0086] Step S260: Correct the current frame capacitance data according to the correction data to obtain touch data.

[0087] Step S270: Obtain the touch position based on the touch data.

[0088] In this embodiment, the specific description of steps S250 to S270 can be referred to steps S130 to S150 in the above embodiment, and will not be repeated here.

[0089] In this embodiment, when liquid is present on the capacitive screen, the system enters a liquid touch mode and identifies the touch location using the liquid mode's methods. When there is no liquid on the capacitive screen, the system enters a normal mode, where liquid interference is not considered, and the touch location is directly identified. Using different operations in different modes ensures the accuracy of touch location recognition.

[0090] To implement the above-described method embodiments, this disclosure also provides a wet-hand touch recognition device. Please refer to [link to relevant documentation]. Figure 6 The wet-hand touch recognition device 100 includes: a current frame capacitance data acquisition module 110, a historical capacitance data acquisition module 120, a correction data acquisition module 130, a touch data acquisition module 140, and a position recognition module 150.

[0091] The current frame capacitance data acquisition module 110 is used to acquire current frame capacitance data when touching the capacitive screen, wherein the current frame capacitance data includes capacitance data of each detection point on the capacitive screen at the current moment.

[0092] The historical capacitance data acquisition module 120 is used to acquire historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the time corresponding to that frame.

[0093] The correction data acquisition module 130 is used to obtain correction data based on the current frame capacitance data and the historical capacitance data;

[0094] The touch data acquisition module 140 is used to correct the current frame capacitance data based on the correction data to obtain touch data;

[0095] The position recognition module 150 is used to obtain the touch position based on the touch data.

[0096] Optionally, the calibration data acquisition module 130 includes: a mean acquisition submodule and a calibration data acquisition submodule.

[0097] The mean value acquisition submodule is used to obtain the mean value of capacitance data from multiple consecutive historical frames based on historical capacitance data.

[0098] The correction data acquisition submodule is used to obtain the correction data based on the difference between the current frame capacitance data and the average capacitance value.

[0099] Optionally, the touch data acquisition module 140 includes an extraction submodule and a touch data acquisition submodule.

[0100] The extraction submodule is used to extract the target capacitance data in the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the position of the finger on the capacitive screen and the capacitance data corresponding to the position of the liquid.

[0101] The touch data acquisition submodule is used to correct the target capacitance data based on the correction data to obtain the touch data.

[0102] Optionally, the touch data acquisition submodule includes: an impact factor acquisition submodule and a correction submodule.

[0103] The impact factor acquisition submodule is used to acquire the impact factor corresponding to the corrected data;

[0104] The correction submodule is used to correct the target capacitance data based on the correction data and the influence factor to obtain the touch data.

[0105] Alternatively, correction can be performed using the following formula:

[0106] u=p′+k*d

[0107] Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

[0108] Optionally, the wet-hand touch recognition device 100 further includes a recognition module and a first mode control module.

[0109] The recognition module is used to input the current frame capacitance data into a trained recognizer and obtain the recognition result output by the trained recognizer.

[0110] The first mode control module is used to enter the liquid touch mode if the recognition result indicates that there is liquid on the capacitive screen.

[0111] The historical capacitance data acquisition module 120 includes: a historical capacitance data acquisition submodule;

[0112] The historical capacitance data acquisition submodule is used to acquire the historical capacitance data in the liquid touch mode.

[0113] Optionally, the wet-hand touch recognition device 100 further includes a second mode control module and a touch position acquisition module.

[0114] The second mode control module is used to enter the normal recognition mode if the recognition result indicates that there is no liquid on the capacitive screen.

[0115] A touch position acquisition module is used to obtain the touch position based on the current frame capacitance data in the normal recognition mode.

[0116] Optionally, the wet-hand touch recognition device 100 also includes a sample acquisition module and a training module.

[0117] The sample acquisition module is used to acquire training samples, wherein the training samples include capacitance data of a wet-handed touch capacitive screen and capacitance data of a non-wet-handed touch capacitive screen.

[0118] The training module is used to train the recognizer using the training samples to obtain the trained recognizer.

[0119] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0120] This disclosure also provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the steps of the wet-hand touch recognition method provided in this disclosure.

[0121] Figure 7A block diagram of an electronic device for performing a wet-hand touch recognition method according to an embodiment of this application is shown. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0122] Reference Figure 7 The electronic device 800 may include one or more of the following components: processing component 802, memory 804, power supply component 806, multimedia component 808, audio component 810, input / output interface 812, sensor component 814, and communication component 816.

[0123] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0124] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of this data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0125] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0126] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0127] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0128] Input / output interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0129] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0130] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0131] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0132] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0133] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the wet-hand touch recognition method described above when executed by the programmable device.

[0134] In summary, the wet-hand touch recognition method, apparatus, electronic device, and medium disclosed herein acquire current frame capacitance data when a capacitive screen is touched with wet hands. This current frame capacitance data includes capacitance data at each detection point on the capacitive screen at the current moment. In wet-hand touch scenarios, liquid on the screen can affect touch position recognition. Since touch operations are generally continuous, historical capacitance data is acquired. This historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, with each historical frame including capacitance data at each detection point on the capacitive screen at the moment corresponding to that frame. Then, correction data is obtained based on the current frame capacitance data and the historical capacitance data. The current frame capacitance data is then corrected using the correction data to obtain touch data, and the accurate touch position is obtained using the touch data.

