CN111860475A - Image processing method and device, electronic device and storage medium - Google Patents
Image processing method and device, electronic device and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses an image processing method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: performing key point detection on the acquired card image to acquire predicted position information of a plurality of key points of a target card in the card image; determining the integrity of the target card contained in the card image based on predicted position information of a plurality of key points of the target card; determining whether to store the card image based at least in part on the integrity of the target card contained in the card image facilitates improving card recognition accuracy and user experience.
Description
Technical Field
The present application relates to the field of computer vision technologies, and in particular, to an image processing method and apparatus, an electronic device, and a storage medium.
Background
Card identification refers to a technology of processing a card image by using a computer vision technology to identify information recorded on a card included in the card image. Taking the bank card as an example, the user needs to record the information of the bank card when handling a new bank card to bind the bank card with the user, however, the efficiency of manually inputting the information of the bank card is low and is easy to make mistakes, the user experience is poor, the bank card photo is shot and the bank card photo is processed by utilizing the bank card recognition technology, so that the recognition of the information of the bank card is realized, the processing efficiency and the accuracy can be improved, and the user experience is improved.
Disclosure of Invention
The embodiment of the application provides an image processing method and device, electronic equipment and a storage medium.
A first aspect of an embodiment of the present application provides an image processing method, including:
performing key point detection on the acquired card image to acquire predicted position information of a plurality of key points of a target card in the card image;
determining the integrity of the target card contained in the card image based on predicted position information of a plurality of key points of the target card;
determining whether to store the card image based at least in part on an integrity of the target card contained in the card image.
In an alternative embodiment, the plurality of keypoints of the target card comprise a plurality of vertices of the target card.
In an optional embodiment, the determining the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card comprises:
determining whether a plurality of key points of the target card are located within the card image based on predicted position information of the plurality of key points and boundary position information of the card image;
Determining an integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image.
In an alternative embodiment, the determining the integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image comprises:
determining that the target card contained in the card image is missing in response to at least one keypoint of the plurality of keypoints not being within the card image.
In an alternative embodiment, the determining the integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image comprises:
in response to at least one first keypoint of the plurality of keypoints not being within the card image, obtaining a minimum distance of the at least one first keypoint to a boundary of the target card;
determining that the target card contained in the card image is absent in response to the presence of a keypoint of the at least one first keypoint whose minimum distance to the boundary of the target card is greater than the preset threshold.
In an optional embodiment, the method further comprises:
determining that the target card contained in the card image is complete in response to the minimum distances from the at least one first keypoint to the boundary of the target card being less than or equal to the preset threshold.
In an optional implementation manner, before the determining the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card, the method further includes:
performing correction processing on the card image to obtain the card image subjected to correction processing;
the determining whether to store the card image includes:
and determining whether to store the card image after the correction processing.
In an alternative embodiment, the determining whether to store the card image based at least in part on the integrity of the target card contained in the card image comprises:
in response to determining that the target card contained in the card image is intact, storing the card image.
In an optional embodiment, the method further comprises:
performing text recognition on the card image, and determining a text recognition result of the target card;
The determining whether to store the card image based at least in part on the integrity of the target card contained in the card image comprises:
determining whether to store the card image based at least in part on an integrity of the target card contained in the card image and a text recognition result of the target card.
In an optional embodiment, the method further comprises:
outputting first prompt information in response to determining that the target card contained in the card image is missing, wherein the first prompt information is used for prompting at least one of missing of the target card contained in the card image, missing position of the target card and adjusting placement position of the target card.
In an optional implementation manner, before the performing the keypoint detection on the acquired card image, the method further includes:
and sending second prompt information to prompt the user to place the target card in a specified area.
In an alternative embodiment, the target card includes one or any combination of an identification card, a bank card, a passport, a driver's license, a driving license, and a social security card.
A second aspect of the embodiments of the present application provides an image processing apparatus, including: a prediction module, an integrity detection module, and a storage module, wherein:
The prediction module is used for detecting key points of the acquired card image to acquire predicted position information of a plurality of key points of a target card in the card image;
the integrity detection module is used for determining the integrity of the target card contained in the card image based on the predicted position information of a plurality of key points of the target card;
the storage module is configured to determine whether to store the card image based at least in part on an integrity of the target card included in the card image.
