CN115860025A - Two-dimensional code image processing method, device, equipment, storage medium and program product - Google Patents

Abstract

The present application relates to a two-dimensional code image processing method, apparatus, device, storage medium, and program product, the method comprising: sampling the cut original two-dimensional code image to obtain a two-dimensional code image to be analyzed; processing the two-dimensional code image to be analyzed based on the mapping relation between the actual gray value and the target gray value of the two-dimensional code image to be analyzed to obtain a target two-dimensional code image; performing gray histogram statistics on the target two-dimensional code image, and determining a value range in which a conversion threshold corresponding to the target two-dimensional code image is located based on a gray histogram statistical result; determining a middle conversion threshold corresponding to the target two-dimensional code image based on the middle value of the value range; and performing binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold value to obtain a processing result corresponding to the target two-dimensional code image.

Description

Two-dimensional code image processing method, device, equipment, storage medium and program product

technical field

The present application relates to the technical field of image processing, in particular to a two-dimensional code image processing method, device, equipment, storage medium and program product.

Background technique

In recent years, a variety of embedded products have chosen to use QR codes as the medium for transmitting WiFi account passwords and other verification information. Among them, the wireless network camera (i.e. WiFi camera) is one of the embedded products. Due to the limited operation of this type of product, it can only access the wireless network by analyzing the wireless network connection information transmitted externally. . Usually, the wireless network camera will configure the relevant network parameters by scanning and analyzing the QR code containing the wireless network connection information generated by the external terminal device.

However, since the image signal processing unit in the wireless network camera will make some adaptive changes to the brightness of the acquired image based on the external lighting conditions, the screen brightness of the terminal device used to display the QR code is too high, and the external lighting Under unfavorable conditions, the two-dimensional code image processed by the image signal processing unit tends to be in an over-exposed state, which will directly affect the recognition success rate of the two-dimensional code image. Therefore, based on the prior art, it is difficult to realize accurate recognition of the two-dimensional code image in the wireless network camera.

Contents of the invention

Based on this, it is necessary to provide a two-dimensional code image processing method, device, equipment, storage medium and program product for the above technical problems.

In a first aspect, the present application provides a two-dimensional code image processing method, which is applied to a wireless network camera, and the method includes:

Sampling the cropped original QR code image to obtain the QR code image to be analyzed;

Based on the mapping relationship between the actual grayscale value of the two-dimensional code image to be analyzed and the target grayscale value, process the two-dimensional code image to be analyzed to obtain the target two-dimensional code image;

Perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the grayscale histogram statistical result;

Determine an intermediate conversion threshold corresponding to the target two-dimensional code image based on an intermediate value of the value range;

Perform binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold to obtain a processing result corresponding to the target two-dimensional code image.

In one of the embodiments, the sampling of the cropped original two-dimensional code image to obtain the two-dimensional code image to be analyzed includes:

Based on the preset image size, edge cutting is performed on the original two-dimensional code image to obtain the original two-dimensional code image after cutting; the original two-dimensional code image after cutting is sampled every row and every column to obtain the two-dimensional code image to be analyzed .

In one of the embodiments, the two-dimensional code image to be analyzed is processed based on the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value to obtain the target two-dimensional code image ,include:

Based on the image brightness gain information, determine the value interval where the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is located; according to the value interval and the preset grayscale mapping rule, determine each actual grayscale value corresponding to the target grayscale value; based on the target grayscale value, process the two-dimensional code image to be analyzed to obtain the target two-dimensional code image.

In one of the embodiments, the determination of the value range of the conversion threshold corresponding to the target two-dimensional code image based on the statistical results of the grayscale histogram includes:

Using a pre-configured sliding window, traverse the statistical results of the gray histogram to determine the position of the peak of the statistical result of the gray histogram; on the side close to the origin of the statistical results of the gray histogram, based on the The shortest distance from the position of the peak to the equilibrium position determines the starting position of the value range; according to the starting position of the value range and the preset translation step, the end position of the value range is obtained.

In one of the embodiments, the sampling range of the sliding window is determined based on the width value of the sliding window; the sampling threshold of the sliding window is determined based on the height value of the sliding window.

In one of the embodiments, according to the value range and the intermediate conversion threshold, the target two-dimensional code image is subjected to binarization conversion processing to obtain a processing result corresponding to the target two-dimensional code image, include:

According to the start position of the value range, the end position of the value range, and the intermediate conversion threshold, perform binarization conversion processing on the target two-dimensional code image to obtain a corresponding value of the target two-dimensional code image Processing result: identifying the target two-dimensional code image based on the processing result corresponding to the target two-dimensional code image.

