WO2021159802A1 - Graphical captcha recognition method, apparatus, computer device, and storage medium - Google Patents

Abstract

A graphical CAPTCHA recognition method and apparatus, a computer device, and a storage medium, comprising: performing, according to an image processing rule, numerical extraction on input verification code images to obtain a sample library; determining target pixels in an image to be recognized originating from a management server; separating among the target pixels to obtain character images comprising a single character and digitizing said character images to obtain character features corresponding to each character image; acquiring from the sample library, according to matching rules, verification code information matching the character features, and feeding back to the management server verification information comprising verification code information. On the basis of image recognition technology and relating to the field of artificial intelligence, a sample library using digitization for storage is obtained. Performing recognition on images to be recognized on the basis of the sample library to obtain verification code information, compared to using a character picture to perform image verification code recognition, greatly reduces the storage space occupied by the sample library while improving the recognition efficiency of images to be recognized.

Description

Graphic verification code identification method, device, computer equipment and storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on September 4, 2020, the application number is 202010921075.9, and the invention title is "graphic verification code identification method, device, computer equipment, and storage medium". The entire content is approved The reference is incorporated in this application.

Technical field

This application relates to the field of image recognition technology, to application scenarios related to smart city image recognition, and in particular to a method, device, computer equipment, and storage medium for recognizing a graphic verification code.

Background technique

Large enterprises will involve testing the program in the process of program development. In the process of logging in and testing the program, you need to enter the corresponding verification code information according to the provided graphic verification code. Image recognition technology can be used to verify the information contained in the graphic verification code. The verification code characters are recognized to obtain the corresponding verification code information. However, the inventor found that the existing graphic verification code recognition method needs to store a large number of character pictures in the character library, and complete the recognition of the graphic verification code through character image matching. This recognition method causes the character library to require a large amount of storage Space, and the process of image matching takes a lot of time, which affects the efficiency of identifying the image verification code. Therefore, there is a problem that the recognition efficiency is not high when recognizing the verification image in the existing technical method.

Summary of the invention

The embodiments of the present application provide a method, device, computer equipment and storage medium for recognizing a graphic verification code, aiming to solve the problem of low recognition efficiency that exists when recognizing a verification image in the prior art method.

In the first aspect, an embodiment of the present application provides a method for identifying a graphic verification code, which includes:

If the verification code image set input by the user is received, all the verification code images contained in the verification code image set are numerically extracted according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library contains multiple verification characters and character template features corresponding to each verification character;

If an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel judgment rule in the image processing rule;

Segmenting from the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

Digitize the character pixels in each of the character images according to the digitization rule in the image processing rules to obtain character features corresponding to each of the character images;

Acquiring verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character;

The combination of the identification information of the image to be identified and the verification code information is fed back to the management server as verification information corresponding to the image to be identified.

In the second aspect, an embodiment of the present application provides a graphic verification code recognition device, which includes:

The sample library construction unit is used to, if the verification code image set input by the user is received, numerically extract all the verification code images contained in the verification code image set according to the preset image processing rules to obtain the verification code image set Corresponding sample library, the sample library includes a plurality of verification characters and character template characteristics corresponding to each verification character;

The target pixel determining unit is configured to, if an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel determination rule in the image processing rule;

A character image acquisition unit, configured to segment the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

A character feature acquiring unit, configured to digitize the character pixels in each character image according to the digitization rule in the image processing rule to obtain the character feature corresponding to each character image;

The verification code information acquiring unit is configured to acquire verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character ；

The verification information feedback unit is configured to feed back the combination of the identification information of the image to be identified and the verification code information as verification information corresponding to the image to be identified to the management server.

In a third aspect, an embodiment of the present application provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and running on the processor, and the processor executes the computer The program implements the pattern verification code recognition method described in the first aspect.

In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the above-mentioned first On the one hand, the graphic verification code recognition method.

The embodiments of the present application provide a method, device, computer equipment, and storage medium for identifying a graphic verification code. According to the image processing rules, the input verification code image is numerically extracted to obtain a sample library, the corresponding target pixel is determined from the image to be recognized from the management server, and the target pixel is segmented to obtain a character image containing a single character. Numericalization is performed to obtain the character feature corresponding to each character image, the verification code information matching the character feature in the sample library is obtained according to the matching rule, and the verification information including the verification code information is fed back to the management server. Through the above method, a sample library that is stored in a numerical form can be obtained, and based on the obtained sample library, the image to be recognized is recognized to obtain the verification code information. Compared with the use of character pictures for image verification code recognition, the sample library can be greatly reduced Need to occupy the storage space, and improve the efficiency of identifying the graphic verification code.

Description of the drawings

In order to explain the technical solutions of the embodiments of the present application more clearly, the following will briefly introduce the drawings used in the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present application. Ordinary technicians can obtain other drawings based on these drawings without creative work.

FIG. 1 is a schematic flowchart of a method for identifying a graphic verification code provided by an embodiment of the application;

2 is a schematic diagram of an application scenario of a method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 3 is a diagram showing the use effect of the graphic verification code recognition method provided by the embodiment of the application;

FIG. 4 is a schematic diagram of a sub-process of a method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 5 is a schematic diagram of another sub-flow of the method for identifying a graphic verification code according to an embodiment of the application;

FIG. 6 is a schematic diagram of another sub-process of the method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 7 is a schematic diagram of another sub-process of the method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 8 is a schematic diagram of another sub-process of the method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 9 is a schematic diagram of another sub-flow of the method for identifying a graphic verification code provided by an embodiment of the application;

FIG. 10 is a schematic block diagram of a graphic verification code recognition device provided by an embodiment of the application;

FIG. 11 is a schematic block diagram of a computer device provided by an embodiment of the application.

Detailed ways

The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application.

It should be understood that when used in this specification and appended claims, the terms "including" and "including" indicate the existence of the described features, wholes, steps, operations, elements and/or components, but do not exclude one or The existence or addition of multiple other features, wholes, steps, operations, elements, components, and/or collections thereof.

