Touch response speed increasing scheme

Abstract

The invention discloses a touch response speed increasing scheme, which comprises the following steps of: setting a reference image A and initializing the reference image A into a blank image, and setting each frame of real-time image B and initializing the real-time image B into a blank image; setting an unqualified light intensity threshold value t; setting a row number M and a column number N; the method comprises the following steps: drawing a reference image A by using all qualified light paths of a full screen, dividing the reference image A and a real-time image B into M * N matrix small areas according to a rule of M rows and N columns of the full screen, dividing the full screen into a plurality of small areas by establishing the reference image during initialization, and recording a light path set passing through each small area and each small area in an associated manner; the method comprises the following steps: quickly judging each small area of each frame to obtain whether each small area has a blocked light path or not and the ratio characteristic of the number of the blocked light paths to the number of all light paths passed by the small area, and quickly generating different small area images in a classified manner, thereby effectively reducing the time consumption for forming the most critical real-time image of each frame and improving the real-time image forming efficiency. The speed of the whole image algorithm is improved, and a foundation is laid for drive-free application of the image algorithm.

Description

Technical Field

[0001] The present invention belongs to the technical field of touch screen algorithms, and particularly relates to a scheme for accelerating the touch response speed. Background Art

[0002] Traditional infrared touch screen image processing algorithms have advantages such as high precision and low touch height, but there are problems of large computational amount and slow speed caused by drawing each frame of real-time image by each light path. Therefore, mainstream image processing algorithms all adopt driving algorithms to deal with (the lower computer only performs scanning and compression transmission due to limited main frequency and storage capacity, and the upper computer performs compression data parsing and image algorithm operations). However, traditional image processing algorithms need to be re-developed in the Android / Windows driver layer, resulting in problems such as increased development difficulty and entanglement of touch problems that are difficult to analyze. The most critical and time-consuming part is the real-time construction and generation of each frame of real-time image. Summary of the Invention

[0003] The purpose of the present invention is to provide a scheme for accelerating the touch response speed to solve the problems of large computational amount and slow speed caused by traditional infrared touch screen image processing algorithms drawing each frame of real-time image by each light path.

[0004] To solve the above problems, the present invention provides a technical solution: A scheme for accelerating the touch response speed, comprising the following steps: S1: Determine the number k of scanning directions and the specific angle of each direction; set the reference image A and initialize it as a blank image, set each frame of real-time image B and initialize it as a blank image; set the unqualified light intensity threshold t; set the number of rows M and the number of columns N; S2: Perform a scan of one frame, and mark the light paths with light intensity less than t as unqualified light paths; S3: Use all qualified light paths in the full screen to draw the reference image A; S4: Divide the reference image A and the real-time image B into M*N matrix small regions according to the rule of M rows and N columns in the full screen, and initialize the flag of each small region of the real-time image B to 0; S5: Traverse each of the M*N small regions in A, and establish the association relationship between the current small region and the set of light paths passing through this small region: that is, record the start and end information of each light path passing through this small region, and synchronously record the total number n of light paths passing through this small region; process each small region in turn; S6: Perform a scan of one frame; S7: Traverse the M*N small regions in sequence: Count the number m of blocked optical paths in the current small region. If m < n / 2 (where n is the number of optical paths associated with the current small region), directly copy the local image of this small region from the reference graph A to the real-time graph B. If m = 0, directly skip this small region and proceed to the next small region for processing. Otherwise, if m > 0, then based on this, remove m blocked lines one by one within the current small region in B. Otherwise, if m ≥ n / 2, then draw m - n unblocked optical path parts one by one within the current small region in the real-time graph B. If m > 0, set the flag of this small region to flag = 1, and process all M*N small regions in this way. S8: Start from any small region with flag = 1 in image B to perform touch point search and calculation. For all small regions that have been passed through and searched, set their flag to 0, and process in this way until the flags of all M*N small regions in the real-time graph B are 0. S9: The algorithm performs ghost point removal and tracks the trajectory based on historical trajectory points and each touch point in the current frame. S10: Transform the coordinates of each trajectory touch point and output them to the host computer. S11: Jump to step 6 and execute in a loop.