Optionally, the plurality of key points of the target card include a plurality of vertices of the target card.
In an optional implementation manner, the integrity detection module is specifically configured to:
determining whether a plurality of key points of the target card are located within the card image based on predicted position information of the plurality of key points and boundary position information of the card image;
determining an integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image.
In an optional implementation manner, the integrity detection module is specifically further configured to:
Determining that the target card contained in the card image is missing in response to at least one keypoint of the plurality of keypoints not being within the card image.
In an optional implementation manner, the integrity detection module is further specifically configured to:
in response to at least one first keypoint of the plurality of keypoints not being within the card image, obtaining a minimum distance of the at least one first keypoint to a boundary of the target card;
determining that the target card contained in the card image is absent in response to the presence of a keypoint of the at least one first keypoint whose minimum distance to the boundary of the target card is greater than the preset threshold.
In an optional implementation manner, the integrity detection module is further specifically configured to:
determining that the target card contained in the card image is complete in response to the minimum distances from the at least one first keypoint to the boundary of the target card being less than or equal to the preset threshold.
In an optional embodiment, the apparatus further comprises a turning module, configured to:
before the integrity detection module determines the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card, performing correction processing on the card image to obtain the corrected card image;
The storage module is specifically configured to determine whether to store the card image subjected to the correction processing.
In an optional implementation manner, the storage module is specifically configured to:
in response to determining that the target card contained in the card image is intact, storing the card image.
In an optional implementation manner, the system further comprises an identification module, configured to perform text identification on the card image, and determine a text identification result of the target card;
the storage module is further configured to determine whether to store the card image based at least in part on an integrity of the target card included in the card image and a text recognition result of the target card.
In an optional embodiment, the card processing device further includes an output module, configured to output first prompt information in response to determining that the target card included in the card image is missing, where the first prompt information is used to prompt at least one of the missing target card, the missing position of the target card, and the adjusting of the placement position of the target card included in the card image.
In an optional implementation manner, the system further includes a prompt module, configured to send second prompt information to prompt a user to place the target card in a specified area before the prediction module performs the key point detection on the acquired card image.
Optionally, the target card includes one or any combination of an identity card, a bank card, a passport, a driving license and a social security card,
A third aspect of embodiments of the present application provides an electronic device, including a processor and a memory, where the memory is configured to store a computer program configured to be executed by the processor, and the processor is configured to perform some or all of the steps described in any one of the methods of the first aspect of embodiments of the present application.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program is configured to cause a computer to perform some or all of the steps described in any one of the methods of the first aspect of embodiments of the present application.
A fifth aspect of the present application provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the method of the first aspect and any of its possible implementations.
In the embodiment of the application, the predicted position information of a plurality of key points of a target card in the card image is obtained by performing key point detection on the obtained card image, the integrity of the target card contained in the card image is determined based on the predicted position information of the plurality of key points of the target card, and whether the card image is stored or not is determined at least partially based on the integrity of the target card contained in the card image, so that the card identification accuracy is improved and the user experience is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic flowchart of an image processing method disclosed in an embodiment of the present application;
FIG. 2 is a schematic diagram of a card image disclosed in an embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of another image processing method disclosed in the embodiments of the present application;
FIG. 4 is a schematic view of the integrity of a target card disclosed in the embodiments of the present application;
FIG. 5 is a schematic structural diagram of an image processing apparatus disclosed in an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The term "and/or" in the present application is only one kind of association relationship describing the associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C. The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The image processing apparatus according to the embodiments of the present application is an apparatus that can process an image, and may be an electronic device, which includes a terminal device, and in particular, the terminal device includes, but is not limited to, other portable devices such as a mobile phone, a laptop computer, or a tablet computer having a touch-sensitive surface (e.g., a touch screen display and/or a touch pad). It should also be understood that in some embodiments, the device is not a portable communication device, but is a desktop computer having a touch-sensitive surface (e.g., a touch screen display and/or touchpad).