It should also be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in the specification of this application and the appended claims, unless the context clearly indicates other circumstances, the singular forms "a", "an" and "the" are intended to include plural forms.

It should be further understood that the term "and/or" used in the specification and appended claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations .

Please refer to FIG. 1 and FIG. 2. FIG. 1 is a schematic flowchart of a method for identifying a graphic verification code provided by an embodiment of the present application, and FIG. 2 is a schematic diagram of an application scenario of the method for recognizing a graphic verification code provided by an embodiment of the present application. The graphic verification code recognition method is applied to the user terminal 10. The method is executed by application software installed in the user terminal 10. The user terminal 10 communicates with at least one management server 20, and the user can input the verification code image set into the user The terminal 10 creates a sample library. If receiving an image to be identified from any management server 20, the user terminal 10 can identify the image to be identified through the sample library to obtain the corresponding verification information containing the verification code information and feed it back to The management server 20 can complete the process of recognizing the image to be recognized. The user terminal 10 is a terminal device that is used to perform a graphic verification code recognition method to identify the image to be recognized and obtain verification code information, such as a desktop computer, a notebook computer, a tablet computer, or a mobile phone, etc., and the management server 20 can send the image to be recognized Enterprise terminal to user terminal 10. As shown in Fig. 1, the method includes steps S110 to S160.

S110. If the verification code image set input by the user is received, numerically extract all verification code images contained in the verification code image set according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library includes multiple verification characters and character template features corresponding to each verification character.

If the verification code image set input by the user is received, all the verification code images contained in the verification code image set are numerically extracted according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library contains multiple verification characters and character template features corresponding to each verification character. Among them, the user is the user of the user terminal, and the user can be a tester who performs a login test on the program in the enterprise. In order to recognize the image to be recognized from the management server, the user needs to input the verification code image set to build the sample library. And accurately recognize the image to be recognized through the constructed sample library. The image processing rules include pixel judgment rules and digitization rules. The verification code image set contains multiple verification code images and a verification character matching the verification code image. The verification code image is an image containing verification characters. , The verification character is a specific character information contained in the image. The verification character can be the character information obtained by manually recognizing the image containing the verification character. The verification character can be uppercase letters, lowercase letters, Arabic numerals, and One or more of Chinese characters. Specifically, a verification character may include a matching image in the verification code image set, and a verification character may also correspond to multiple images, and various fonts have different ways of writing a verification character.

For example, if the verification character "Five" corresponds to multiple images with multiple fonts, each image corresponds to one font, and each image contains image information obtained by writing "Five" in one font. , Multiple images corresponding to "Five" and multiple different fonts can be added to the verification code image collection; increasing the number of images matching the verification characters can significantly improve the accuracy of the recognition of the verification image to be recognized.

The sample library is to store sample information used to identify the verification image to be recognized. The sample library contains multiple verification characters and one or more character template features that match each verification character.

For example, the four images corresponding to the verification character "five" are respectively digitized, and each image can get a corresponding character template feature, and finally four character template features corresponding to "five" can be obtained , That is, the obtained sample library contains four character template features corresponding to the verification character "five".

According to the pixel judgment rules in the image processing rules, the effective pixels corresponding to each verification code image can be obtained, and the effective pixels corresponding to the effective pixels can be cropped according to the position information of the effective pixels. The pixel is digitized to obtain the character template feature corresponding to each verification code image. The character template feature is the numerical information used to reflect the effective pixel feature, and the character template feature is corresponded and stored to obtain the sample library.

In an embodiment, as shown in FIG. 4, step S110 includes sub-steps S111, S112, and S113.

S111. Determine effective pixels corresponding to each image according to the image information of each verification code image in the verification code image set and the pixel determination rule.

Determine the effective pixel corresponding to each image according to the image information of each verification code image in the verification code image set and the pixel judgment rule. The pixel judgment rules include grayscale rules and grayscale thresholds. The verification code image contains several pixels, and each pixel contains a corresponding pixel value in the image, and the pixel value corresponding to the pixel corresponds to the image Image information. The pixel judgment rule is the rule information for judging the pixel value of each pixel. According to the pixel value of the pixel contained in the verification code image and the pixel judgment rule, the effective pixel corresponding to the image can be determined. Specifically, if the verification code image is a color image, each pixel in the color image corresponds to a pixel value on the three color channels of red (R), green (G), and blue (B) corresponding to RGB; if The verification code image is a grayscale image, and each pixel in the grayscale image corresponds to a pixel value on the color channel of black. The pixel value is represented by a non-negative integer, and its value range is [0,255] Take the color channel of black as an example. If the pixel value of a certain pixel is 0, it means that the color of the pixel is black. If the pixel value of a certain pixel is 255, it means that the color of the pixel is white, and the pixel value is other The value indicates that the color of the pixel is a specific gray scale between white and black.

In one embodiment, as shown in FIG. 5, step S111 includes sub-steps S1111, S1112, and S1113.

S1111, grayscale each verification code image according to the grayscale rules to obtain a grayscale image matching each verification code image; S1112, perform grayscale image processing on the pixels contained in the grayscale image Determine whether the gray value of is greater than the gray threshold to obtain pixels whose gray value is not greater than the gray threshold; S1113, determine whether each pixel with the gray value not greater than the gray threshold is isolated , To remove isolated pixels from the pixels whose gray value is not greater than the gray threshold value to obtain the effective pixel.