[0005] Preferably, in step S1, the scanning direction refers to that in the 1-to-k optical path scanning, for the optical paths corresponding to the i-th lamp, there are multiple different angles. For each angle of the k optical paths corresponding to one emitting lamp, it is called a scanning direction. The 1-to-k optical path scanning has k scanning directions, and each scanning direction consists of a group of parallel optical paths with the same slope.

[0006] Preferably, in step S4, initialize the flag of each small region in the real-time graph B to flag = 0, where 0 indicates that there is no blocked optical path in this small region.

[0007] Preferably, in step S7, removing m blocked lines one by one means extracting the optical path parts passing through the small region, and drawing m - n unblocked optical path parts one by one means removing the remaining unblocked optical paths after removing m blocked optical paths. flag = 1, where 1 indicates that there is a blocked optical path in this small region.

[0008] The beneficial effects of the present invention include: The present invention proposes, for the most time-consuming part of the touch control image algorithm, to establish a reference graph during initialization, divide the full screen into multiple small regions at the same time, and associate and record the set of optical paths passing through each small region with each small region. By quickly judging each small region in each frame, obtain whether there is a blocked optical path in each small region, the ratio characteristic of the number of blocked optical paths to the total number of optical paths passing through this small region, and classify and quickly generate different small region images accordingly. Based on this, it effectively reduces the time consumption for forming the real-time graph of each frame, which is the most critical, improves the speed of the overall image algorithm, and lays a foundation for the driverless application of the image algorithm. Brief Description of the Drawings

[0009] For ease of description, the present invention will be described in detail by the following specific embodiments and the accompanying drawings.

[0010] Figure 1 It is a schematic flowchart of the present invention. Detailed Description of the Embodiments

[0011] Embodiment 1 The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0012] As Figure 1 shown, a touch response speed improvement solution includes the following steps: S1: Determine the number k of scanning directions and the specific angle of each direction; set the reference image A and initialize it as a blank image, set the real-time image B of each frame and initialize it as a blank image; set the unqualified light intensity threshold t; set the number of rows M and the number of columns N; S2: Perform a frame of scanning, and mark the optical paths with light intensity less than t as unqualified optical paths; S3: Use all qualified optical paths in the full screen to draw the reference image A; S4: Divide the reference image A and the real-time image B into M*N matrix small regions according to the rule of M rows and N columns in the full screen, and initialize the flag of each small region in the real-time image B to 0; S5: Traverse each of the M*N small regions in A, and establish the association relationship between the current small region and the set of optical paths passing through this small region: that is, record the start and end information of each optical path passing through this small region, and synchronously record the total number n of optical paths passing through this small region; process each small region in this way; S6: Perform a frame of scanning; S7: Traverse the M*N small regions in turn: count the number m of blocked optical paths in the current small region. If m < n / 2 of the number of optical paths associated with the current small region, directly copy the local image of this small region from the reference image A to the real-time image B. If m = 0, directly skip this small region and proceed to the next small region for processing. Otherwise, if m > 0, based on this, m blocked lines are removed one by one in the current small region in B. Otherwise, if m ≥ n / 2, m - n unblocked optical path parts are drawn one by one in the current small region in the real-time image B. If m > 0, set the flag of this small region to 1, and process all M*N small regions in this way; S8: Start the touch point search and calculation from an arbitrarily selected small area with flag = 1 in Image B. For all small areas that have been passed through and searched, set their flag = 0. Process in this way until the flags of all M*N small areas in the real-time Image B are 0. S9: The algorithm eliminates spurious points and performs trajectory tracking based on historical trajectory points and each touch point in the current frame. S10: Transform the coordinates of each trajectory touch point and output them to the host computer. S11: Jump to Step 6 and execute in a loop.

