TWI842551B - Capacitive touch area recognition method, touch device and information processing device - Google Patents

Abstract

A capacitive touch region recognition method is implemented by a control circuit and includes: obtaining a frame of capacitance sensing data from a capacitance sensor array and dividing the frame of capacitance sensing data into multiple sub-regions; using a gradient operator to perform a convolution calculation on each of the sub-regions to obtain a representative gradient of each of the sub-regions; and finding a target gradient with a maximum length among the representative gradients, determining a threshold value according to a ratio of the maximum length, comparing the threshold value with the lengths of the representative gradients to find multiple valid gradients with lengths greater than the threshold value, and determining at least one touch region according to the corresponding positions of the valid gradients in the frame of capacitance sensing data.

Description

Capacitive touch area identification method, touch device and information processing device

The present invention relates to a touch detection method, and more particularly to a capacitive touch area recognition method.

With the development of materials and electronic technology, capacitive touch screens have been widely used in mobile phones, computers, touch panels, touch buttons and other products. Capacitive touch screens are composed of capacitive sensor arrays and control circuits. The capacitive sensor array is embedded in the screen. When a finger or capacitive pen touches it, its capacitance changes. The control circuit mainly includes sensor drive and acquisition, data processing and other modules, which are generally composed of chips and peripheral circuits. During operation, the control circuit will periodically drive and collect the capacitance value of each capacitance sensor. The collected capacitance value data is stored in the memory in the form of a matrix or array. The control circuit processes the capacitance value data and divides the touch area, and then calculates the touch position coordinates based on the touch area.

In order to improve the accuracy and efficiency of touch recognition, there are touch recognition solutions based on the regional growth theory in the prior art, which use a combination of fixed threshold and dynamic threshold to perform multiple recursive processing on the capacitance data to generate the touch area. However, it still has the disadvantages of low recognition efficiency, heavy reliance on experience in threshold selection, and poor adaptability to different screens.

In order to solve the above problems, a novel capacitive touch area recognition method is urgently needed in the art.

One purpose of the present invention is to disclose a capacitive touch area recognition method, which can accurately identify and divide the touch area through a low-complexity processing procedure.

Another object of the present invention is to disclose a capacitive touch area recognition method that can be applied to different screens through a highly universal processing procedure.

Another object of the present invention is to disclose a touch device that can improve touch detection efficiency through the aforementioned method, thereby improving the operator's experience.

Another object of the present invention is to disclose an information processing device that can improve the touch detection efficiency by using the aforementioned touch device, thereby improving the operator's experience.

To achieve the above-mentioned purpose, a capacitive touch region identification method is proposed, which is implemented by a control circuit and includes: obtaining a frame of capacitance sensing data from a capacitance sensor array and dividing the frame of capacitance sensing data into multiple sub-regions; using a gradient operator to perform a convolution calculation on each of the sub-regions to obtain a representative gradient of each sub-region; and finding a target gradient with a maximum length among the representative gradients, determining a threshold value according to a ratio of the maximum length, comparing the threshold value with the lengths of the representative gradients to find multiple valid gradients with a length greater than the threshold value, and determining at least one touch region according to the corresponding positions of the valid gradients in the frame of capacitance sensing data.

In one embodiment, the capacitive touch area recognition method further includes: performing a weighted average operation on each touch area to obtain an equivalent touch coordinate of each touch area.

In possible embodiments, the gradient operator may be a Roberts operator, a Sobel operator, a Prewitt operator, a Marr-Hildreth operator or a Canny operator.

In one embodiment, the ratio value is a positive real number less than 1.

To achieve the aforementioned purpose, the present invention further proposes a touch device having a capacitance sensor array and a control circuit, wherein the control circuit is used to execute a capacitive touch area identification procedure, and the capacitive touch area identification procedure includes: Obtaining a frame of capacitance sensing data from the capacitance sensor array, and dividing the frame of capacitance sensing data into a plurality of sub-areas; Using a gradient operator to perform a convolution calculation on each of the sub-areas to obtain a representative gradient of each of the sub-areas; and Find a target gradient with a maximum length among the representative gradients, determine a threshold value according to a ratio value of the maximum length, compare the threshold value with the lengths of the representative gradients to find multiple effective gradients with lengths greater than the threshold value, and determine at least one touch area according to the corresponding positions of the effective gradients in the frame of capacitance sensing data.

In one embodiment, the capacitive touch area recognition method further includes: performing a weighted average operation on each of the touch areas to obtain an equivalent touch coordinate of each of the touch areas.

In possible embodiments, the gradient operator may be a Roberts operator, a Sobel operator, a Prewitt operator, a Marr-Hildreth operator or a Canny operator.

In one embodiment, the ratio value is a positive real number less than 1.

To achieve the aforementioned object, the present invention further proposes an information processing device having a central processing unit and the aforementioned touch device, wherein the central processing unit is used to communicate with the touch device.

In possible embodiments, the information processing device may be a smart phone, a portable computer or a car computer.

In order to enable the Review Committee to further understand the structure, features, purpose, and advantages of the present invention, the following are attached with drawings and detailed descriptions of preferred specific embodiments.