If the verification code image is not a grayscale image, you can perform grayscale processing on the image through the grayscale rule to obtain the corresponding grayscale image. The grayscale rule can convert the pixel value of each pixel in RGB In order to correspond to a pixel value on the color channel of black; if the verification code image is a grayscale image, there is no need to perform grayscale processing. Fig. 3 is an effect diagram of the graphic verification code recognition method provided by an embodiment of the application, and the gray image obtained after gray-scale processing is shown in Fig. 3-(a). Determine whether the pixel value of each pixel in the grayscale image is greater than the grayscale threshold, and obtain all pixels that are not greater than the grayscale threshold. For example, if the grayscale threshold is 80, you can determine the pixel value of each pixel to obtain the pixel Pixels with a value not greater than 80; since the effective information that can be identified from the image is a pixel block formed by connecting multiple pixels, the pixel block formed by connecting multiple pixels in the image can be used as an effective pixel , Specifically, whether each pixel obtained is not greater than the grayscale threshold is judged in isolation, that is, whether each pixel is connected to other pixels whose pixel value is not greater than the grayscale threshold. If connected, the judgment result is The pixel is not isolated; if it is not connected, the judgment result is that the pixel is isolated, and the effective pixel can be obtained by removing the isolated pixel. The image corresponding to the obtained effective pixel is shown in Figure 3-(b).

S112: Extract an effective image including the effective pixel according to the position information of the effective pixel in each of the images.

The effective image including the effective pixel is extracted according to the position information of the effective pixel in each of the images. Specifically, the coordinate value of each effective pixel in the image in the image is the position information of the effective pixel. According to the position information of the effective pixel, the effective image containing the effective pixel can be extracted from the image. The obtained effective image is as As shown in Figure 3-(c).

In an embodiment, step S112 includes the sub-steps: determining the rectangular boundary of the effective pixel according to the position information of the effective pixel in one of the images; extracting the corresponding rectangular image from the effective pixels according to the rectangular boundary; The rectangular image is binarized to obtain an effective image containing only black and white.

Determine a rectangular boundary corresponding to the effective pixel according to the position information of the effective pixel in the image. The rectangular boundary is a rectangular frame determined according to the coordinate value of the outermost effective pixel in the effective pixel, and the rectangle is extracted from the effective pixel according to the rectangular boundary. Image, the rectangular image contains all effective pixels, the rectangular image is binarized, all effective pixels are changed to black, and other pixels in the rectangular image are changed to white, that is, the resulting effective image contains only black and Two colors of white.

S113: Perform digitization on each of the effective images according to the digitization rule to obtain character template characteristics corresponding to each of the verification code images.

Perform digitization on each of the valid images according to the digitization rule to obtain character template characteristics corresponding to each of the verification code images. According to the digitization rule, it is the rule information for digitizing the valid image. After digitizing the valid image, the character template feature corresponding to the valid image can be obtained. The character template feature is the feature of the verification code image through the numerical value. Quantitatively expressed feature information, the character template feature includes a size array and a coordinate array. The size array is used to represent the size of the effective image, and the coordinate array can be used to represent the coordinate value of each effective pixel in the effective image.

In an embodiment, as shown in FIG. 6, step S113 includes sub-steps S1131, S1132, and S1133.

S1131. Obtain the size information of a piece of the effective image, and generate a size array corresponding to the size information according to the digitization rule; S1132, obtain the coordinate information of all effective pixels in the effective image, and according to the digitization The rule and the coordinate information generate a coordinate array corresponding to each of the effective pixels; S1133. Use the size array and all the coordinate arrays as character template features of a verification code image corresponding to the effective image.

For example, if the size information of a valid image is: 25 pixels in length and 15 pixels in width, the size array corresponding to the effective image is {25, 15}; a valid pixel in the effective image is located in the third row and the seventh column , Then the coordinate array corresponding to the effective pixel is {3, 7}.

S120: If an image to be recognized from the management server is received, determine a target pixel corresponding to the image to be recognized according to the pixel determination rule in the image processing rule.

If the image to be recognized from the management server is received, the target pixel corresponding to the image to be recognized is determined according to the pixel determination rule in the image processing rule. When the user logs in to the webpage or mailbox through the user terminal, the management server will send the image to be recognized to the user terminal. The image to be recognized is the graphic verification code that needs to be recognized. The graphic verification code consists of one or more verification code characters. According to the pixel judgment rule in the image processing rule, the pixel in the image to be recognized is judged and the corresponding target pixel is obtained. The pixel judgment rule includes the gray scale rule and the gray threshold.

In one embodiment, step S120 includes the sub-steps: grayscale the image to be recognized according to the grayscale rule to obtain a grayscale image to be recognized that matches the image to be recognized; Identify whether the gray value of the pixels contained in the grayscale image is greater than the gray threshold value to determine to obtain pixels with gray value greater than the gray threshold value; for each pixel whose gray value is greater than the gray threshold value Whether or not to be isolated is determined, so as to remove isolated pixels from the pixels whose grayscale value is greater than the grayscale threshold to obtain the target pixel. Specifically, the method of obtaining the corresponding target pixel from the image to be recognized is the same as the method of obtaining the corresponding effective pixel from the verification code image, and will not be further described here.

S130: According to a preset image adjustment rule and the position information of the target pixel, a character image containing a single character is obtained by segmenting the target pixel.

According to a preset image adjustment rule and the position information of the target pixel, a character image containing a single character is obtained by segmenting the target pixel. Specifically, according to the position information of each pixel in the target pixel, a segmented image containing a single character can be segmented from the target pixel, and the segmented image can be adjusted according to the image adjustment rules to obtain a character image containing only a single character , That is, according to the number of characters contained in the target pixel, multiple character images with the same number of characters can be obtained.

In one embodiment, as shown in FIG. 7, step S130 includes sub-steps S131, S132, and S133.

S131. Obtain, according to the position information of each pixel in the target pixel, a pixel block formed by connecting a plurality of pixels in the target pixel; each of the pixel blocks includes a character.

A pixel block formed by connecting a plurality of pixels in the target pixel is obtained according to the position information of each pixel in the target pixel; each of the pixel blocks includes a character. Since a single character is a pixel block formed by connecting multiple pixels, according to the position information of the target pixel, a pixel block connected with multiple pixels is used as a pixel block corresponding to a character.

