Vehicle windshield wiper control method, device, equipment, medium and product

Abstract

The invention discloses a vehicle windshield wiper control method, device and equipment, a medium and a product. The method comprises the steps that in the running process of a vehicle, if a windshield wiper control instruction is detected, image collection is conducted through a vehicle-mounted camera to obtain a target image containing a front windshield of the vehicle; determining an initial raindrop coverage rate corresponding to the target image, and performing iterative division on the target image based on an iterative dichotomy method according to the initial raindrop coverage rate until a divided regional image meets a recursion ending condition; and determining a rainfall estimation value according to the target recursion depth when recursion is ended, and controlling the windshield wiper frequency of the vehicle according to the determined rainfall estimation value. According to the technical scheme, the windshield wiper frequency is dynamically adjusted by analyzing the raindrop condition on the front windshield in real time, the intelligent level of windshield wiper control can be improved, and driving safety and comfort are improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a vehicle windshield wiper control method, device, equipment, medium and product. Background Art

[0002] When driving in rainy weather, the reasonable control of windshield wiper frequency is crucial for driving safety and clear vision. At present, most traditional windshield wiper control methods are based on time intervals or simple rain sensors, which have the problems of slow response and insufficient accuracy.

[0003] Therefore, how to analyze the raindrops on the windshield in real time, dynamically adjust the wiper frequency, and improve the intelligence level of wiper control, thereby improving driving safety and comfort, is a problem that needs to be solved urgently. Summary of the invention

[0004] The present invention provides a vehicle wiper control method, device, equipment, medium and product to improve the intelligence level of wiper control and enhance driving safety and comfort.

[0005] According to one aspect of the present invention, a vehicle wiper control method is provided, comprising:

[0006] During the operation of the vehicle, if a wiper control command is detected, an image is collected through the vehicle camera to obtain a target image including the front windshield of the vehicle;

[0007] Determine the initial raindrop coverage rate corresponding to the target image, and iteratively divide the target image according to the initial raindrop coverage rate based on the iterative binary division method until there is a divided area image that meets the end recursion condition;

[0008] A rain estimation value is determined according to a target recursion depth when the recursion ends, and a windshield wiper frequency of the vehicle is controlled according to the determined rain estimation value.

[0009] According to another aspect of the present invention, there is provided a vehicle wiper control device, comprising:

[0010] The acquisition module is used to acquire images through the vehicle camera to obtain a target image including the front windshield of the vehicle if a wiper control command is detected during the operation of the vehicle;

[0011] An iterative module is used to determine an initial raindrop coverage rate corresponding to a target image, and iteratively divide the target image according to the initial raindrop coverage rate based on an iterative binary division method until there is a divided region image that satisfies an end recursion condition;

[0012] The control module is used to determine a rainfall estimation value according to a target recursion depth when the recursion ends, and to control a windshield wiper frequency of the vehicle according to the determined rainfall estimation value.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle wiper control method described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle wiper control method described in any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the vehicle wiper control method according to any embodiment of the present invention is implemented.

[0019] The technical solution of the embodiment of the present invention is that during the operation of the vehicle, if a wiper control instruction is detected, an image is collected through the vehicle camera to obtain a target image containing the front windshield of the vehicle; the initial raindrop coverage rate corresponding to the target image is determined, and according to the initial raindrop coverage rate, the target image is iteratively divided based on the iterative binary method until there is a divided area image that meets the end recursion condition; the rainfall estimation value is determined according to the target recursion depth when the recursion ends, and the vehicle's wiper frequency is controlled according to the determined rainfall estimation value. By analyzing the raindrop situation on the front windshield in real time, the wiper frequency is dynamically adjusted, which can improve the intelligence level of wiper control and enhance driving safety and comfort.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a vehicle wiper control method provided by Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of a vehicle wiper control method provided by Embodiment 2 of the present invention;

[0024] Figure 3 is a structural block diagram of a vehicle wiper control device provided by Embodiment 3 of the present invention;

[0025] Figure 4 It is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", "target", "candidate", "alternative", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0028] Embodiment 1

[0029] Figure 11 is a flow chart of a vehicle wiper control method provided by Embodiment 1 of the present invention; this embodiment is applicable to the case where the vehicle estimates the amount of rain during driving and adjusts the wiper frequency in time, the method can be executed by a vehicle wiper control device, the vehicle wiper control device can be implemented in the form of hardware and / or software, the vehicle wiper control device can be configured in an electronic device, such as a vehicle, and executed by an electronic control unit of the vehicle, such as Figure 1 As shown, the vehicle wiper control method includes:

[0030] S101. During the operation of a vehicle, if a wiper control command is detected, an image is collected through a vehicle-mounted camera to obtain a target image including a front windshield of the vehicle.