In the second aspect, the present application also provides a two-dimensional code image processing device, which is applied to a wireless network camera, and the device includes:

The image sampling module is used to sample the cropped original two-dimensional code image to obtain the two-dimensional code image to be analyzed;

A grayscale mapping module, configured to process the two-dimensional code image to be analyzed based on the mapping relationship between the actual grayscale value of the two-dimensional code image to be analyzed and the target grayscale value, to obtain the target two-dimensional code image;

A threshold range determination module, configured to perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the grayscale histogram statistical results;

An intermediate threshold determination module, configured to determine an intermediate conversion threshold corresponding to the target two-dimensional code image based on the intermediate value of the value range;

The processing result acquisition module is configured to perform binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold to obtain a processing result corresponding to the target two-dimensional code image.

In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the above method are realized.

In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the above method are realized.

The above-mentioned two-dimensional code image processing method, device, equipment, storage medium and program product, firstly, sample the cut original two-dimensional code image to obtain the two-dimensional code image to be analyzed. Then, based on the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value, the two-dimensional code image to be analyzed is processed to obtain the target two-dimensional code image. Next, perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the statistical results of the grayscale histogram. Afterwards, based on the intermediate value of the value range, an intermediate conversion threshold corresponding to the target two-dimensional code image is determined. Finally, according to the range of values and the intermediate conversion threshold, the target two-dimensional code image is binarized and converted to obtain the corresponding processing result of the target two-dimensional code image. This application first resamples the original two-dimensional code image after cropping, and then based on the mapping relationship between the actual gray value and the target gray value of the resampled two-dimensional code image, each of the two-dimensional code image The gray value corresponding to the pixel is included in the target gray value range, and finally the two-dimensional code image is binarized using the dynamically selected conversion threshold value range, which not only realizes the two-dimensional code image after binarization On the basis of the effective improvement of the quality, the accuracy of the recognition of the two-dimensional code image is improved, and the efficiency of the recognition of the two-dimensional code image can be effectively improved by reducing the amount of redundant data in the recognition of the two-dimensional code image .

Description of drawings

Fig. 1 is a schematic flow chart of a two-dimensional code image processing method in an embodiment;

Fig. 2 is a schematic flow chart of a specific way of obtaining a two-dimensional code image to be analyzed in an embodiment;

Fig. 3 is a schematic flow chart of a specific way of acquiring a target two-dimensional code image in an embodiment;

FIG. 4 is a schematic flowchart of a specific manner of determining the value range of the conversion threshold in an embodiment;

FIG. 5 is a schematic flow diagram of a specific manner of obtaining a processing result corresponding to a target two-dimensional code image in an embodiment;

Fig. 6 is a structural block diagram of a two-dimensional code image processing device in an embodiment;

Figure 7 is an internal block diagram of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

When used herein, the singular forms "a", "an" and "the/the" may also include the plural forms unless the context clearly dictates otherwise. It should also be understood that the terms "comprising/comprising" or "having" etc. specify the presence of stated features, integers, steps, operations, components, parts or combinations thereof, but do not exclude the presence or addition of one or more The possibility of other features, integers, steps, operations, components, parts or combinations thereof. Meanwhile, the term "and/or" used in this specification includes any and all combinations of the related listed items.

In recent years, a variety of embedded products have chosen to use QR codes as the medium for transmitting WiFi account passwords and other verification information. Among them, the wireless network camera (i.e. WiFi camera) is one of the embedded products. Due to the limited operation of this type of product, it can only access the wireless network by analyzing the wireless network connection information transmitted externally. . Usually, the wireless network camera will scan the two-dimensional code containing the wireless network connection information generated by the external terminal device, and transmit the obtained two-dimensional code image to the two-dimensional code image recognition library inside the wireless network camera, for example, The zbar library is used to identify and analyze, and configure related network parameters based on the analysis results.

However, since the image signal processing unit (ISP, Image Signal Processor) in the wireless network camera will perform some adaptive changes to the brightness of the acquired image based on the external lighting conditions, the screen brightness of the terminal device used to display the two-dimensional code If the temperature is too high and the external lighting conditions are not good, the two-dimensional code image processed by the image signal processing unit will often show an over-exposed state, which will directly affect the recognition success rate of the two-dimensional code image.

In addition, because the wireless network camera uses a dedicated embedded system, there are many restrictions on the use of its available memory, and the analysis time of the two-dimensional code recognition library for the two-dimensional code will increase with the increase of the image size , and based on the two-dimensional code image obtained by the existing technology, there are still some redundant data volumes, which not only brings an additional burden to the memory capacity of the wireless network camera, but also reduces the quality of the two-dimensional code in the wireless network camera The efficiency of image recognition.