S132: Extract a segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel.

Extracting a segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel. Specifically, a rectangular boundary corresponding to the pixel block can be determined according to the position of a certain pixel block in the target pixel, and the rectangular boundary is determined according to the coordinate value of the outermost pixel in the pixel block According to the rectangle boundary, extract a segmented image corresponding to the pixel block from the target pixel.

S133. Adjust the segmented images according to the image adjustment rule to obtain a character image corresponding to each segmented image.

The segmented image is adjusted according to the image adjustment rule to obtain a character image corresponding to each segmented image. Specifically, the segmented images can be adjusted according to the feature information such as the size of the segmented images to obtain a character image corresponding to each segmented image. Specifically, the image adjustment rules include one of enlargement, reduction, cropping, and rotation. Or more, the adjusted character image is an image that meets the image adjustment rules.

S140: Perform digitization on the character pixels in each of the character images according to the digitization rules in the image processing rules to obtain character features corresponding to each of the character images.

The character pixels in each of the character images are digitized according to the digitization rules in the image processing rules to obtain character features corresponding to each of the character images. According to the digitization rule, it is the rule information for digitizing the character pixels contained in the character image. After digitizing a character image, the character feature corresponding to the character image can be obtained. The character feature is the numerical value of the character The feature information that is quantified by the feature of the image. The character feature also includes a size array and a coordinate array. The size array is used to represent the size of the character image, and the coordinate array can be used to represent the coordinate value of each character pixel in the character image.

In one embodiment, step S140 includes sub-steps: obtaining size information of a piece of the character image, generating a size array corresponding to the size information according to the digitization rule; obtaining the size of all character pixels in the character image For coordinate information, a coordinate array corresponding to each character pixel is generated according to the digitization rule and the coordinate information; the size array and all the coordinate arrays are used as character features corresponding to the character image.

The method of obtaining the corresponding character feature from the character image is the same as the method of obtaining the corresponding character template feature from the valid image, and will not be explained here.

S150. Obtain verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, where the verification code information includes at least one verification character.

Acquire verification code information matching the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character. Specifically, the number of character images contained in the image to be recognized is equal to the number of verification characters in the verification code information, and each character image corresponds to a character feature. The sample library corresponding to each character feature can be obtained according to the matching rules. For a verification character, the verification code information corresponding to the image to be recognized can be obtained by combining the obtained verification characters.

In an embodiment, as shown in FIG. 8, step S150 includes sub-steps S151 and S152.

S151. Obtain a verification character corresponding to each character feature in the sample library according to the matching rule.

Acquire one verification character corresponding to each character feature in the sample library according to the matching rule. The matching rule includes a size threshold, a pixel density calculation formula, and a density threshold. The size threshold is threshold information used to determine whether the size ratio of the character feature matches the size ratio of the character template feature. The size ratio can be based on the size array If the difference between the size ratio of the character feature and the size ratio of the character template feature is not greater than the size threshold, the two match, otherwise the two do not match; the pixel density calculation formula is used to obtain The character feature or character template feature is calculated to obtain the calculation formula of the corresponding pixel density. If the pixel density corresponding to the character feature is larger, it means that the character image corresponding to the character feature contains more character pixels per unit area, and vice versa It indicates that the character image corresponding to the character feature contains fewer character pixels per unit area; the density threshold is the threshold information used to determine whether the pixel density of the character feature matches the pixel density of the character template feature, if If the difference between the pixel density of the character feature and the pixel density of the character template feature is not greater than the density threshold, the two match, otherwise the two do not match.

According to the above method, the qualified character template feature combination is obtained as a second feature set corresponding to a character feature, and the matching degree between each character template feature in the second feature set and the character feature is calculated, and a matching character is obtained by screening. The character template feature with the highest feature matching degree, and the verification character of the character template feature is further obtained as the verification character of the character feature. According to the above method, a verification character corresponding to each character feature can be obtained.

In an embodiment, as shown in FIG. 9, step S151 includes sub-steps S1511, S1512, S1513, and S1514.

S1511, according to the size threshold, obtain a character template feature whose size ratio matches a size ratio of the character feature in the sample library to obtain a first feature set.

For example, the size array of a character feature is {25, 15}, the size array of a character template feature in the sample library is {20, 10}, and the size threshold is 0.3; the size ratio of the character feature is 1.6667, and the character The size ratio of the template feature is 2, and the difference between the two size ratios is 0.3333, which is greater than the size threshold, then the character template feature does not match the character feature.

S1512. Calculate the first pixel density of the character feature and the second pixel density of each character template feature in the first feature set according to the pixel density calculation formula.

Calculating the pixel density takes a character feature as an example. The number of coordinate arrays included in the character feature is obtained and divided by the product of the values in the size array to obtain the pixel density of the character feature. The pixel density calculation formula can be expressed as:

M=N/(C ₁ ×C ₂ ) (1);

Among them, M is the pixel density of the character feature, N is the number of coordinate arrays in the character feature _{, C 1 is the first value of the size array in the character feature, and C 2 is} the second value of the size array in the character feature .

If the size array of a character feature is {25, 15} and the number of coordinate arrays in the component feature is 60, the corresponding pixel density M=60/(25×15)=0.16. The method of calculating the pixel density of the character template feature is the same as the above method.

S1513. Determine whether the difference between the first pixel density and each of the second pixel densities is less than the density threshold, so as to obtain character template features whose difference is less than the density threshold as a second feature set .

S1514. Calculate the matching degree between the character feature and each character template feature in the second feature set, and obtain the verification character corresponding to the character template feature with the highest matching degree in the second feature set as the character The feature corresponds to the verification character.