[0031] The wiper control command is a command for instructing image acquisition and rainfall estimation to control the vehicle wiper frequency, and the vehicle camera refers to a high-definition camera configured on the front side of the vehicle for acquiring images of the vehicle's front windshield. The target image refers to an image used for rainfall estimation, which may specifically refer to an image acquired by acquiring images of the vehicle's front windshield, or may refer to an image obtained after preprocessing the acquired image.

[0032] Optionally, the vehicle's electronic control unit can automatically generate wiper control instructions in real time to execute the steps S101-S103 of the embodiment of the present invention to control the vehicle's wiper frequency; it can also automatically generate wiper control instructions periodically based on a preset cycle; it can also generate wiper control instructions upon receiving a wiper control request from the driver to execute the steps S101-S103 of the embodiment of the present invention to control the vehicle's wiper frequency, wherein the driver can actively issue a wiper control request to the vehicle when it feels that it is about to rain or when it is already raining.

[0033] Optionally, image acquisition is performed through a vehicle-mounted camera to obtain a target image including the vehicle's windshield, including: acquiring an image of the vehicle's windshield through a vehicle-mounted camera to obtain a candidate image; grayscale processing is performed on the candidate image to obtain a grayscale image, and a Gaussian filter is used to filter the grayscale image to obtain a filtered image; and image segmentation is performed on the filtered image to eliminate the background area in the filtered image except the windshield area to obtain a target image.

[0034] The candidate image refers to a preliminary image acquired by the vehicle-mounted camera through image acquisition, and the candidate image may be a color image, for example. The filtered image refers to an image obtained by denoising a grayscale image using a Gaussian filter.

[0035] Optionally, a preset image recognition algorithm can be used to identify the filtered image to determine the front windshield area and the background area in the filtered image, and further a preset image segmentation algorithm can be used to remove the background area in the filtered image except the front windshield area to obtain the target image.

[0036] It should be noted that by converting color images into grayscale images, the amount of calculation can be effectively reduced. At the same time, by using Gaussian filters for denoising, the image can be smoothed and the interference of noise can be effectively reduced, thereby improving the accuracy of subsequent rainfall estimation results.

[0037] S102, determining an initial raindrop coverage rate corresponding to the target image, and iteratively dividing the target image according to the initial raindrop coverage rate based on an iterative binary division method until there is a divided regional image that meets the recursive termination condition.

[0038] Among them, the initial raindrop coverage refers to the raindrop coverage calculated based on the contrast, blur, edge point ratio and preset weighting coefficient of the target image without dividing the target image. The initial raindrop coverage is used to evaluate the raindrop coverage of the entire target image. Iterative dichotomy refers to a method of iteratively dividing the target image until there is a regional raindrop coverage of the divided regional image greater than a preset coverage threshold. The regional image refers to an image obtained by dividing the target image, and the regional image is a partial image of the target image. The end recursive condition refers to the condition for evaluating whether to end the iterative division. The end recursive condition can specifically be that there is at least one regional image in the regional images obtained in a round of division. The regional raindrop coverage is greater than the preset coverage threshold. The end recursive condition can also be that the recursive depth reaches the maximum recursive depth.

[0039] Optionally, after each round of iterative division of the target image, it is possible to determine whether the regional raindrop coverage is greater than a preset coverage threshold; if not, it is further determined whether the current recursion depth has reached the maximum recursion depth; if the maximum recursion depth has been reached, the recursion can be terminated; if the maximum recursion depth has not been reached, the iterative division can continue; further, if the raindrop coverage of the corresponding area is greater than a preset coverage threshold, it is possible to directly determine to terminate the recursion without calculating whether the current recursion depth has reached the maximum recursion depth.