It can be seen that based on the prior art, not only is it difficult to realize accurate recognition of two-dimensional code images in wireless network cameras, but also there is a problem of low efficiency when recognizing two-dimensional code images.

The two-dimensional code image processing method provided in the embodiment of the present application can be applied to a server for execution. Among them, the data storage system can store the data that the server needs to process; the data storage system can be integrated on the server, and can also be placed on the cloud or other network servers; the server can be an independent server or a server cluster composed of multiple servers. accomplish.

In one embodiment, as shown in FIG. 1 , a method for processing a two-dimensional code image is provided, which is applied to a wireless network camera and includes the following steps:

Step S110, sampling the cropped original two-dimensional code image to obtain the two-dimensional code image to be analyzed.

In this step, the original two-dimensional code image refers to the original two-dimensional code image collected by camera shooting or other methods; sampling the original two-dimensional code image after cropping refers to firstly sampling the original two-dimensional code image obtained based on the preset size. The QR code image is cropped, and then the cropped original QR code image is re-sampled; the QR code image to be analyzed means that the collected original QR code image is first cropped based on the preset size, and then The clipped original two-dimensional code image is re-sampled to obtain the obtained two-dimensional code image to be analyzed.

In practical applications, the above-mentioned original two-dimensional code image may be an original two-dimensional code image with a relatively high resolution collected by the front-end camera of the wireless network camera, for example, the image collected by the front-end camera of the wireless network camera, resolution The original QR code image with a rate of 1080P.

Step S120, based on the mapping relationship between the actual gray value of the image to be analyzed and the target gray value, the image of the two-dimensional code to be analyzed is processed to obtain the image of the target two-dimensional code.

In this step, the to-be-analyzed QR code image refers to cutting the collected original QR code image based on a preset size, and then resampling the cropped original QR code image to obtain the obtained QR code image to be analyzed. Analyze the two-dimensional code image; the actual gray value of the two-dimensional code image to be analyzed refers to the actual gray value corresponding to each pixel in the two-dimensional code image to be analyzed; the target gray value refers to the two-dimensional code image to be analyzed The target gray value corresponding to each pixel in the code image; the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value refers to the gray value of each pixel in the two-dimensional code image to be analyzed The mapping relationship between the actual gray value corresponding to the point and the target gray value corresponding to each pixel in the two-dimensional code image to be analyzed; the target two-dimensional code image refers to the The mapping relationship between the actual gray value corresponding to each pixel and the target gray value corresponding to each pixel in the two-dimensional code image to be analyzed is processed to obtain the target QR code image.

In practical applications, based on the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value, the specific method of processing the two-dimensional code image to be analyzed can be to use the The target gray value corresponding to each pixel is replaced with the actual gray value corresponding to the pixel, so that the gray value interval corresponding to each pixel of the QR code image to be analyzed falls into the target gray value interval .

Step S130, performing gray histogram statistics on the target two-dimensional code image, and determining the value range of the conversion threshold corresponding to the target two-dimensional code image based on the statistical results of the gray histogram.

In this step, the target two-dimensional code image refers to the target gray level corresponding to each pixel in the two-dimensional code image to be analyzed based on the actual gray value corresponding to each pixel in the two-dimensional code image to be analyzed The mapping relationship between values is to process the two-dimensional code image to be analyzed, so as to obtain the target two-dimensional code image; the gray histogram statistical result refers to the gray histogram statistics of the aforementioned target two-dimensional code image, and obtains The statistical results of the gray histogram; based on the statistical results of the gray histogram, determining the value range of the conversion threshold corresponding to the target two-dimensional code image refers to determining the aforementioned target two-dimensional code in the statistical results of the gray histogram. The value range of the conversion threshold corresponding to the code image.

Step S140, based on the intermediate value of the value range, determine the intermediate conversion threshold corresponding to the target two-dimensional code image.

In this step, the value range refers to the value range where the conversion threshold corresponding to the target two-dimensional code image is located; the middle value of the value range refers to the middle of the value range where the conversion threshold corresponding to the target two-dimensional code image is located value; the target two-dimensional code image refers to the difference between the actual gray value corresponding to each pixel in the two-dimensional code image to be analyzed and the target gray value corresponding to each pixel in the two-dimensional code image to be analyzed The mapping relationship between the two-dimensional code image to be analyzed is processed to obtain the target two-dimensional code image; based on the intermediate value of the value range, the intermediate conversion threshold corresponding to the target two-dimensional code image is determined, which refers to the target two-dimensional code image The intermediate value of the value range where the conversion threshold corresponding to the code image is located is used as the intermediate conversion threshold corresponding to the target two-dimensional code image.