The following describes embodiments of the present application in detail.
Referring to fig. 1, fig. 1 is a schematic flowchart of an image processing method according to an embodiment of the present disclosure, and as shown in fig. 1, the image processing method includes the following steps.
101. And carrying out key point detection on the acquired card image to obtain the predicted position information of a plurality of key points of the target card in the card image.
The main body of the image processing method may be the above-described image processing apparatus, for example, the image processing method may be executed by a terminal device or a server or other processing device, where the terminal device may be a User Equipment (UE), a mobile device, a user terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like. In some possible implementations, the image processing method may be implemented by a processor calling computer readable instructions stored in a memory.
In this embodiment of the application, the card image may be an image acquired by a camera, for example, a picture taken by a camera of a terminal device, or a screenshot in a video taken by the camera of the terminal device, and this is not limited in this embodiment of the application.
The card image may include the target card, and optionally the target card may be rectangular, such as rectangular, or in any other shape. The shape of the target card is not limited in the embodiments of the present application.
Optionally, the target card includes one or any combination of an identity card, a bank card, a passport, a driving license, and a social security card, and may also be a document such as a paper contract and an agreement, which is not limited in this embodiment of the present application.
The method can be used for detecting key points of the acquired card image and obtaining the predicted position information of a plurality of key points of the target card in the card image. In one possible implementation, a Convolutional Neural Network (CNN) may be used to perform keypoint detection on the card image, and obtain predicted position information of a plurality of keypoints of the target card, where the predicted position information of the keypoints may include coordinates of the keypoints.
Specifically, the position information of the key points of the target card in the card image may be output, for example, two-dimensional coordinates of the plurality of key points may be output.
In image processing, a key point is essentially a feature that is an abstract description of a fixed region or spatial physical relationship that describes a composition or context within a certain neighborhood. It is not just a point information, or represents a location, but rather the combined relationship of the context to the surrounding neighborhood.
For example, in the task of detecting key points of a face, there are 28 key points, or 64 and 128 key points which are relatively popular at present, where each point represents a class of features in different faces and has a certain commonality, and the class of features includes not only some characteristics of pixels, such as feature points of lips, but also the positional relationship between lips and face.
The neural network for realizing the key point detection may be an existing key point detection network, for example, one branch may be used for regression of pixel points, and the other branch may be used for regression of the relationship of the pixel points. The point label and relation label defining method reduces the difficulty of regression, the multi-stage calculation mode used in the network is equivalent to providing a certain prediction result for each stage, the next stage performs multi-stage precision experiment on the result, and the similar method can be applied to various fields.
For example, as shown in fig. 2, the card image shown in fig. 2 includes the target card, and the key points of the target card include four vertices l, m, o, and n of the target card, and specifically, predicted coordinates of the four key points may be obtained. Because the possibility that the vertex (angle) position exceeds the shooting range is high when the general certificate shooting is incomplete, the key point is selected as the vertex position of the target card, the accuracy of image integrity detection can be higher, and the judgment is quicker.
The image boundary in the embodiment of the application can also be called as one of the most classical and basic problems in image processing and computer vision when the image edge is the most basic characteristic edge detection of the image, and has important application in many aspects such as object identification, three-dimensional reconstruction, image matching, retrieval and the like.
Generally, when the target card (such as an identity card, a bank card, a passport, a driving license, or a social security card) is located in a complicated background, the edge of the target card is often one of the most important information. Optionally, the boundary of the target card in the card image, that is, the position of the frame of the certificate, may be determined by detecting the edge of the card image, so as to better determine the key point. Specifically, edge point position information in the card image can be obtained by using an edge detection algorithm, such as a roberts operator, a sobel operator, a prewitt operator, and the like, and edge contour information can also be obtained by using a subsequent tracking algorithm, such as a canny operator.
In an alternative embodiment, the boundary of the target card in the card image may be determined, and then the predicted position information of the plurality of key points of the target card in the card image may be obtained.