[0040] Optionally, determining an initial raindrop coverage rate corresponding to the target image includes: determining the ratio of edge points corresponding to the target image based on a preset edge detection algorithm, and determining the blurriness corresponding to the target image based on a Laplace transform strategy; determining the initial raindrop coverage rate corresponding to the target image based on a preset coverage rate calculation rule according to the contrast, blurriness, edge point ratio and preset weighting coefficient corresponding to the target image.

[0041] The preset edge detection algorithm may be, for example, a Canny edge detection algorithm. The preset weighting coefficients may include a first weighting coefficient corresponding to contrast, a second weighting coefficient corresponding to blurriness, and a third weighting coefficient corresponding to edge point ratio.

[0042] It should be noted that the three features of contrast, blur and edge point ratio can reflect the impact of raindrops on the image from different angles. Therefore, by weighted calculation of these features, a more accurate estimate of raindrop coverage can be obtained. Specifically, raindrops on the windshield will cause changes in the brightness of the local area, thereby affecting the contrast of the image. Therefore, the contrast reflects the difference between the bright and dark areas in the image, and raindrops will increase the local contrast of the image; raindrops will form blurred spots on the windshield, resulting in an increase in the blurriness of the local area of ​​the image, and the blurriness can be measured by the Laplace transform of the image, so the variance of the Laplace operator reflects the sharpness of the image; the edges formed by raindrops in the image will lead to an increase in the number of edge points, and the edge point ratio can be calculated by the Canny edge detection algorithm, so the density of edge points can reflect the edge characteristics of the raindrop coverage area.

[0043] Optionally, the contrast of the target image may be determined according to the maximum and minimum values ​​of the corresponding pixels of the target image. Specifically, the difference between the maximum and minimum values ​​may be determined as the contrast corresponding to the target image.

[0044] Optionally, the Canny edge detection algorithm can be used to substitute each pixel in the target image into the Canny function to determine whether the pixel is an edge point, so as to count the number of edge points in the target image, and finally determine the ratio of the number of edge points to the total number of pixels in the target image as the edge point ratio.

[0045] For example, the Canny edge detection algorithm can be used to determine whether each pixel in the target image is an edge point based on the following formula:

[0046]

[0047] Among them, E(x, y) refers to the evaluation value of whether each pixel is an edge point. If the calculated E(x, y) is 1, it indicates that the pixel is an edge point, otherwise it is determined that the pixel does not belong to the edge point. Canny(I(x, y)) refers to the target value obtained by substituting the pixel in the target image into the Canny function, and threshold refers to the edge point threshold. Specifically, if the target value is greater than the edge point threshold, it can be determined that the pixel belongs to the edge point, otherwise it is determined that the pixel does not belong to the edge point.

[0048] Exemplarily, the edge point ratio may be determined based on the following formula:

[0049]

[0050] Where Pedge refers to the edge point ratio, N refers to the total number of pixels in the target image, and ∑E(x, y) refers to the number of edge points in the target image.

[0051] Optionally, based on the Laplace transform strategy, according to a preset Laplace operator kernel, the target image and the Laplace operator kernel are multiplied to obtain a Laplace image, and the variance of the Laplace image is further determined as the blurriness corresponding to the target image.

[0052] Exemplarily, according to the Laplace image, the blurriness corresponding to the target image can be determined based on the following formula:

[0053]

[0054] Among them, Var(L) refers to the blur corresponding to the target image, M and N refer to the number of rows and columns of the pixel matrix corresponding to the Laplace image, μ refers to the pixel mean of the Laplace image, and L(x, y) refers to the values ​​of each item in the pixel matrix corresponding to the Laplace image.

[0055] Exemplarily, according to the contrast, blur, edge point ratio and preset weighting coefficient corresponding to the target image, the initial raindrop coverage corresponding to the target image may be determined based on the following formula:

[0056] W rain =w1·C global +ω2·Var(L)+w3·P edge ;

[0057] Among them, w1, w2 and w3 are the first weighting coefficient corresponding to contrast, the second weighting coefficient corresponding to blur and the third weighting coefficient corresponding to edge point ratio, respectively, satisfying w1+w2+w3=1. Wrain refers to the initial raindrop coverage, Cglobal refers to contrast, Var(L) refers to blur, and Pedge refers to edge point ratio.

[0058] Optionally, according to the initial raindrop coverage rate, the target image is iteratively divided based on the iterative binary division method until a divided regional image exists that satisfies the end recursion condition, including: determining whether the initial raindrop coverage rate meets the end recursion condition based on the size relationship between the initial raindrop coverage rate and a preset coverage rate threshold; if not, iteratively dividing the target image based on the iterative binary division method until a divided regional image meets the end recursion condition.