Step S150, according to the value range and the intermediate conversion threshold, perform binarization conversion processing on the target two-dimensional code image, and obtain a processing result corresponding to the target two-dimensional code image.

In this step, the value range refers to the value range where the conversion threshold corresponding to the target two-dimensional code image is located; the intermediate conversion threshold refers to the determined intermediate conversion corresponding to the target two-dimensional code image based on the intermediate value of the value range Threshold; the target two-dimensional code image refers to the difference between the actual gray value corresponding to each pixel in the two-dimensional code image to be analyzed and the target gray value corresponding to each pixel in the two-dimensional code image to be analyzed. The mapping relationship between the two-dimensional code image to be analyzed is processed to obtain the target two-dimensional code image; according to the value range and the intermediate conversion threshold, the target two-dimensional code image is binarized and converted, which refers to the target two-dimensional code image based on The aforementioned value range and the aforementioned intermediate conversion threshold are used to perform binarization conversion processing on the target two-dimensional code image; the corresponding processing results of the target two-dimensional code image refer to the target two-dimensional The two-dimensional code image is subjected to binarization conversion processing, so as to obtain the processing result corresponding to the target two-dimensional code image.

In the above two-dimensional code image processing method, firstly, the clipped original two-dimensional code image is sampled to obtain the two-dimensional code image to be analyzed. Then, based on the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value, the two-dimensional code image to be analyzed is processed to obtain the target two-dimensional code image. Next, perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the statistical results of the grayscale histogram. Afterwards, based on the intermediate value of the value range, an intermediate conversion threshold corresponding to the target two-dimensional code image is determined. Finally, according to the range of values and the intermediate conversion threshold, the target two-dimensional code image is binarized and converted to obtain the corresponding processing result of the target two-dimensional code image. This application first resamples the original two-dimensional code image after cropping, and then based on the mapping relationship between the actual gray value and the target gray value of the resampled two-dimensional code image, each of the two-dimensional code image The gray value corresponding to the pixel is included in the target gray value range, and finally the two-dimensional code image is binarized using the dynamically selected conversion threshold value range, which not only realizes the two-dimensional code image after binarization On the basis of the effective improvement of the quality, the accuracy of the recognition of the two-dimensional code image is improved, and the efficiency of the recognition of the two-dimensional code image can be effectively improved by reducing the amount of redundant data in the recognition of the two-dimensional code image .

Regarding the specific manner of obtaining the two-dimensional code image to be analyzed, in one embodiment, as shown in FIG. 2, the above step S110 specifically includes:

Step S210, based on the preset image size, edge cropping is performed on the original two-dimensional code image to obtain a cropped original two-dimensional code image.

In this step, the original two-dimensional code image refers to the original two-dimensional code image collected by the camera; the original two-dimensional code image after cropping refers to the original two-dimensional code image based on the preset image size. Edge cropping to obtain the cropped original QR code image.

In practical applications, assuming that the original QR code image with a resolution of 1080P is captured by the front-end camera of the wireless network camera, and the preset image size is 1600*800 (width*height), then based on the preset image size , crop the edge of the original QR code image to get the original QR code after cropping

Image refers to cutting the edge of the original QR code image 5 with a resolution of 1080P based on a preset image size of 1600*800 to obtain a cropped original QR code image with an image size of 1600*800; based on the preset Image size, the specific reason for cutting the edge of the original two-dimensional code image may be that in the actual two-dimensional code scanning operation, the user has a low probability of placing the two-dimensional code image on the edge of the camera (that is, the image edge The utilization rate of the position is low), and the edge position of the collected image often has influence

Distortion (i.e. low usability rate) that affects its recognition accuracy, so by cutting the edge of the original two-dimensional code image, most of the useful information in the original two-dimensional code image can be retained, and edge cutting The final image size can be effectively reduced, thereby solving the problem of limited available memory of wireless network cameras using dedicated embedded systems.

Step S220, sampling the cropped original two-dimensional code image alternately by row and by column to obtain the two-dimensional code image to be analyzed.

5 In this step, the cropped original two-dimensional code image refers to the original two-dimensional code image after trimming based on the preset image size, so as to obtain the original two-dimensional code image after cropping; the original two-dimensional code image after cropping Sampling the two-dimensional code image by row and column means resampling the cropped original two-dimensional code image by extracting one row of data every other row and one column of data every other column, so that the resampled

The size of the newly sampled image is half of the size of the original image; the QR code image to be analyzed refers to the original QR code image after cropping 0, using the method of extracting a row of data every other row and a column of data every other column.

Perform re-sampling to obtain the image of the QR code to be analyzed.