Specifically, the convex hull of the target card can be obtained through a key point detection algorithm, and then the boundary of the convex hull is used as the boundary of the target card.
The above-mentioned keypoint detection algorithm may be any method for inputting a plurality of points on a plane and outputting their convex hulls, such as a rotating kayak method, a Graham scanning method, a Jarvis stepping method algorithm, and the like, and may also include a related algorithm in OpenCV. OpenCV is a BSD license (open source) based distributed cross-platform computer vision library that can run on Linux, Windows, Android, and Mac OS operating systems. The method is light and efficient, is composed of a series of C functions and a small number of C + + classes, provides interfaces of languages such as Python, Ruby, MATLAB and the like, and realizes a plurality of general algorithms in the aspects of image processing and computer vision.
In a real vector space V, for a given set X, the intersection S of all convex sets containing X is called the convex hull of X. The convex hull of X may be constructed with a convex combination of all points (X1.. Xn) within X.
In general terms, given a set of points on a two-dimensional plane, a convex hull is understood to mean a convex closed figure formed by connecting the outermost points, which can contain all the points of the set of points, which can be represented in the card image as the border of the target card, and on the other hand, at least one of the above-mentioned keypoints can be identified among these points.
After obtaining the predicted position information of the plurality of key points of the target card in the card image, step 102 may be performed.
102. And determining the integrity of the target card included in the card image based on the predicted position information of the plurality of key points of the target card.
The identification of the target card has wide application, and it is very important to detect whether the target card is missing, and in practical application, the target card is often required to be complete, and the image of the target card can be reserved for storage, audit and the like. The integrity of the target card included in the card image may be determined based on predicted position information of a plurality of key points of the target card. The integrity of the target card in the card image can be mainly judged by judging whether a plurality of key points of the target card are in the card image.
Specifically, it may be determined whether or not the plurality of key points are located within the card image based on predicted position information of the plurality of key points of the target card and boundary position information of the card image;
and determining the integrity of the target card contained in the card image based on whether the plurality of key points are located in the card image.
The boundary position information of the card image can be acquired when the card image is processed, and the boundary position information of the card image can comprise the boundary point coordinates of the card image, can be determined based on the edge detection of pixel points, and can also be acquired through image information identification. Optionally, information such as resolution, image format, etc. of the card image may also be obtained. The border of the card image is a rectangle formed by connecting a plurality of straight lines, generally four straight lines.
The positions of the key points and the boundary of the card image can be analyzed and judged to determine whether the target card is missing in the card image. The above-mentioned deficiency can be understood as that the target card does not completely show in the card image, for example, the target card does not completely show due to the shooting angle problem, and there is a partial deficiency, generally, the edge of the target card exceeds the image area.
In a possible embodiment, the determining the integrity of the target card included in the card image based on whether the plurality of key points are located in the card image may include:
and determining that the target card contained in the card image is missing in response to at least one of the plurality of key points not being within the card image.
Whether the plurality of key points are located in the card image can be determined according to the predicted position information of the key points and the boundary position information of the card image.
By determining whether the key point is within the card image, it can be determined whether the target card is missing from the card image. When all the key points are in the card image, it can be determined that the target card is not missing in the card image. And at least one key point in the plurality of key points is not in the card image, which indicates that the key point is out of the card image, namely the target card is not completely shot (a part of the target card exceeds the card image during shooting), so that the target card contained in the card image can be determined to be missing.
The selection and prediction of the key points can be proper, and the judgment of too many key points is not needed, so that the data processing amount is reduced.
In some embodiments, the above-mentioned key point detection may be implemented by a neural network, such as a convolutional neural network or a cyclic neural network. For example, the acquired original card image or the preprocessed card image is input to a neural network for keypoint detection, so as to obtain keypoint information of the target card in the card image, wherein the convolutional neural network may include a plurality of convolutional layers, an activation function, and a plurality of pooling layers. For example, the activation function may include a Linear rectification function (ReLU), which may be more efficient in gradient descent and backward propagation, thereby avoiding the problems of gradient explosion and gradient disappearance. The predicted position information of the key points can be obtained through the convolutional neural network, and optimization can be performed based on the output confidence degree during training.