[0059] Optionally, if the initial raindrop coverage is greater than a preset coverage threshold, it is determined that the recursion termination condition is met, and the recursion can be terminated at this time, and the current recursion depth is recorded as 1. If the initial raindrop coverage is less than or equal to the preset coverage threshold, the target image is iteratively divided based on the iterative binary division method, and it is determined whether the regional raindrop coverage corresponding to each divided regional image is greater than the coverage threshold.

[0060] Optionally, the preset coverage threshold and maximum recursion depth can be adjusted according to actual conditions to adapt to different rainfall conditions. For example, considering that iterative recursion consumes more computing resources, the corresponding maximum recursion depth can be set based on the large, medium and small levels of the vehicle's computing resources, such as 34, 14 and 5 respectively.

[0061] It should be noted that the size of the preset coverage rate threshold can represent the sensitivity of the activation of the vehicle wiper to the amount of rain. The smaller the preset coverage rate threshold, the more likely it is that the wiper will be activated when the rainfall is light, and the larger the preset coverage rate threshold, the more likely it is that the wiper frequency adjustment will be activated when the rainfall is heavy. Specifically, the corresponding preset coverage rate threshold can be automatically adjusted according to the demand information input by relevant personnel.

[0062] Optionally, based on the iterative binary division method, the target image is iteratively divided until there is a divided regional image that meets the end recursion condition, including: based on the iterative binary division method, dividing the target image into a preset number of regional images; determining the regional raindrop coverage rate corresponding to each regional image, and determining whether there is a regional image whose regional raindrop coverage rate meets the end recursion condition based on the regional raindrop coverage rate and a preset coverage rate threshold, and if so, stopping the iterative division of the target image.

[0063] The preset number may be, for example, two or four. Exemplarily, the target image may be recursively divided into two or four parts (e.g., upper left, upper right, lower left, lower right), and the raindrop coverage rate calculation and judgment process is repeated for each regional image until a preset coverage rate threshold or a maximum recursive depth is reached.

[0064] Exemplarily, the image can be divided into four regional images each time, and the regional raindrop coverage of each regional image can be calculated based on the above-mentioned initial raindrop coverage calculation formula. If the regional raindrop coverage of any part exceeds the preset coverage threshold, the current recursive depth is recorded as 2 to obtain the target recursive depth. Otherwise, the four divided regional images are further divided into four sub-region images, and it is determined whether the regional raindrop coverage of the 16 sub-region images obtained by division exceeds the preset coverage threshold. If so, the current recursive depth is determined to be 3 to obtain the target recursive depth. If not, the division is performed until the preset coverage threshold or the maximum recursive depth is reached.

[0065] It should be noted that if the current rainfall is very heavy, the calculated raindrop coverage will be very large, and the threshold will be exceeded during the initial calculation, and the recursive depth will be 1. On the contrary, in extreme cases, if the weather is clear and there is no rain, the iterative segmentation will continue until the maximum recursive depth is reached, and the recursive depth value will be very large at this time.

[0066] S103, determining a rainfall estimation value according to the target recursion depth when the recursion ends, and controlling the windshield wiper frequency of the vehicle according to the determined rainfall estimation value.

[0067] The target recursion depth refers to the recursion depth at the end of the recursion. The size of the rainfall can be reflected by the size of the recursion depth value. When the recursion depth is large, it means that the rainfall is small; when the recursion depth is small, it means that the rainfall is large.

[0068] Optionally, determining the rainfall estimation value according to the target recursion depth when the recursion ends includes: determining the target recursion depth when the recursion ends; and determining the rainfall estimation value based on a preset rainfall estimation rule according to the target recursion depth, the maximum recursion depth and the maximum rainfall.

[0069] Exemplarily, according to the target recursion depth, the maximum recursion depth and the maximum rainfall, the rainfall estimation value may be determined based on the following formula:

[0070]

[0071] Where R is the estimated rainfall, Rmax is the maximum rainfall, D is the target recursion depth, and Dmax is the maximum recursion depth. When D is equal to 0, the formula is R=Rmax, indicating very heavy rain, and when D is equal to Dmax, the formula is R=0, indicating no rain. The larger the target recursion depth, the smaller the estimated rainfall value R. The maximum rainfall can be calibrated according to the rain sensor or actual conditions.