In practical applications, assuming that the cropped original QR code image is cropped from the original image with a resolution of 1080P, and its image size is 1600*800, then extract a row of data every other row and a column every other column In the way of data, the cut original two-dimensional code image is re-sampled to obtain the two-dimensional code image to be analyzed with an image size of 800*400 (width*height). Compared with wireless network cameras, by directly setting the target resolution or target image size of the captured image to adjust the size of the two-dimensional code image, using the aforementioned method to re-sample the two-dimensional code image can effectively improve The clarity of the processed two-dimensional code image, and then retain more useful information in the processed two-dimensional code image.

In the above-mentioned embodiment, the cropped original two-dimensional code image is sampled every row and every column to obtain the two-dimensional code image to be analyzed. While successfully realizing the effective control of the image size of the two-dimensional code, the image size is improved. The adjusted two-dimensional code image clarity not only improves the processing efficiency of the two-dimensional code image, but also ensures the recognition accuracy for the two-dimensional code image.

Regarding the specific manner of acquiring the target two-dimensional code image, in one embodiment, as shown in FIG. 3 , the above step S120 specifically includes:

Step S310, based on the image brightness gain information, determine the value interval where the actual gray value of each pixel of the two-dimensional code image to be analyzed is located.

In this step, the image brightness gain information can be embodied as the brightness related parameters set by the user in the image signal processing unit in the wireless network camera for performing brightness gain on the captured image, and the user passes the brightness related parameters Adjustment can reduce the value interval of the image grayscale value; based on the image brightness gain information, determining the value interval where the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is located means that based on the image brightness gain information, After the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is determined, the value interval in which the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is determined.

Step S320, according to the value range and preset grayscale mapping rules, determine the target grayscale value corresponding to each actual grayscale value.

In this step, the value interval refers to the value interval in which the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is located; the preset grayscale mapping rule refers to the value interval of each pixel of the two-dimensional code image to be analyzed The value interval where the actual gray value of the point is mapped to the default gray mapping rule of the value interval where the target gray value is located; the target gray value corresponding to each actual gray value refers to the two-dimensional gray value to be analyzed The target gray value corresponding to the actual gray value of each pixel of the code image.

In practical applications, the above-mentioned preset grayscale mapping rule may be to map the minimum value of the above-mentioned value range to 0, and map the maximum value of the above-mentioned value range to 255 (that is, the value range of the actual gray-scale value, to The target gray value interval [0, 255] is mapped), and then the gray value interval of the two-dimensional code image adjusted by the image brightness gain information is restored to the normal gray value interval.

Step S330, based on the target gray value, process the two-dimensional code image to be analyzed to obtain the target two-dimensional code image.

In this step, the target gray value, that is, the target gray value corresponding to each actual gray value, refers to the target gray value corresponding to the actual gray value of each pixel of the two-dimensional code image to be analyzed; target two The two-dimensional code image refers to the target two-dimensional code image obtained by replacing the actual gray value corresponding to each pixel of the two-dimensional code image to be analyzed with the target gray value corresponding to the pixel.

The above embodiments determine the actual grayscale value corresponding to each pixel in the two-dimensional code image based on the image brightness gain information, and obtain the target two-dimensional code according to the mapping relationship between each grayscale value and the target grayscale value The image method restores the gray value range corresponding to the two-dimensional code image to the normal gray value range, which not only effectively avoids the automatic adjustment of the collected two-dimensional code image due to the use of pre-set image brightness gain information , resulting in a reduction in the recognition accuracy of the two-dimensional code image, and also improves the recognition efficiency for the two-dimensional code image.

Regarding the specific manner of determining the value range where the conversion threshold is located, in one embodiment, as shown in FIG. 4 , the above step S130 specifically includes:

Step S410, using a pre-configured sliding window, traversing the statistical results of the gray histogram, and determining the position of the peak of the statistical result of the gray histogram.

In this step, the pre-configured sliding window refers to the sliding window that has been pre-configured with parameters such as sampling range, sampling threshold, and continuous sampling interval; the grayscale histogram statistical result refers to the grayscale histogram of the target two-dimensional code image. Graph statistics, the obtained grayscale histogram statistical results; the position of the peak of the grayscale histogram statistical results refers to the grayscale histogram statistics determined after traversing the aforementioned grayscale histogram statistical results using the aforementioned pre-configured sliding window The position of the peak of the result.

In practical applications, the above continuous sampling interval can be set to start from the minimum value of the pixel gray value 0, and then slide to the end of the maximum value of the pixel gray value 255, so as to traverse the statistical results of the above gray histogram, and then find Find the position of the peak in the statistical result of the grayscale histogram.

Step S420, on the side close to the origin in the statistical results of the gray histogram, determine the starting position of the value range based on the shortest distance from the position of the peak to the equilibrium position.