In some embodiments, the neural network may output location information of a plurality of key points of the target card, or further output detection confidence information of the plurality of key points, such as scores, and the like, which are not limited in this disclosure.
According to the image processing method in the embodiment of the application, the key point detection is carried out through the convolutional neural network, the information of the card image can be well extracted without the recursive neural network, the calculated amount is reduced, and the card identification accuracy is favorably improved.
Optionally, the method further includes: and outputting first prompt information in response to determining that the target card contained in the card image is missing, wherein the first prompt information is used for prompting one of missing of the target card contained in the card image, missing position of the target card, and adjusting placement position of the target card, or any combination thereof. The prompt information may be text information or voice information, where the text information may be displayed in any area inside or outside the card image, or pop up a prompt box, and the like, which is not limited in this embodiment of the application.
Through the first prompt message, the user can be prompted that the target card contained in the card image is missing, the image of the complete target card needs to be uploaded again, the verification or the card storage process is completed successfully, and the missing position of the target card can be indicated in detail in the first prompt message, for example, the missing position is marked in the card image in a mode of displaying the image, or the missing position is indicated through characters, for example, "the upper left corner of the identity card in the image is missing" is uploaded. The user may also be prompted to adjust the placement position of the target card through the first prompt information, specifically, in the certificate verification process, the user may place the certificate at a specified position, an image of the certificate (i.e., the card image) is captured by the image processing device, and when the image processing device determines that the certificate included in the image is missing, the first prompt information may be output to prompt the user to adjust the placement position of the target card to obtain a complete certificate image, such as "please adjust the placement position of the certificate" or "please move the certificate to the upper right", and so on.
In some embodiments, the process may be performed in real time, and in the case that it is determined that the target card included in the currently acquired card image is not complete, the acquisition of the card image may be continued and the detection process may be repeated until a card image satisfying the condition is detected.
103. Determining whether to store the card image based at least in part on an integrity of the target card contained in the card image.
After the integrity test is performed on the target card in the card image in step 102 to obtain a result, it may be determined whether to store the card image.
In an alternative embodiment, the card image may be stored in response to determining that the target card included in the card image is intact.
The target card without the deficiency meets the requirement, the card image can be stored to be used as the storage card of the user, and also can be used as the basis for carrying out identity verification or audit in the next step.
In an alternative embodiment, the method further comprises: performing text recognition on the card image, and determining a text recognition result of the target card;
the step 103 may specifically include:
determining whether to store the card image based at least in part on an integrity of the target card included in the card image and a text recognition result of the target card.
The target card in the card image may contain characters, and text recognition may be performed on the card image to obtain the text recognition result, and whether the target card is of a designated card type or not may be determined by the text recognition result, and if the target card is complete and of the designated card type, the card image may be stored. If the target card is complete but not a designated card type, the card image may not be stored.
In some embodiments, the text recognition described above may be performed with a determination that the target card contained in the card image is complete (i.e., absent). In this way, when the target card in the card image is determined to be missing, text recognition is not performed, so that the time for text recognition can be saved, and the processing efficiency can be improved.
For example, when the certificate image is used for online identity authentication, for example, some application programs need to upload an identity card, a bank card, and the like for identity authentication, text Recognition, for example, Optical Character Recognition (OCR) can be performed to extract text content from the certificate image, whether the type of the certificate to be acquired is, for example, a specific bank, and information such as a certificate number and a card number therein can be extracted, which is convenient for identity authentication or information storage. For another example, some illegal pictures may be uploaded on the social network, and if the pictures contain illegal text, the pictures can be automatically identified for subsequent processing.
It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.
In this embodiment of the application, key point detection may be performed on an acquired card image to obtain predicted position information of a plurality of key points of a target card in the card image, integrity of the target card included in the card image is determined based on the predicted position information of the plurality of key points of the target card, and whether to store the card image is determined based at least in part on the integrity of the target card included in the card image, so that image integrity can be detected, and accuracy of image recognition and information extraction can be improved.