[0072] For example, assuming that the maximum recursion depth is 10, the maximum rainfall is 100 mm / h, and the target recursion depth is 4, the rainfall estimation value can be determined to be R=100(1-4 / 10)=60 mm / h.

[0073] Optionally, after determining the rainfall estimate, the corresponding wiper frequency can be determined according to the rainfall level to which the rainfall estimate belongs and according to a preset correspondence between the rainfall level and the wiper frequency to control the vehicle wipers. When the target recursive depth is smaller, it indicates that the rainfall is heavier and a higher wiper frequency is required; when the target recursive depth is larger, it indicates that the rainfall is lighter and a lower wiper frequency is required. If the rainfall estimate is 0, the corresponding wiper frequency can be directly determined to be 0.

[0074] It should be noted that, in actual situations, when it just starts to rain or the rain is relatively light, the raindrops cannot cover the entire front windshield. The present invention can quickly locate the area that may contain rain by continuously segmenting the target image based on the iterative binary method. That is to say, the windshield area where the final regional raindrop coverage is greater than the preset coverage threshold is actually the area on the windshield with the most rain.

[0075] The technical solution of the embodiment of the present invention is that during the operation of the vehicle, if a wiper control instruction is detected, an image is collected through the vehicle camera to obtain a target image containing the front windshield of the vehicle; the initial raindrop coverage rate corresponding to the target image is determined, and according to the initial raindrop coverage rate, the target image is iteratively divided based on the iterative binary method until there is a divided area image that meets the end recursion condition; the rainfall estimation value is determined according to the target recursion depth when the recursion ends, and the vehicle's wiper frequency is controlled according to the determined rainfall estimation value. By analyzing the raindrop situation on the front windshield in real time, the wiper frequency is dynamically adjusted, which can improve the intelligence level of wiper control and enhance driving safety and comfort.

[0076] Embodiment 2

[0077] Figure 2 is a flow chart of a vehicle wiper control method provided by Embodiment 2 of the present invention; based on the above embodiments, this embodiment provides a preferred example of using iterative dichotomy to estimate rainfall and thus control vehicle wipers, specifically, Figure 2 As shown, the method includes:

[0078] S201. During the operation of the vehicle, if a wiper control command is detected, an image of the front windshield of the vehicle is collected by a vehicle-mounted camera to obtain a candidate image.

[0079] S202, grayscale processing is performed on the candidate image to obtain a grayscale image, and a Gaussian filter is used to filter the grayscale image to obtain a filtered image.

[0080] S203: performing image segmentation processing on the filtered image to remove the background area except the front windshield area in the filtered image to obtain a target image.

[0081] S204: Determine the edge point ratio corresponding to the target image based on a preset edge detection algorithm, and determine the blurriness corresponding to the target image based on a Laplace transform strategy.

[0082] S205 , determining an initial raindrop coverage rate corresponding to the target image according to the contrast, blur, edge point ratio and preset weighting coefficient corresponding to the target image and based on a preset coverage rate calculation rule.

[0083] S206: Determine whether the initial raindrop coverage rate satisfies a recursive termination condition based on the relationship between the initial raindrop coverage rate and a preset coverage rate threshold.

[0084] S207: If not, iteratively divide the target image based on the iterative binary division method until there is a divided regional image that meets the recursive termination condition.

[0085] S208, determining a target recursion depth when the recursion ends, and determining a rainfall estimation value according to the target recursion depth, the maximum recursion depth and the maximum rainfall based on a preset rainfall estimation rule.

[0086] S209: Controlling the windshield wiper frequency of the vehicle according to the determined rainfall estimation value.

[0087] The technical solution of the present invention has the following technical effects: (1) Improving the accuracy and intelligence of wiper frequency control: Most existing wiper control methods are based on fixed time intervals or simple rain sensors, which cannot reflect rainfall changes in real time and accurately. The present invention realizes dynamic adjustment of wiper frequency by comprehensively analyzing raindrop coverage, thereby improving the accuracy and intelligence of wiper control. (2) Enhancing driving safety and visual clarity: When driving in rainy days, raindrops on the front windshield will significantly affect the driver's visual clarity. Through the method of the present invention, the wiper frequency can be adjusted in a timely and accurate manner to ensure that the driver's field of vision is clear, thereby enhancing driving safety. (3) Real-time and multi-feature fusion: The present invention uses a vehicle-mounted high-definition camera to collect images in real time, and combines multiple features such as contrast, blur and edge point ratio to calculate raindrop coverage, providing a real-time rainfall detection method that comprehensively considers multiple influencing factors, avoiding the limitations of traditional single feature methods.