The principle of the present invention is:

(1) Dividing a frame of capacitance sensing data into multiple sub-areas;

(2) performing a gradient operation on each of the sub-regions to obtain a representative gradient for each of the sub-regions;

(iii) finding a target gradient having a maximum length among the representative gradients, and determining a threshold value according to a ratio value of the maximum length;

(iv) comparing the threshold value with the lengths of the representative gradients to find a plurality of effective gradients having lengths greater than the threshold value, and determining at least one touch region according to corresponding positions of the effective gradients in the frame of capacitance sensing data; and

(V) Performing a weighted average operation on each touch area to obtain an equivalent touch coordinate of each touch area.

Accordingly, the present invention can improve the touch detection efficiency and can be applied to touch screens of different sizes.

Please refer to FIG. 1, which shows a block diagram of an embodiment of the touch device of the present invention. As shown in FIG. 1, a touch device 100 has a capacitive sensor array 110 and a control circuit 120, wherein the control circuit 120 is used to execute a capacitive touch area recognition procedure, and the capacitive touch area recognition procedure includes:

(i) The control circuit 120 obtains a frame of capacitance sensing data D _CAP from the capacitance sensor array 110 and divides the frame of capacitance sensing data D _CAP into a plurality of sub-regions;

(ii) the control circuit 120 uses a gradient operator to perform a convolution calculation on each of the sub-regions to obtain a representative gradient of each of the sub-regions;

(iii) the control circuit 120 finds a target gradient with a maximum length among the representative gradients, and determines a threshold value according to a ratio value of the maximum length;

(iv) the control circuit 120 compares the lengths of the representative gradients with the threshold value to find out a plurality of effective gradients whose lengths are greater than the threshold value, and determines at least one touch area according to corresponding positions of the effective gradients in the frame of capacitance sensing data D _CAP ; and

(V) Performing a weighted average operation on each touch area to obtain an equivalent touch coordinate of each touch area.

In detail, the gradient operator (also called convolution kernel) can be an existing Roberts operator, Sobel operator, Prewitt operator, Marr-Hildreth operator or Canny operator. Taking the Roberts operator as an example, the Roberts operator is divided into a horizontal operator S _x and a vertical operator _Sy , as shown below:

, .

Assume that the original data of the 2*2 sub-area is , then the 2*2 original data and the Roberts operator can be used to obtain the data representing the gradient of the sub-region (G _x , G _y ) through convolution calculation, and the formula is as follows: .

In addition, the lengths G representing the gradients can be expressed as:

.

Next, the control circuit 120 finds a target gradient with a maximum length G _max among the representative gradients, and determines the threshold value according to a ratio of the maximum length G _max . For example, the threshold value may be equal to 0.5*G _max .

Next, the control circuit 120 compares the threshold (0.5*G _max ) with the lengths G of the representative gradients to find out a plurality of effective gradients whose lengths are greater than the threshold, and determines at least one touch region according to corresponding positions of the effective gradients in the frame of capacitance sensing data D _CAP .

In addition, since the Sobel operator, Prewitt operator, Marr-Hildreth operator and Canny operator are all known techniques, they are not described in detail here.

As can be seen from the above, the present invention discloses a capacitive touch area recognition method. Please refer to FIG2, which shows a flow chart of an embodiment of the capacitive touch area recognition method of the present invention, which is implemented by a control circuit. As shown in FIG2, the method includes: obtaining a frame of capacitance sensing data from a capacitance sensor array, and dividing the frame of capacitance sensing data into a plurality of sub-areas (step a); using a gradient operator to perform a convolution calculation on each of the sub-areas to obtain a representative gradient for each of the sub-areas (step b); finding a target gradient with a maximum length among the representative gradients, and dividing the target gradient according to the maximum length. A ratio value is used to determine a threshold value (step c); the threshold value is compared with the lengths of the representative gradients to find a plurality of effective gradients whose lengths are greater than the threshold value, and at least one touch area is determined according to the corresponding positions of the effective gradients in the frame of capacitance sensing data (step d); and a weighted average operation is performed on each of the touch areas to obtain an equivalent touch coordinate of each of the touch areas (step e).

In the above steps, the gradient operator can be an existing Roberts operator, Sobel operator, Prewitt operator, Marr-Hildreth operator or Canny operator. In addition, the ratio value can be a positive real number less than 1.

According to the above description, the present invention further proposes an information processing device. Please refer to FIG. 3, which shows a block diagram of an embodiment of the information processing device of the present invention. As shown in FIG. 3, an information processing device 200 has a central processing unit 210 and a touch device 220, wherein the touch device 220 is implemented by the touch device 100, and the central processing unit 210 is used to communicate with the touch device 220 to receive touch coordinate data.

In addition, the information processing device 200 may be a smart phone, a portable computer or a car computer.

Through the above disclosed design, the present invention has the following advantages:

1. The capacitive touch area recognition method of the present invention can accurately identify and divide the touch area through a low-complexity processing procedure.