In this step, the grayscale histogram statistical result refers to the grayscale histogram statistical result obtained by performing grayscale histogram statistics on the target two-dimensional code image; in the grayscale histogram statistical result, the side close to the origin, It refers to the side close to 0 (ie, the origin of the Cartesian coordinate system) in the statistical results of the gray histogram; , after traversing the statistical results of the gray histogram, determine the position of the peak of the statistical result of the gray histogram; the shortest distance from the position of the peak to the equilibrium position refers to the position from the peak to the equilibrium position (that is, the slope of the average change is relatively small The shortest distance of the small gentle position); the value range refers to the value range where the conversion threshold corresponding to the target two-dimensional code image is located; the starting point position of the value range refers to the value close to the origin in the aforementioned grayscale histogram statistical results On one side of , based on the shortest distance from the position of the wave peak to the equilibrium position, determine the starting position of the value range where the conversion threshold corresponding to the target two-dimensional code image is located.

In step S430, the end position of the value range is obtained according to the start position of the value range and the preset translation step.

In this step, the value range refers to the value range where the conversion threshold corresponding to the target two-dimensional code image is located; the starting point of the value range refers to the side close to the origin in the aforementioned grayscale histogram statistical results, based on The shortest distance from the position of the peak to the equilibrium position, the starting position of the value range where the conversion threshold corresponding to the determined target two-dimensional code image is located; The X-axis value of the Cartesian coordinate system in the statistical results of the degree histogram increases, and the preset translation step length of the specific distance for translation; the end position of the value range refers to the starting position of the aforementioned value range and the aforementioned preset Set the translation step, starting from the starting position of the value range, and after the corresponding distance in the direction of increasing the X-axis value of the Cartesian coordinate system in the gray histogram statistical result, obtain the end position of the obtained value range.

The above embodiment successfully avoids the inconspicuous black dots in the two-dimensional code image that may be caused by overexposure of the image by dynamically selecting the value range of the conversion threshold for binary conversion of the two-dimensional code image. On the basis of the problem, the image quality of the two-dimensional code image after binarization processing is improved, and the accuracy of recognition for the two-dimensional code image is effectively improved.

Regarding the specific way of setting the sliding window for sampling, in one embodiment, the sampling range of the sliding window is determined based on the width value of the sliding window; the sampling threshold of the sliding window is determined based on the height value of the sliding window Sure.

Regarding the specific manner of obtaining the processing result corresponding to the target two-dimensional code image, in one embodiment, as shown in FIG. 5, the above step S150 specifically includes:

Step S510, according to the start position of the value range, the end position of the value range and the intermediate conversion threshold, perform binarization conversion processing on the target two-dimensional code image, and obtain a processing result corresponding to the target two-dimensional code image.

In this step, the value range refers to the value range where the conversion threshold corresponding to the target two-dimensional code image is located; the starting point of the value range refers to the side close to the origin in the aforementioned grayscale histogram statistical results, based on The shortest distance from the position of the wave peak to the equilibrium position, the starting position of the value range where the conversion threshold corresponding to the determined target two-dimensional code image is located; Set the translation step length, starting from the starting position of the value range, and after moving the corresponding distance in the direction of increasing the X-axis value of the Cartesian coordinate system in the gray histogram statistical results, obtain the end position of the obtained value range; the middle The conversion threshold refers to the intermediate conversion threshold corresponding to the target two-dimensional code image determined based on the intermediate value of the value range; the processing result corresponding to the target two-dimensional code image refers to the starting position, the above-mentioned The target two-dimensional code image is subjected to binarization conversion processing based on the end position of the value range and the aforementioned intermediate conversion threshold, and then the three processing results corresponding to the target two-dimensional code image are obtained (that is, based on the starting point position of the aforementioned value range, for After the target two-dimensional code image is binarized and converted, the first processing result corresponding to the target two-dimensional code image is obtained; based on the end position of the aforementioned value range, after the target two-dimensional code image is binarized and converted , the second processing result corresponding to the target two-dimensional code image obtained; based on the aforementioned intermediate conversion threshold, after the target two-dimensional code image is binarized and converted, the third processing result corresponding to the target two-dimensional code image is obtained ).

Step S520, based on the processing result corresponding to the target two-dimensional code image, identify the target two-dimensional code image.

In this step, the processing result corresponding to the target two-dimensional code image refers to performing binary conversion on the target two-dimensional code image based on the starting position of the aforementioned value range, the end position of the aforementioned value range, and the aforementioned intermediate conversion threshold. Processing, and then obtained three processing results corresponding to the target two-dimensional code image; based on the processing results corresponding to the target two-dimensional code image, identifying the target two-dimensional code image refers to the three types of processing corresponding to the aforementioned target two-dimensional code image in turn As a result, recognition and analysis are performed.