[0088] In summary, the technical solution of the present invention can achieve high precision: by comprehensively considering multiple characteristics, the calculation of raindrop coverage is more accurate; intelligent control: dynamically adjust the wiper frequency according to the amount of rainfall to improve driving safety and comfort; real-time: use the on-board camera to collect images in real time, and the algorithm has high real-time performance.

[0089] Embodiment 3

[0090] Figure 3: is a structural block diagram of a vehicle wiper control device provided in the third embodiment of the present invention; this embodiment is applicable to the situation where the vehicle estimates the rainfall during driving and adjusts the wiper frequency in time, and the vehicle wiper control device provided in the embodiment of the present invention can execute the vehicle wiper control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method; the vehicle wiper control device can be implemented in the form of hardware and / or software, and configured in an electronic device with a vehicle wiper control function, such as a vehicle, and executed by the vehicle's electronic control unit, such as Figure 3 As shown, the vehicle wiper control device specifically includes:

[0091] The acquisition module 301 is used to acquire an image through the vehicle camera to obtain a target image including the front windshield of the vehicle if a wiper control instruction is detected during the operation of the vehicle;

[0092] Iterative module 302, used to determine the initial raindrop coverage rate corresponding to the target image, and iteratively divide the target image according to the initial raindrop coverage rate based on the iterative binary division method until there is a divided area image that meets the end recursion condition;

[0093] The control module 303 is used to determine a rainfall estimation value according to a target recursion depth when the recursion ends, and to control a windshield wiper frequency of the vehicle according to the determined rainfall estimation value.

[0094] The technical solution of the embodiment of the present invention is that during the operation of the vehicle, if a wiper control instruction is detected, an image is collected through the vehicle camera to obtain a target image containing the front windshield of the vehicle; the initial raindrop coverage rate corresponding to the target image is determined, and according to the initial raindrop coverage rate, the target image is iteratively divided based on the iterative binary method until there is a divided area image that meets the end recursion condition; the rainfall estimation value is determined according to the target recursion depth when the recursion ends, and the vehicle's wiper frequency is controlled according to the determined rainfall estimation value. By analyzing the raindrop situation on the front windshield in real time, the wiper frequency is dynamically adjusted, which can improve the intelligence level of wiper control and enhance driving safety and comfort.

[0095] Furthermore, the iteration module 302 may include:

[0096] A judgment unit, used to determine whether the initial raindrop coverage rate meets the recursion termination condition according to the size relationship between the initial raindrop coverage rate and a preset coverage rate threshold;

[0097] The iterative unit is used to iteratively divide the target image based on the iterative binary division method, if not, until there is a divided regional image that meets the end recursion condition.

[0098] Furthermore, the iteration module 302 is specifically used for:

[0099] Based on a preset edge detection algorithm, determine the edge point ratio corresponding to the target image, and based on a Laplace transform strategy, determine the blurriness corresponding to the target image;

[0100] According to the contrast, blur, edge point ratio and preset weighting coefficient corresponding to the target image, the initial raindrop coverage corresponding to the target image is determined based on the preset coverage calculation rules.

[0101] Furthermore, the iteration unit is specifically used for:

[0102] Based on the iterative binary division method, the target image is divided into a preset number of regional images;

[0103] Determine the regional raindrop coverage rate corresponding to each regional image, and determine whether the regional raindrop coverage rate of any regional image meets the recursive termination condition based on the regional raindrop coverage rate and the preset coverage rate threshold. If so, stop the iterative division of the target image.

[0104] Furthermore, the acquisition module 301 is specifically used for:

[0105] Capturing an image of the front windshield of the vehicle through a vehicle-mounted camera to obtain a candidate image;

[0106] Performing grayscale processing on the candidate image to obtain a grayscale image, and using a Gaussian filter to filter the grayscale image to obtain a filtered image;

[0107] The filtered image is subjected to image segmentation processing to remove the background area except the front windshield area in the filtered image to obtain the target image.