Specifically, the value of each coordinate array in the character feature is divided by the size array of the character feature to obtain the vector array corresponding to each coordinate array. For example, the size array of a certain character feature is {25, 15}, where If a certain coordinate array is {3, 7}, a vector array corresponding to the coordinate array is calculated to be {3/25, 7/15}, that is, {0.12, 0.4667}. Obtain the vector array of each character template feature in the second feature set in the same way, obtain the number of arrays where the vector array of a character template feature coincides with the vector array of the character feature, and divide the number of coincident arrays by the character feature's vector array The calculation result obtained by the vector array is used as the matching degree between the character template feature and the character feature. According to the above method, the matching degree between each character template feature in the second feature set and the character feature is calculated, and the verification character corresponding to the character template feature with the highest matching degree is obtained as the verification character corresponding to the character feature.

S152. Combine the verification characters according to the sequence of the character features to obtain verification code information corresponding to the character features.

The verification characters are combined according to the sequence of the character features to obtain verification code information corresponding to the character features. The character image obtained after segmentation of the image to be recognized has a certain sequence, and the sequence of the character image is the same as the sequence of the character features, and a verification character corresponding to each character feature can be combined according to the sequence of the character features , In order to obtain the verification code information consisting of multiple verification characters arranged in a predetermined order.

For example, the verification code information obtained after recognizing a certain image to be recognized is "T4bP".

S160. Feed the combination of the identification information of the image to be identified and the verification code information as verification information corresponding to the image to be identified to the management server.

The combination of the identification information of the image to be identified and the verification code information is fed back to the management server as verification information corresponding to the image to be identified. The image to be identified also contains an identification information corresponding to the image to be identified. The identification information can uniquely identify each image to be identified. The user terminal can perform identification information corresponding to the image to be identified and the obtained verification code information. Combination to obtain the corresponding verification information and feed it back to the management server. After receiving the verification information, the management server can obtain the target verification code matching the identification information in the verification information, so as to obtain the verification information in the verification information according to the target verification code. Verification code information is verified.

The technical methods in this application can be applied to application scenarios that include graphic verification code recognition, such as smart government/smart city management/smart community/smart security/smart logistics/smart healthcare/smart education/smart environmental protection/smart transportation, so as to promote smart cities Construction.

In the graphic verification code recognition method provided by the embodiments of the present application, the input verification code image is numerically extracted according to the image processing rules to obtain a sample library, and the corresponding target pixel is determined from the image to be recognized from the management server, and from The target pixel is segmented to obtain a character image containing a single character, the character image is digitized to obtain the character feature corresponding to each character image, and the verification code information matching the character feature in the sample library is obtained according to the matching rule, which will contain the verification code The verification information of the information is fed back to the management server. Through the above method, a sample library that is stored in a numerical form can be obtained, and based on the obtained sample library, the image to be recognized is recognized to obtain the verification code information. Compared with the use of character pictures for image verification code recognition, the sample library can be greatly reduced Need to occupy the storage space, and improve the efficiency of identifying the graphic verification code.

The embodiment of the present application also provides a graphic verification code recognition device, which is used to execute any embodiment of the foregoing graphic verification code recognition method. Specifically, please refer to FIG. 10, which is a schematic block diagram of a graphic verification code recognition apparatus provided by an embodiment of the present application. The graphic verification code recognition device can be configured in the user terminal.

As shown in FIG. 10, the graphic verification code recognition device 100 includes a sample library construction unit 110, a target pixel determination unit 120, a character image acquisition unit 130, a character feature acquisition unit 140, a verification code information acquisition unit 150, and a verification information feedback unit 160.

The sample library construction unit 110 is configured to, if the verification code image set input by the user is received, digitally extract all the verification code images contained in the verification code image set according to a preset image processing rule to obtain a verification code image A sample library corresponding to the set, the sample library includes a plurality of verification characters and a character template feature corresponding to each verification character.

In an embodiment, the sample library construction unit 110 includes a sub-unit effective pixel determination unit, an effective image acquisition unit, and a numerical processing unit.

The effective pixel determination unit is used to determine the effective pixel corresponding to each image according to the image information of each verification code image in the verification code image set and the pixel judgment rule; the effective image acquisition unit is used to determine the effective pixel corresponding to each image according to the The position information of the effective pixels in the image extracts the effective image including the effective pixels; the digitization processing unit is configured to digitize each of the effective images according to the digitization rule to obtain the verification code image Corresponding character template characteristics.

In an embodiment, the effective pixel determination unit includes sub-units: a gray image acquisition unit, a gray value judgment unit, and a pixel removal unit.

A gray-scale image acquisition unit, configured to gray-scale each verification code image according to the gray-scale rule to obtain a gray-scale image matching each verification code image; a gray-scale value judgment unit, It is used to judge whether the gray value of the pixels contained in the gray image is greater than the gray threshold value, so as to obtain the pixels whose gray value is not greater than the gray threshold value; Whether each pixel whose gray value is not greater than the gray threshold is judged in isolation, so as to remove isolated pixels from the pixels whose gray value is not greater than the gray threshold to obtain the effective pixel.

In an embodiment, the effective image acquisition unit includes sub-units: a rectangular boundary determination unit, a rectangular image extraction unit, and a binarization processing unit.

A rectangular boundary determining unit, configured to determine a rectangular boundary of the effective pixel according to the position information of an effective pixel in the image; a rectangular image extracting unit, configured to extract a corresponding rectangular image from the effective pixel according to the rectangular boundary; The binarization processing unit is configured to binarize the rectangular image to obtain an effective image containing only black and white.

In an embodiment, the numerical processing unit includes sub-units: a size array generating unit, a coordinate array generating unit, and a character template feature acquiring unit.

The size array generation unit is used to obtain the size information of the valid image, and the size array corresponding to the size information is generated according to the digitization rule; the coordinate array generation unit is used to obtain all the valid images in the effective image. The coordinate information of the pixel generates a coordinate array corresponding to each effective pixel according to the digitization rule and the coordinate information; the character template feature acquisition unit is used to take the size array and all the coordinate arrays as the AND The character template feature of a verification code image corresponding to the effective image.