[0135] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of this disclosure. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0136] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A wet-hand touch recognition method, characterized in that, The method includes: When touching a capacitive touchscreen, the current frame capacitance data is acquired, wherein the current frame capacitance data includes the capacitance data of each detection point on the capacitive touchscreen at the current moment; Acquire historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the time corresponding to that frame. Based on historical capacitance data, obtain the average capacitance value of capacitance data from multiple consecutive historical frames; Correction data is obtained based on the difference between the current frame capacitance data and the average capacitance value; The current frame capacitance data is corrected based on the correction data to obtain touch data, wherein the touch data includes capacitance values ​​of multiple detection points; The touch position is obtained based on the touch data.

2. The method according to claim 1, characterized in that, The step of correcting the current frame capacitance data based on the correction data to obtain touch data includes: Extract the target capacitance data from the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the position of the finger on the capacitive screen and the capacitance data corresponding to the position of the liquid. The target capacitance data is corrected based on the correction data to obtain the touch data.

3. The method according to claim 2, characterized in that, The step of correcting the target capacitance data based on the correction data to obtain the touch data includes: Obtain the impact factor corresponding to the corrected data; The target capacitance data is corrected based on the correction data and the influence factor to obtain the touch data.

4. The method according to claim 3, characterized in that, Correction is performed using the following formula: Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

5. The method according to claim 1, characterized in that, The method further includes: The current frame capacitance data is input into the trained recognizer to obtain the recognition result output by the trained recognizer; If the recognition result indicates that there is liquid on the capacitive screen, the liquid touch mode is entered. The acquisition of historical capacitance data includes: In the liquid touch mode, the historical capacitance data is acquired.

6. The method according to claim 5, characterized in that, The method further includes: If the recognition result indicates that there is no liquid on the capacitive screen, then the normal recognition mode is entered; In the normal recognition mode, the touch position is obtained based on the current frame capacitance data.

7. The method according to claim 6, characterized in that, Training the recognizer includes: Obtain training samples, wherein the training samples include capacitance data of a wet-handed touch capacitive screen and capacitance data of a non-wet-handed touch capacitive screen; The trained recognizer is obtained by training the recognizer using the training samples.

8. A wet-hand touch recognition device, characterized in that, The wet hand touch recognition device includes: The current frame capacitance data acquisition module is used to acquire current frame capacitance data when the touch capacitive screen is touched, wherein the current frame capacitance data includes capacitance data of each detection point on the capacitive screen at the current moment; The historical capacitance data acquisition module is used to acquire historical capacitance data, wherein the historical capacitance data includes capacitance data corresponding to multiple consecutive historical frames, and the capacitance data corresponding to each historical frame includes capacitance data of each detection point on the capacitive screen at the time corresponding to that frame. A correction data acquisition module is used to obtain correction data based on the current frame capacitance data and the historical capacitance data. The correction data acquisition module includes an average value acquisition submodule and a correction data acquisition submodule. The mean value acquisition submodule is used to obtain the mean value of capacitance data from multiple consecutive historical frames based on historical capacitance data. The correction data acquisition submodule is used to obtain the correction data based on the difference between the current frame capacitance data and the average capacitance value. A touch data acquisition module is used to correct the current frame capacitance data based on the correction data to obtain touch data, wherein the touch data includes capacitance values ​​of multiple detection points; The location recognition module is used to obtain the touch location based on the touch data.

9. The apparatus according to claim 8, characterized in that, The touch data acquisition module includes: an extraction submodule and a touch data acquisition submodule; The extraction submodule is used to extract target capacitance data from the current frame capacitance data, wherein the target capacitance data is the capacitance data corresponding to the finger position on the capacitive screen and the capacitance data corresponding to the liquid position. The touch data acquisition submodule is used to correct the target capacitance data based on the correction data to obtain the touch data.

10. The apparatus according to claim 9, characterized in that, The touch data acquisition submodule includes: an impact factor acquisition submodule and a correction submodule; The impact factor acquisition submodule is used to acquire the impact factor corresponding to the corrected data; The correction submodule is used to correct the target capacitance data according to the correction data and the influence factor to obtain the touch data.

11. The apparatus according to claim 10, characterized in that, Correction is performed using the following formula: Where u is the touch data, p' is the target capacitance data, k is the influence factor, and d is the correction data.

12. The apparatus according to claim 8, characterized in that, The wet-hand touch recognition device further includes: a recognition module and a first mode control module; The recognition module is used to input the current frame capacitance data into a trained recognizer to obtain the recognition result output by the trained recognizer. The first mode control module is used to enter the liquid touch mode if the recognition result indicates that there is liquid on the capacitive screen; The historical capacitance data acquisition module includes: a historical capacitance data acquisition submodule; The historical capacitance data acquisition submodule is used to acquire the historical capacitance data in the liquid touch mode.

13. The apparatus according to claim 12, characterized in that, The wet hand touch recognition device also includes: a second mode control module and a touch position acquisition module; The second mode control module is used to enter the normal recognition mode if the recognition result indicates that there is no liquid on the capacitive screen; The touch position acquisition module is used to obtain the touch position based on the current frame capacitance data in the normal recognition mode.

14. The apparatus according to claim 13, characterized in that, The wet-hand touch recognition device also includes: a sample acquisition module and a training module; The sample acquisition module is used to acquire training samples, wherein the training samples include capacitance data of a wet-handed touch capacitive screen and capacitance data of a non-wet-handed touch capacitive screen. The training module is used to train the recognizer using the training samples to obtain the trained recognizer.

15. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the steps of the method according to any one of claims 1 to 7.

16. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When executed by a processor, the program instructions implement the steps of the method described in any one of claims 1 to 7.

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