Referring to fig. 3, fig. 3 is a schematic flowchart of another image processing method disclosed in the embodiment of the present application, and fig. 3 is obtained by further optimizing on the basis of fig. 1. The main body for executing the steps of the embodiment of the present application may be the image processing apparatus described above. As shown in fig. 3, the image processing method includes the steps of:
201. and sending out second prompt information to prompt the user to place the target card in the designated area.
The execution subject in the embodiment of the present application may be the image processing apparatus, for example, the image processing method may be executed by a terminal device or a server or other processing device, where the terminal device may be a User Equipment (UE), a mobile device, a user terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like. In some possible implementations, the image processing method may be implemented by a processor calling computer readable instructions stored in a memory.
The target card may be rectangular, such as rectangular. The shape of the target card is not limited in the embodiments of the present application. Optionally, the target card includes one or any combination of an identity card, a bank card, a passport, a driving license, and a social security card, and may also be a document such as a paper contract and an agreement, which is not limited in this embodiment of the present application.
Specifically, the image processing apparatus may send the second prompt message to prompt the user to place the target card in the designated area, and then may acquire the card image of the target card through the camera, so as to execute step 202. The first prompt message may be a text message or a voice message, which is not limited in the embodiment of the present application.
202. And carrying out key point detection on the acquired card image to obtain the predicted position information of a plurality of key points of the target card in the card image.
The step 202 may refer to the detailed description of the step 101 in the embodiment shown in fig. 1, and is not described herein again.
In this embodiment of the application, the card image may be an image acquired by a camera, for example, a picture taken by a camera of a terminal device, or a screenshot in a video taken by the camera of the terminal device, and this is not limited in this embodiment of the application.
Optionally, before step 202, the method further includes:
and carrying out correction processing on the card image to obtain the corrected card image.
Before performing the key point identification on the card image, the image processing apparatus may perform a preliminary image identification to determine whether the target card in the card image is displayed in the forward direction, and if the target card in the card image is not displayed in the forward direction, perform the above-mentioned alignment processing on the card image to obtain the card image after the alignment processing, and then perform step 202.
Through the correction processing, the card image of the target card which is displayed in the forward direction can not be converted into the forward direction for display, and the processing accuracy and the display effect of image recognition are improved.
203. And determining whether the plurality of key points are located in the card image based on the predicted position information of the plurality of key points of the target card and the boundary position information of the card image.
For obtaining the boundary of the card image, reference may be made to the detailed description of step 102 in the embodiment shown in fig. 1, which is not described herein again.
If it is determined that the plurality of key points are located within the card image, step 206 may be performed.
Optionally, if there is at least one first key point in the key points that is not in the card image, step 204 may be executed.
204. And obtaining the minimum distance from at least one first key point to the boundary of the target card in response to the fact that at least one first key point in the plurality of key points is not in the card image.
The predicted position information of the key point of the target card may include two-dimensional coordinates of the key point, that is, the position of the key point and the boundary position of the target card may be accurately determined in the card image according to the established coordinate system, so as to determine whether the key point is in the card image. If at least one of the key points is not in the card image, for convenience of description, the key point which is not in the card image is marked as a first key point, and the minimum distance from the first key point to the boundary of the target card can be further obtained for judgment.
The boundary of the card image is a straight line, and when the position of the key point and the boundary of the card image are known, the minimum distance from the at least one first key point to the boundary of the target card can be calculated and obtained according to a point-to-straight line distance formula.
Further, the at least one first key point may be determined, and whether a minimum distance between the at least one first key point and the boundary of the target card is greater than a preset threshold value may be determined.
If the minimum distance between the at least one first keypoint and the boundary of the target card is less than or equal to the preset threshold, step 205 may be executed; if there is a keypoint of the at least one first keypoint whose minimum distance to the boundary of the target card is greater than the preset threshold, step 207 may be executed.
205. And determining that the target card contained in the card image is complete in response to the minimum distance from the at least one first key point to the boundary of the target card being less than or equal to the preset threshold value.