The target pixel determining unit 120 is configured to, if an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel determination rule in the image processing rule.

The character image acquisition unit 130 is configured to segment the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel.

In an embodiment, the character image acquisition unit 130 includes sub-units: a pixel block acquisition unit, a segmented image acquisition unit, and an image adjustment unit.

The pixel block obtaining unit is configured to obtain, according to the position information of each pixel in the target pixel, a pixel block formed by connecting a plurality of pixels in the target pixel; each of the pixel blocks includes a character The segmented image acquisition unit is used to extract the segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel; the image adjustment unit is used to adjust the image according to the image adjustment rule The segmented images are adjusted to obtain a character image corresponding to each of the segmented images.

The character feature acquiring unit 140 is configured to digitize the character pixels in each character image according to the digitization rule in the image processing rule to obtain the character feature corresponding to each character image.

The verification code information obtaining unit 150 is configured to obtain verification code information matching the character feature in the sample library according to the preset matching rules and the character feature, and the verification code information includes at least one of the verification code information. character.

In an embodiment, the verification code information acquiring unit 150 includes sub-units: a verification character matching unit and a verification character combination unit.

The verification character matching unit is used to obtain a verification character corresponding to each character feature in the sample library according to the matching rule; the verification character combination unit is used to compare the verification character according to the sequence of the character features The combination is performed to obtain the verification code information corresponding to the character feature.

In an embodiment, the verification character matching unit includes subunits: a first feature set acquisition unit, a pixel density acquisition unit, a second feature set acquisition unit, and a verification character determination unit.

The first feature set obtaining unit is configured to obtain, according to the size threshold, the character template feature whose size ratio matches the size ratio of one of the character features in the sample library to obtain the first feature set; the pixel density obtaining unit uses The first pixel density of the character feature and the second pixel density of each character template feature in the first feature set are calculated according to the pixel density calculation formula; the second feature set acquisition unit is used to determine the first Whether the difference between the pixel density and each of the second pixel densities is less than the density threshold, so as to obtain the character template features whose difference is less than the density threshold as the second feature set; the verification character determination unit uses To calculate the matching degree between the character feature and each character template feature in the second feature set, obtain the verification character corresponding to the character template feature with the highest matching degree in the second feature set as the character feature Corresponding to the verification character.

The verification information feedback unit 160 is configured to feed back the combination of the identification information of the image to be identified and the verification code information as verification information corresponding to the image to be identified to the management server.

In the graphic verification code recognition device provided by the embodiment of the application, the graphic verification code recognition method is applied to numerically extract the input verification code image according to the image processing rules to obtain a sample library, which is determined from the to-be-recognized image from the management server The corresponding target pixel is segmented from the target pixel to obtain a character image containing a single character, the character image is digitized to obtain the character feature corresponding to each character image, and the verification code matching the character feature in the sample library is obtained according to the matching rule Information, the verification information containing the verification code information is fed back to the management server. Through the above method, a sample library that is stored in a numerical form can be obtained, and based on the obtained sample library, the image to be recognized is recognized to obtain the verification code information. Compared with the use of character pictures for image verification code recognition, the sample library can be greatly reduced Need to occupy the storage space, and improve the efficiency of identifying the graphic verification code.

The above-mentioned graphic verification code recognition device can be implemented in the form of a computer program, and the computer program can be run on a computer device as shown in FIG. 11.

Please refer to FIG. 11, which is a schematic block diagram of a computer device according to an embodiment of the present application.

Referring to FIG. 11, the computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.

The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, the processor 502 can execute the graphic verification code identification method.

The processor 502 is used to provide calculation and control capabilities, and support the operation of the entire computer device 500.

The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute the graphic verification code identification method.

The network interface 505 is used for network communication, such as providing data information transmission. Those skilled in the art can understand that the structure shown in FIG. 11 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

Wherein, the processor 502 is configured to run a computer program 5032 stored in the memory, so as to implement the corresponding function in the above-mentioned graphic verification code identification method.

Those skilled in the art can understand that the embodiment of the computer device shown in FIG. 11 does not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or less components than those shown in the figure. Or some parts are combined, or different parts are arranged. For example, in some embodiments, the computer device may only include a memory and a processor. In such an embodiment, the structures and functions of the memory and the processor are consistent with the embodiment shown in FIG. 11, and will not be repeated here.

It should be understood that, in this embodiment of the application, the processor 502 may be a central processing unit (Central Processing Unit, CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSPs), Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor.

In another embodiment of the present application, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium, or may be a volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, where the computer program implements the steps included in the above-mentioned graphic verification code recognition method when the computer program is executed by the processor.

Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working process of the above-described equipment, device, and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here. A person of ordinary skill in the art may be aware that the units and algorithm steps of the examples described in the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both, in order to clearly illustrate the hardware and software Interchangeability, in the above description, the composition and steps of each example have been generally described in accordance with the function. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Professionals and technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of this application.

In the several embodiments provided in this application, it should be understood that the disclosed equipment, device, and method may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, or the units with the same function may be combined into one. Units, for example, multiple units or components can be combined or integrated into another system, or some features can be omitted or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may also be electrical, mechanical or other forms of connection. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application. In addition, the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product can be stored in a computer. The read storage medium includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned computer-readable storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), magnetic disk or optical disk and other media that can store program codes. The above are only specific implementations of this application, but the protection scope of this application is not limited to this. Any person skilled in the art can easily think of various equivalents within the technical scope disclosed in this application. Modifications or replacements, these modifications or replacements shall be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims (20)

1. A graphic verification code recognition method, which includes:

   If the verification code image set input by the user is received, all the verification code images contained in the verification code image set are numerically extracted according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library contains multiple verification characters and character template features corresponding to each verification character;

   If an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel judgment rule in the image processing rule;