[0013] In Step S1, the scanning direction refers to that in the 1-to-k optical path scanning, for the optical path corresponding to the i-th lamp, there are multiple different angles. For each angle of the k optical paths corresponding to one emitting lamp, it is called a scanning direction. The 1-to-k optical path scanning has k scanning directions, and each scanning direction consists of a set of parallel optical paths with the same slope. In Step S4, initialize the flag of each small area in the real-time Image B to 0, where 0 indicates that there is no blocked optical path in this small area. In Step S7, remove m blocked lines one by one to extract the part of the optical path passing through the small area, and draw m - n unblocked optical path parts one by one, which are the remaining unblocked optical paths after removing m blocked optical paths, and flag = 1, where 1 indicates that there is a blocked optical path in this small area.

[0014] The algorithm in Step 9 eliminates spurious points. The algorithm used is the traditional polygon cutting algorithm. Calculate all candidate touch points using the touch areas in each direction, and at the same time record the set of touch areas involved in the operation of each candidate touch point for this touch point. Then, according to the traditional touch area exclusive algorithm (remove false points and filter out true points).

[0015] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A touch response speed acceleration solution, characterized in that: The following steps are involved: S1: Set the number of scanning directions k and the specific angle of each direction; set the reference image A and initialize it as a blank image, set each frame of real-time image B and initialize it as a blank image; set the unqualified light intensity threshold t; set the number of rows M and the number of columns N; S2: perform a frame scan and mark the light path with light intensity less than t as an unqualified light path; S3: Use all qualified light paths on the full screen to draw reference image A; S4: Divide the reference image A and the real-time image B into M*N matrix small areas according to the rule of M rows and N columns of the full screen, and initialize the flag of each small area of ​​the real-time image B to 0; S5: traverse each of the M*N small areas in A, and establish an association relationship between the current small area and the set of light paths passing through this small area: that is, record the start and end information of each light path passing through this small area, and simultaneously record the total number n of light paths passing through this small area; process each small area in this way; S6: perform a frame scan; S7: Traverse the M*N small areas in sequence: count the number of blocked light paths m in the current small area, if m<the number of light paths associated with the current small area n / 2, directly copy the local image of this small area from the reference image A to the real-time image B, if m=0, directly skip this small area and proceed to the processing of the next small area, otherwise if m>0, based on this, extract the m blocked lines one by one in the current small area in B; otherwise if m≥n / 2, draw the mn unblocked light path parts one by one in the current small area in the real-time image B; if m>0, set the flag of this small area to 1, and process all the M*N small areas in this way; S8: starting from a small area with flag=1 in the image B, searching and obtaining the touch point, setting the flag=0 for all the small areas that have been passed and searched, and repeating this process until the flags of the M*N small areas in the real-time image B are all 0; S9: The algorithm removes strange points and performs trajectory tracking based on historical trajectory points and touch points in the current frame; S10: The coordinates of each track touch point are transformed and output to the host computer; S11: Jump to step 6 and execute the loop.

2. A touch response speed acceleration solution according to claim 1, characterized in that: In step S1, the scanning direction refers to the multiple different angles for the optical path corresponding to the i-th lamp in a pair of k optical path scans. Each angle of the k optical paths corresponding to an emitting lamp is called a scanning direction. A pair of k optical path scans has k scanning directions, and each scanning direction is composed of a group of parallel optical paths with the same slope.

3. The touch response speed acceleration solution according to claim 1, characterized in that: In step S4, the flag of each small area in the real-time image B is initialized to 0, where 0 indicates that there is no blocked light path in this small area.

4. The touch response speed acceleration solution according to claim 1, characterized in that: In step S7, m blocked lines are extracted one by one to extract the light path portion passing through the small area, and mn unblocked light path portions are drawn one by one to remove the remaining unblocked light paths after removing the m blocked light paths. Flag=1, 1 indicates that there is a blocked light path in this small area.

Images