If the minimum distance from the at least one first keypoint to the boundary of the target card is less than or equal to the preset threshold, it may be understood that the distance from the keypoint not in the card image to the boundary of the target card is not large, and the integrity of the target card is not greatly affected, so that the integrity of the target card included in the card image may be determined. The preset threshold value may be set and adjusted according to requirements, and is not limited herein.
In the case where the target card included in the card image is determined to be complete, step 206 may be performed.
206. And storing the card image.
If the target card contained in the card image is determined to be complete, namely the target card is not missing, namely the card image meets the requirements, the card image can be stored to be used as the information storage card of the user and also be used as the basis for carrying out identity verification or auditing in the next step. Further alternatively, text recognition may be performed on the card image.
For example, when the certificate image is used for online identity authentication, for example, some application programs need to upload an identity card, a bank card, and the like for identity authentication, text Recognition, for example, Optical Character Recognition (OCR) can be performed to extract text content from the certificate image, whether the type of the certificate to be acquired is, for example, a specific bank, and information such as a certificate number and a card number therein can be extracted, which is convenient for identity authentication or information storage. For another example, some illegal pictures may be uploaded on the social network, and if the pictures contain illegal text, the pictures can be automatically identified for subsequent processing.
207. And determining that the target card contained in the card image is absent in response to the fact that the key point with the minimum distance to the boundary of the target card larger than the preset threshold exists in the at least one first key point.
If the minimum distance from at least one of the first keypoints to the boundary of the target card is greater than the preset threshold, it can be understood that the keypoints with the minimum distance from the boundary of the target card greater than the preset threshold are far beyond the distance of the card image, which affects the integrity and information identification of the target card, and thus the target card included in the card image is determined to be missing.
If it is determined that the target card included in the card image is missing, step 208 may be performed.
208. And outputting first prompt information, wherein the first prompt information is used for prompting the adjustment of the placement position of the target card.
When the target card included in the card image is missing, the first presentation information may be output to prompt the user to adjust the placement position of the target card.
Specifically, in the certificate verification process, a user may place a certificate at a designated position, an image of the certificate (i.e., the above-mentioned card image) is captured by the image processing device, and when the image processing device determines that the certificate included in the image is missing, a first prompt message may be output to prompt the user to delete a target card included in the card image and prompt the user to adjust the placement position of the target card, so as to obtain a complete certificate image again, for example, output a "please adjust the placement position of the certificate. Please move the certificate to the upper right and place the certificate in the designated area. The first prompt message may be a text message, a voice message, or the like, which is not limited in this embodiment of the application.
Referring to fig. 4, fig. 4 is a schematic view of processing a card image disclosed in an embodiment of the present application, as shown in fig. 4, a target card a in an image a, whose key points are all in an area within a boundary of the image a, such as a point q, may determine that the target card a is complete in the image a. In the target card B in the image B, the point p of one of the key points is in the area outside the boundary of the image B, so that the target card B can be judged to be missing in the card image B; alternatively, whether the image B is stored may also be determined by determining whether the minimum distance h from the point p to the boundary of the target card B is greater than a preset threshold. The dotted line shown in the figure is the complement of the target card B beyond the image B.
The preset threshold value can be set and modified for the card image processing tasks of different target cards, and the preset threshold value is not limited in the embodiment of the application. For example, the core content of some target cards is concentrated in the middle of the certificate and is far away from the edge of the certificate, and the preset threshold value set at the moment can be larger, because even if the edge and corner of the target card are missing in the card image, the information extraction and verification aiming at the core content are not influenced, and so on, the detection standard can be flexibly adjusted according to the needs, and the flexible adaptability of the image processing method is improved.
It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.