In practical applications, the specific way of identifying and analyzing the three processing results corresponding to the above-mentioned target two-dimensional code image in turn may be to send the three processing results corresponding to the above-mentioned target two-dimensional code image to the wireless network camera in sequence In the built-in two-dimensional code recognition library, the recognition and analysis of two-dimensional code images are carried out.

The above embodiment improves the accuracy of the binarized two-dimensional code image by obtaining the processing result corresponding to the target two-dimensional code image based on the starting position, end position and intermediate conversion threshold of the value range where the conversion threshold is located. The image quality keeps more useful information in the two-dimensional code image, thereby effectively improving the recognition accuracy of the two-dimensional code image.

It should be understood that although the steps in the flow charts involved in the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flow charts involved in the above-mentioned embodiments may include multiple steps or stages, and these steps or stages are not necessarily executed at the same time, but may be performed at different times For execution, the execution order of these steps or stages is not necessarily performed sequentially, but may be executed in turn or alternately with other steps or at least a part of steps or stages in other steps.

Based on the same inventive concept, an embodiment of the present application further provides a two-dimensional code image processing device for implementing the above-mentioned X two-dimensional code image processing method. The solution to the problem provided by the device is similar to the implementation described in the above method, so the specific limitations in one or more embodiments of the two-dimensional code image processing device provided below can be referred to above for the two-dimensional code The limitation of the image processing method will not be repeated here.

In one embodiment, as shown in FIG. 6, a two-dimensional code image processing device is provided, which is applied to a wireless network camera, and the device 600 includes:

An image sampling module 610, configured to sample the cropped original two-dimensional code image to obtain the two-dimensional code image to be analyzed;

The grayscale mapping module 620 is configured to process the two-dimensional code image to be analyzed based on the mapping relationship between the actual grayscale value of the two-dimensional code image to be analyzed and the target grayscale value, to obtain the target two-dimensional code image;

The threshold range determination module 630 is configured to perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range where the conversion threshold corresponding to the target two-dimensional code image is located based on the grayscale histogram statistical results;

An intermediate threshold determination module 640, configured to determine an intermediate conversion threshold corresponding to the target two-dimensional code image based on the intermediate value of the value range;

The processing result acquisition module 650 is configured to perform binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold, to obtain a processing result corresponding to the target two-dimensional code image.

In one of the embodiments, the image sampling module 610 is specifically configured to perform edge cropping on the original two-dimensional code image based on a preset image size to obtain a cropped original two-dimensional code image; Sampling is performed alternately and alternately to obtain the image of the two-dimensional code to be analyzed.

In one of the embodiments, the grayscale mapping module 620 is specifically configured to determine the value interval where the actual grayscale value of each pixel of the two-dimensional code image to be analyzed is located based on the image brightness gain information; Value range and preset grayscale mapping rules, determine the target grayscale value corresponding to each actual grayscale value; based on the target grayscale value, process the two-dimensional code image to be analyzed to obtain the target two-dimensional code image .

In one of the embodiments, the threshold range determination module 630 is specifically configured to use a pre-configured sliding window to traverse the statistical results of the gray histogram to determine the position of the peak of the statistical result of the gray histogram; On the side close to the origin in the statistical results of the gray histogram, determine the starting position of the value range based on the shortest distance from the position of the peak to the equilibrium position; according to the starting position of the value range and the preset translation step Long, get the end position of the value range.

In one of the embodiments, in the threshold range determination module 630, the sampling range of the sliding window is determined based on the width value of the sliding window; the sampling threshold of the sliding window is based on the height value of the sliding window Make sure.

In one of the embodiments, the processing result acquisition module 650 is specifically configured to perform processing on the target two-dimensional code image according to the start position of the value range, the end position of the value range, and the intermediate conversion threshold Binarization conversion processing to obtain a processing result corresponding to the target two-dimensional code image; based on the processing result corresponding to the target two-dimensional code image, identify the target two-dimensional code image.

Each module in the above-mentioned two-dimensional code image processing device can be fully or partially realized by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, and can also be stored in the memory of the computer device in the form of software, so that the processor can invoke and execute the corresponding operations of the above-mentioned modules.

In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure may be as shown in FIG. 7 . The computer device includes a processor, a memory, an input/output interface (Input/Output, I/O for short), and a communication interface. Wherein, the processor, the memory and the input/output interface are connected through the system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store data related to two-dimensional code image processing and the like. The input/output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a two-dimensional code image processing method is realized.