   Segmenting from the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

   Digitize the character pixels in each of the character images according to the digitization rule in the image processing rules to obtain character features corresponding to each of the character images;

   Acquiring verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character;

   The combination of the identification information of the image to be identified and the verification code information is fed back to the management server as verification information corresponding to the image to be identified.
2. The method for recognizing a graphic verification code according to claim 1, wherein the image processing rule includes a pixel judgment rule and a digitization rule, and all verification codes contained in the verification code image set are processed according to a preset image processing rule. The image is extracted numerically to obtain a sample library corresponding to the captcha image set, including:

   Determine the effective pixels corresponding to each image according to the image information and pixel judgment rules of each verification code image in the verification code image set;

   Extracting an effective image including the effective pixels according to the position information of the effective pixels in each of the images;

   Perform digitization on each of the valid images according to the digitization rule to obtain character template characteristics corresponding to each of the verification code images.
3. The method for recognizing a graphic verification code according to claim 2, wherein the pixel judgment rule includes a gray scale rule and a gray threshold, and the judgment is based on the image information and pixel of each verification code image in the verification code image set The rules determine the effective pixels corresponding to each of the images, including:

   Grayscale each of the verification code images according to the grayscale rule to obtain a grayscale image matching each of the verification code images;

   Judging whether the gray value of the pixels contained in the gray image is greater than the gray threshold value, so as to obtain pixels whose gray value is not greater than the gray threshold value;

   It is determined whether each pixel with the gray value not greater than the gray threshold is isolated, so as to remove the isolated pixels from the pixels with the gray value not greater than the gray threshold to obtain the effective pixel.
4. 4. The graphic verification code recognition method according to claim 2, wherein the digitizing each of the valid images according to the digitization rule to obtain the character template characteristics corresponding to each of the verification code images includes :

   Acquiring size information of the effective image, and generating a size array corresponding to the size information according to the digitization rule;

   Acquiring coordinate information of all effective pixels in the effective image, and generating a coordinate array corresponding to each effective pixel according to the digitization rule and the coordinate information;

   The size array and all the coordinate arrays are used as character template features of a verification code image corresponding to the valid image.
5. The method for recognizing a graphic verification code according to claim 1, wherein the segmenting to obtain a character image containing a single character from the target pixel according to a preset image adjustment rule and the position information of the target pixel comprises:

   Acquiring, according to the position information of each pixel in the target pixel, a pixel block formed by connecting a plurality of pixels in the target pixel; each of the pixel blocks includes a character;

   Extracting a segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel;

   The segmented image is adjusted according to the image adjustment rule to obtain a character image corresponding to each segmented image.
6. The method for recognizing a graphic verification code according to claim 1, wherein the obtaining verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature comprises:

   Obtaining a verification character corresponding to each character feature in the sample library according to the matching rule;

   The verification characters are combined according to the sequence of the character features to obtain verification code information corresponding to the character features.
7. The method for recognizing a graphic verification code according to claim 6, wherein the matching rule includes a size threshold, a pixel density calculation formula, and a density threshold, and the sample library is obtained according to the matching rule. A verification character corresponding to the character feature, including:

   Acquiring, according to the size threshold, a character template feature whose size ratio matches a size ratio of the character feature in the sample library to obtain a first feature set;

   Calculating the first pixel density of the character feature and the second pixel density of each character template feature in the first feature set according to the pixel density calculation formula;

   Judging whether the difference between the first pixel density and each of the second pixel densities is less than the density threshold, so as to obtain character template features whose difference is less than the density threshold as a second feature set;

   Calculate the matching degree between the character feature and each character template feature in the second feature set, and obtain the verification character corresponding to the character template feature with the highest matching degree in the second feature set as the corresponding character feature Verify characters.
8. A graphic verification code recognition device, including:

   The sample library construction unit is used to, if the verification code image set input by the user is received, numerically extract all the verification code images contained in the verification code image set according to the preset image processing rules to obtain the verification code image set Corresponding sample library, the sample library includes a plurality of verification characters and character template characteristics corresponding to each verification character;

   The target pixel determining unit is configured to, if an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel determination rule in the image processing rule;

   A character image acquisition unit, configured to segment the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

   A character feature acquiring unit, configured to digitize the character pixels in each character image according to the digitization rule in the image processing rule to obtain the character feature corresponding to each character image;

   The verification code information acquiring unit is configured to acquire verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character ；

   The verification information feedback unit is configured to feed back the combination of the identification information of the image to be identified and the verification code information as verification information corresponding to the image to be identified to the management server.
9. A computer device includes a memory, a processor, and a computer program stored on the memory and capable of running on the processor, wherein the processor implements the following steps when the processor executes the computer program:

   If the verification code image set input by the user is received, all the verification code images contained in the verification code image set are numerically extracted according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library contains multiple verification characters and character template features corresponding to each verification character;

   If an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel judgment rule in the image processing rule;

   Segmenting from the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

   Digitize the character pixels in each of the character images according to the digitization rule in the image processing rules to obtain character features corresponding to each of the character images;

   Acquiring verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character;

   The combination of the identification information of the image to be identified and the verification code information is fed back to the management server as verification information corresponding to the image to be identified.
10. 9. The computer device according to claim 9, wherein the image processing rules include pixel judgment rules and digitization rules, and all the verification code images contained in the verification code image set are numerically evaluated according to the preset image processing rules. To obtain a sample library corresponding to the verification code image set, including:

    Determine the effective pixels corresponding to each image according to the image information and pixel judgment rules of each verification code image in the verification code image set;

    Extracting an effective image including the effective pixels according to the position information of the effective pixels in each of the images;

    Perform digitization on each of the valid images according to the digitization rule to obtain character template characteristics corresponding to each of the verification code images.
11. The computer device according to claim 10, wherein the pixel judgment rule includes a gray scale rule and a gray threshold, and the pixel judgment rule is determined according to the image information and pixel judgment rule of each verification code image in the verification code image set. The effective pixels corresponding to each of the images include:

    Grayscale each of the verification code images according to the grayscale rule to obtain a grayscale image matching each of the verification code images;

    Judging whether the gray value of the pixels contained in the gray image is greater than the gray threshold value, so as to obtain pixels whose gray value is not greater than the gray threshold value;

    It is determined whether each pixel with the gray value not greater than the gray threshold is isolated, so as to remove the isolated pixels from the pixels with the gray value not greater than the gray threshold to obtain the effective pixel.
12. 10. The computer device according to claim 10, wherein the digitizing each of the valid images according to the digitizing rule to obtain the character template characteristics corresponding to each of the verification code images comprises:

    Acquiring size information of the valid image, and generating a size array corresponding to the size information according to the digitization rule;

    Acquiring coordinate information of all effective pixels in the effective image, and generating a coordinate array corresponding to each effective pixel according to the digitization rule and the coordinate information;

    The size array and all the coordinate arrays are used as character template features of a verification code image corresponding to the valid image.
13. 9. The computer device according to claim 9, wherein the segmenting to obtain a character image containing a single character from the target pixel according to a preset image adjustment rule and the position information of the target pixel comprises:

    Acquiring, according to the position information of each pixel in the target pixel, a pixel block formed by connecting a plurality of pixels in the target pixel; each of the pixel blocks includes a character;

    Extracting a segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel;

    The segmented image is adjusted according to the image adjustment rule to obtain a character image corresponding to each segmented image.
14. 9. The computer device according to claim 9, wherein said obtaining the verification code information that matches the character feature in the sample library according to the preset matching rule and the character feature comprises:

    Obtaining a verification character corresponding to each character feature in the sample library according to the matching rule;

    The verification characters are combined according to the sequence of the character features to obtain verification code information corresponding to the character features.
15. The computer device according to claim 14, wherein the matching rule includes a size threshold, a pixel density calculation formula, and a density threshold, and the sample library corresponding to each character feature in the sample library is obtained according to the matching rule A verification character of, including:

    Acquiring, according to the size threshold, a character template feature whose size ratio matches a size ratio of the character feature in the sample library to obtain a first feature set;

    Calculating the first pixel density of the character feature and the second pixel density of each character template feature in the first feature set according to the pixel density calculation formula;

    Judging whether the difference between the first pixel density and each of the second pixel densities is less than the density threshold, so as to obtain character template features whose difference is less than the density threshold as a second feature set;

    Calculate the matching degree between the character feature and each character template feature in the second feature set, and obtain the verification character corresponding to the character template feature with the highest matching degree in the second feature set as the corresponding character feature Verify characters.
16. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the following operations:

    If the verification code image set input by the user is received, all the verification code images contained in the verification code image set are numerically extracted according to the preset image processing rules to obtain a sample library corresponding to the verification code image set. The sample library contains multiple verification characters and character template features corresponding to each verification character;

    If an image to be recognized from the management server is received, determine the target pixel corresponding to the image to be recognized according to the pixel judgment rule in the image processing rule;

    Segmenting from the target pixel to obtain a character image containing a single character according to a preset image adjustment rule and the position information of the target pixel;

    Digitize the character pixels in each of the character images according to the digitization rule in the image processing rules to obtain character features corresponding to each of the character images;

    Acquiring verification code information that matches the character feature in the sample library according to a preset matching rule and the character feature, and the verification code information includes at least one verification character;

    The combination of the identification information of the image to be identified and the verification code information is fed back to the management server as verification information corresponding to the image to be identified.
17. The computer-readable storage medium according to claim 16, wherein the image processing rules include pixel judgment rules and digitization rules, and the verification codes included in the verification code image set are processed according to the preset image processing rules. The image is extracted numerically to obtain a sample library corresponding to the captcha image set, including:

    Determine the effective pixels corresponding to each image according to the image information and pixel judgment rules of each verification code image in the verification code image set;

    Extracting an effective image including the effective pixels according to the position information of the effective pixels in each of the images;

    Perform digitization on each of the valid images according to the digitization rule to obtain character template characteristics corresponding to each of the verification code images.
18. The computer-readable storage medium according to claim 17, wherein the pixel judgment rule includes a grayscale rule and a grayscale threshold, and the judgment is based on the image information and pixel of each verification code image in the verification code image set The rules determine the effective pixels corresponding to each of the images, including:

    Grayscale each of the verification code images according to the grayscale rule to obtain a grayscale image matching each of the verification code images;

    Judging whether the gray value of the pixels contained in the gray image is greater than the gray threshold value, so as to obtain pixels whose gray value is not greater than the gray threshold value;

    It is determined whether each pixel with the gray value not greater than the gray threshold is isolated, so as to remove the isolated pixels from the pixels with the gray value not greater than the gray threshold to obtain the effective pixel.
19. 18. The computer-readable storage medium according to claim 17, wherein the digitizing each of the valid images according to the digitizing rule to obtain character template features corresponding to each of the verification code images includes :

    Acquiring size information of the effective image, and generating a size array corresponding to the size information according to the digitization rule;

    Acquiring coordinate information of all effective pixels in the effective image, and generating a coordinate array corresponding to each effective pixel according to the digitization rule and the coordinate information;

    The size array and all the coordinate arrays are used as character template features of a verification code image corresponding to the valid image.
20. 15. The computer-readable storage medium according to claim 16, wherein the segmenting to obtain a character image containing a single character from the target pixel according to a preset image adjustment rule and the position information of the target pixel comprises:

    Acquiring, according to the position information of each pixel in the target pixel, a pixel block formed by connecting a plurality of pixels in the target pixel; each of the pixel blocks includes a character;

    Extracting a segmented image corresponding to each pixel block according to the position of the pixel block in the target pixel;

    The segmented image is adjusted according to the image adjustment rule to obtain a character image corresponding to each segmented image.

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