[0108] Furthermore, the control module 303 is specifically used for:

[0109] Determine the target recursion depth at which to end the recursion;

[0110] According to the target recursion depth, the maximum recursion depth and the maximum rainfall, based on the preset rainfall estimation rules, the rainfall estimation value is determined.

[0111] Embodiment 4

[0112] Figure 4 It is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0113] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0114] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0115] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a vehicle wiper control method.

[0116] In some embodiments, the vehicle wiper control method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle wiper control method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the vehicle wiper control method in any other appropriate manner (e.g., by means of firmware).

[0117] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0119] In the context of the present invention, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0121] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0122] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0123] In one embodiment, the embodiment of the present invention further includes a computer program product, the computer program product includes a computer program, and the computer program implements the vehicle wiper control method of any embodiment of the present invention when executed by a processor.

[0124] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0125] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0126] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle wiper control method, characterized in that: include: During the operation of the vehicle, if a wiper control command is detected, an image is collected through the vehicle camera to obtain a target image including the front windshield of the vehicle; Determine the initial raindrop coverage rate corresponding to the target image, and iteratively divide the target image according to the initial raindrop coverage rate based on the iterative binary division method until there is a divided area image that meets the end recursion condition; A rain estimation value is determined according to a target recursion depth when the recursion ends, and a windshield wiper frequency of the vehicle is controlled according to the determined rain estimation value.

2. The method according to claim 1, characterized in that According to the initial raindrop coverage, the target image is iteratively divided based on the iterative binary method until there is a divided area image that meets the end recursion condition, including: According to the relationship between the initial raindrop coverage rate and the preset coverage rate threshold, determine whether the initial raindrop coverage rate meets the recursive termination condition; If not, the target image is iteratively divided based on the iterative binary division method until there is a divided region image that meets the recursive termination condition.

3. The method according to claim 1, characterized in that Determine the initial raindrop coverage corresponding to the target image, including: Based on a preset edge detection algorithm, determine the edge point ratio corresponding to the target image, and based on a Laplace transform strategy, determine the blurriness corresponding to the target image; According to the contrast, blur, edge point ratio and preset weighting coefficient corresponding to the target image, the initial raindrop coverage corresponding to the target image is determined based on the preset coverage calculation rules.

4. The method according to claim 2, characterized in that: Based on the iterative binary division method, the target image is iteratively divided until there is a divided region image that meets the end recursion condition, including: Based on the iterative binary division method, the target image is divided into a preset number of regional images; Determine the regional raindrop coverage rate corresponding to each regional image, and determine whether the regional raindrop coverage rate of any regional image meets the recursive termination condition based on the regional raindrop coverage rate and the preset coverage rate threshold. If so, stop the iterative division of the target image.

5. The method according to claim 1, characterized in that: The vehicle-mounted camera is used to collect images to obtain a target image containing the front windshield of the vehicle, including: Capturing an image of the front windshield of the vehicle through a vehicle-mounted camera to obtain a candidate image; Performing grayscale processing on the candidate image to obtain a grayscale image, and using a Gaussian filter to filter the grayscale image to obtain a filtered image; The filtered image is subjected to image segmentation processing to remove the background area except the front windshield area in the filtered image to obtain the target image.

6. The method according to claim 1, characterized in that The rainfall estimate is determined based on the target recursion depth at the end of the recursion, including: Determine the target recursion depth at which to end the recursion; According to the target recursion depth, the maximum recursion depth and the maximum rainfall, based on the preset rainfall estimation rules, the rainfall estimation value is determined.

7. A vehicle wiper control device, characterized in that: include: The acquisition module is used to acquire images through the vehicle camera to obtain a target image including the front windshield of the vehicle if a wiper control command is detected during the operation of the vehicle; An iterative module is used to determine an initial raindrop coverage rate corresponding to a target image, and iteratively divide the target image according to the initial raindrop coverage rate based on an iterative binary division method until there is a divided region image that satisfies an end recursion condition; The control module is used to determine a rainfall estimation value according to a target recursion depth when the recursion ends, and to control a windshield wiper frequency of the vehicle according to the determined rainfall estimation value.

8. An electronic device, characterized in that: The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle wiper control method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle wiper control method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the vehicle wiper control method according to any one of claims 1 to 6.

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