Those skilled in the art can understand that the structure shown in Figure 7 is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation to the computer equipment on which the solution of this application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, where a computer program is stored in the memory, and the processor implements the steps in the foregoing method embodiments when executing the computer program.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the foregoing method embodiments are implemented.

In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the foregoing method embodiments are implemented.

It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all It is information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any reference to storage, database or other media used in the various embodiments provided in the present application may include at least one of non-volatile and volatile storage. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive variable memory (ReRAM), magnetic variable memory (Magnetoresistive Random Access Memory, MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (Phase Change Memory, PCM), graphene memory, etc. The volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory. As an illustration and not a limitation, the RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM). The databases involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a blockchain-based distributed database, etc., but is not limited thereto. The processors involved in the various embodiments provided by this application can be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., and are not limited to this.

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above-mentioned embodiments only express several implementation modes of the present application, and the description thereof is relatively specific and detailed, but should not be construed as limiting the patent scope of the present application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be determined by the appended claims.

Claims (10)

1. A two-dimensional code image processing method is characterized in that, being applied to a wireless network camera, the method comprises: Sampling the cropped original QR code image to obtain the QR code image to be analyzed; Based on the mapping relationship between the actual grayscale value of the two-dimensional code image to be analyzed and the target grayscale value, process the two-dimensional code image to be analyzed to obtain the target two-dimensional code image; Perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the grayscale histogram statistical result; Determine an intermediate conversion threshold corresponding to the target two-dimensional code image based on an intermediate value of the value range; Perform binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold to obtain a processing result corresponding to the target two-dimensional code image. 2. The method according to claim 1, wherein the sampling of the clipped original two-dimensional code image to obtain the two-dimensional code image to be analyzed comprises: Based on the preset image size, edge cutting is performed on the original two-dimensional code image to obtain the original two-dimensional code image after cutting; Sampling the cropped original two-dimensional code image by row and by column to obtain the two-dimensional code image to be analyzed. 3. The method according to claim 1, wherein the two-dimensional code to be analyzed is processed based on the mapping relationship between the actual gray value of the two-dimensional code image to be analyzed and the target gray value. image to get the target QR code image, including: Based on the image brightness gain information, determine the value interval where the actual gray value of each pixel of the two-dimensional code image to be analyzed is located; Determine a target gray value corresponding to each actual gray value according to the value range and preset gray mapping rules; Based on the target gray value, the to-be-analyzed two-dimensional code image is processed to obtain the target two-dimensional code image. 4. The method according to claim 1, wherein the determination of the value range where the conversion threshold corresponding to the target two-dimensional code image is located based on the statistical results of the gray histogram comprises: Using a pre-configured sliding window, traversing the statistical results of the gray histogram, and determining the position of the peak of the statistical result of the gray histogram; On the side close to the origin in the statistical results of the gray histogram, determine the starting position of the value range based on the shortest distance from the position of the peak to the equilibrium position; The end position of the value range is obtained according to the start position of the value range and the preset translation step. 5. The method according to claim 4, wherein the sampling range of the sliding window is determined based on the width value of the sliding window; the sampling threshold of the sliding window is based on the height value of the sliding window Make sure. 6. The method according to claim 4 or 5, wherein, according to the value range and the intermediate conversion threshold, the target two-dimensional code image is subjected to binarization conversion processing to obtain the The processing results corresponding to the target QR code image, including: According to the start position of the value range, the end position of the value range, and the intermediate conversion threshold, perform binarization conversion processing on the target two-dimensional code image to obtain a corresponding value of the target two-dimensional code image process result; Identifying the target two-dimensional code image based on a processing result corresponding to the target two-dimensional code image. 7. A two-dimensional code image processing device, characterized in that it is applied to a wireless network camera, and the device includes: The image sampling module is used to sample the cropped original two-dimensional code image to obtain the two-dimensional code image to be analyzed; A grayscale mapping module, configured to process the two-dimensional code image to be analyzed based on the mapping relationship between the actual grayscale value of the two-dimensional code image to be analyzed and the target grayscale value, to obtain the target two-dimensional code image; A threshold range determination module, configured to perform grayscale histogram statistics on the target two-dimensional code image, and determine the value range of the conversion threshold corresponding to the target two-dimensional code image based on the grayscale histogram statistical results; An intermediate threshold determination module, configured to determine an intermediate conversion threshold corresponding to the target two-dimensional code image based on the intermediate value of the value range; The processing result acquisition module is configured to perform binarization conversion processing on the target two-dimensional code image according to the value range and the intermediate conversion threshold to obtain a processing result corresponding to the target two-dimensional code image. 8. A computer device, comprising a memory and a processor, the memory stores a computer program, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program step. 9. A computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are realized. 10. A computer program product, comprising a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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