2. The capacitive touch area recognition method of the present invention can be applied to different screens through a highly universal processing procedure.

3. The touch device of the present invention can improve the touch detection efficiency through the aforementioned method, thereby improving the operator's experience.

4. The information processing device of the present invention can improve the touch detection efficiency through the aforementioned touch device, thereby improving the operator's experience.

The invention disclosed in this case is a preferred embodiment. Any partial changes or modifications that are derived from the technical concept of this case and are easily inferred by people familiar with the art do not deviate from the scope of the patent rights of this case.

In summary, this case shows that its purpose, means and effects are all different from the known technology, and it is the first invention that is practical and indeed meets the patent requirements for invention. We sincerely request the review committee to examine this carefully and grant a patent as soon as possible to benefit the society. This is our utmost prayer.

100: Touch device 110: Capacitor sensor array 120: Control circuit 200: Information processing device 210: Central processing unit 220: Touch device Step a: Obtain a frame of capacitance sensing data from a capacitor sensor array, and divide the frame of capacitance sensing data into multiple sub-regions. Step b: Perform a convolution calculation on each of the sub-regions using a gradient operator to obtain a representative gradient for each of the sub-regions. Step c: Find a target gradient with a maximum length among the representative gradients, and determine a threshold value according to a ratio of the maximum length. Step d: Compare the threshold value with the lengths of the representative gradients to find multiple effective gradients whose lengths are greater than the threshold value, and determine at least one touch area according to the corresponding positions of the effective gradients in the frame of capacitance sensing data. Step e: Perform a weighted average operation on each of the touch areas to obtain the equivalent touch coordinates of each of the touch areas.

FIG. 1 is a block diagram of an embodiment of a touch device of the present invention. FIG. 2 is a flow chart of an embodiment of a capacitive touch area identification method of the present invention. FIG. 3 is a block diagram of an embodiment of an information processing device of the present invention.

Step a: Obtain a frame of capacitance sensing data from a capacitance sensor array, and divide the frame of capacitance sensing data into multiple sub-areas

Step b: Use a gradient operator to perform a convolution calculation on each sub-region to obtain a representative gradient for each sub-region.

Step c: Find a target gradient with a maximum length among the representative gradients, and determine a threshold value according to a ratio of the maximum length

Step d: Compare the threshold value with the lengths of the representative gradients to find multiple effective gradients whose lengths are greater than the threshold value, and determine at least one touch area according to the corresponding positions of the effective gradients in the frame of capacitance sensing data

Step e: Perform a weighted average operation on each touch area to obtain the equivalent touch coordinates of each touch area.

Claims (10)

A capacitive touch region identification method is implemented by a control circuit and includes: Obtaining a frame of capacitance sensing data from a capacitance sensor array and dividing the frame of capacitance sensing data into multiple sub-regions; Using a gradient operator to perform a convolution calculation on each of the sub-regions to obtain a representative gradient for each of the sub-regions; and Finding a target gradient with a maximum length among the representative gradients, determining a threshold value according to a ratio of the maximum length, comparing the threshold value with the lengths of the representative gradients to find multiple valid gradients with lengths greater than the threshold value, and determining at least one touch region according to the corresponding positions of the valid gradients in the frame of capacitance sensing data. The capacitive touch area identification method as described in claim 1 further includes: performing a weighted average operation on each touch area to obtain an equivalent touch coordinate of each touch area. A capacitive touch area recognition method as described in claim 1, wherein the gradient operator is an operator selected from a group consisting of Roberts operators, Sobel operators, Prewitt operators, Marr-Hildreth operators and Canny operators. A capacitive touch area identification method as described in claim 1, wherein the ratio value is a positive real number less than 1. A touch device has a capacitance sensor array and a control circuit, wherein the control circuit is used to execute a capacitive touch area identification procedure, the capacitive touch area identification procedure comprising: Obtaining a frame of capacitance sensing data from the capacitance sensor array, and dividing the frame of capacitance sensing data into a plurality of sub-areas; Using a gradient operator to perform a convolution calculation on each of the sub-areas to obtain a representative gradient of each of the sub-areas; and Find a target gradient with a maximum length among the representative gradients, determine a threshold value according to a ratio value of the maximum length, compare the threshold value with the lengths of the representative gradients to find multiple effective gradients with lengths greater than the threshold value, and determine at least one touch area according to the corresponding positions of the effective gradients in the frame of capacitance sensing data. The touch device as described in claim 5, wherein the capacitive touch area identification method further includes: performing a weighted average operation on each of the touch areas to obtain equivalent touch coordinates of each of the touch areas. A touch control device as described in claim 5, wherein the gradient operator is an operator selected from a group consisting of Roberts operator, Sobel operator, Prewitt operator, Marr-Hildreth operator and Canny operator. A touch device as described in claim 5, wherein the ratio value is a positive real number less than 1. An information processing device having a central processing unit and a touch device as described in any one of claims 5 to 8, wherein the central processing unit is used to communicate with the touch device. The information processing device as described in claim 9 is a device selected from the group consisting of a smart phone, a portable computer and a car computer.

Images