The embodiment of the application prompts a user to place a target card in a designated area by sending second prompt information, performs key point detection on an acquired card image to obtain predicted position information of a plurality of key points of the target card in the card image, determines whether the plurality of key points are located in the card image based on the predicted position information of the plurality of key points of the target card and the boundary position information of the card image, then obtains a minimum distance from at least one first key point to a boundary of the target card in response to the fact that at least one first key point exists in the plurality of key points and is not located in the card image, and determines that the target card contained in the card image is complete in response to the fact that the minimum distance from the at least one first key point to the boundary of the target card is less than or equal to the preset threshold value, the card image can be stored, and in response to the fact that the key point with the minimum distance to the boundary of the target card being greater than the preset threshold value exists in the at least one first key point, the target card contained in the card image is determined to be absent, first prompt information can be output, the first prompt information is used for prompting adjustment of the placement position of the target card, image integrity can be detected, accuracy of image recognition and information extraction is improved, meanwhile detection standards can be flexibly adjusted according to needs to complete different image processing tasks, and adaptability is high.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is to be understood that the image processing apparatus includes hardware structures and/or software modules corresponding to the respective functions in order to implement the above-described functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The embodiment of the present application may perform the division of the functional units for the image processing apparatus according to the method example described above, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present disclosure. As shown in fig. 5, the image processing apparatus 300 includes: a prediction module 310, an integrity detection module 320, and a storage module 330, wherein:
the prediction module 310 is configured to perform key point detection on the acquired card image to obtain predicted position information of a plurality of key points of the target card in the card image;
the integrity detection module 320 is configured to determine integrity of the target card included in the card image based on predicted position information of a plurality of key points of the target card;
the storage module 330 is configured to determine whether to store the card image based at least in part on the integrity of the target card included in the card image.
Optionally, the plurality of key points of the target card include a plurality of vertices of the target card.
Optionally, the integrity detection module 320 is specifically configured to:
determining whether the plurality of key points are located in the card image based on the predicted position information of the plurality of key points of the target card and the boundary position information of the card image;
And determining the integrity of the target card contained in the card image based on whether the plurality of key points are located in the card image.
Optionally, the integrity detection module 320 is further specifically configured to:
and determining that the target card contained in the card image is missing in response to at least one of the plurality of key points not being within the card image.
Optionally, the integrity detection module 320 is further specifically configured to:
in response to at least one first keypoint being absent from the card image among the plurality of keypoints, obtaining a minimum distance from the at least one first keypoint to a boundary of the target card;
and determining that the target card contained in the card image is absent in response to the fact that the key point with the minimum distance to the boundary of the target card larger than the preset threshold exists in the at least one first key point.
Optionally, the integrity detection module 320 is further specifically configured to:
and determining that the target card contained in the card image is complete in response to the minimum distance from the at least one first key point to the boundary of the target card being less than or equal to the preset threshold value.
Optionally, the image processing apparatus 300 further includes a storage module 340, configured to store the card image if the target card is not missing in the card image.
Optionally, the image processing apparatus 300 further includes a correcting module 340, configured to:
before the integrity detection module determines the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card, performing correction processing on the card image to obtain the corrected card image;
the storage module 330 is specifically configured to determine whether to store the card image after the conversion processing.
Optionally, the storage module 330 is specifically configured to:
and in response to determining that the target card included in the card image is complete, storing the card image.
Optionally, the image processing apparatus 300 further includes an identification module 350, configured to perform text identification on the card image, and determine a text identification result of the target card;
the storage module 330 is further configured to determine whether to store the card image based at least in part on the integrity of the target card included in the card image and a text recognition result of the target card.
Optionally, the image processing apparatus 300 further includes an output module 360, configured to output first prompt information in response to determining that the target card included in the card image is missing, where the first prompt information is used to prompt at least one of the target card included in the card image is missing, a missing position of the target card, and an adjustment of a placement position of the target card.
Optionally, the image processing apparatus 300 further includes a prompt module 370, configured to send a second prompt message to prompt a user to place the target card in a designated area before the prediction module performs the key point detection on the acquired card image.
Optionally, the target card includes one or any combination of an identity card, a bank card, a passport, a driving license and a social security card.
The image processing method in the foregoing embodiments of fig. 1 and 3 can be implemented by using the image processing apparatus 300 in the embodiment of the present application.
With the image processing apparatus 300 shown in fig. 5, the image processing apparatus 300 may perform key point detection on the acquired card image to obtain predicted position information of a plurality of key points of a target card in the card image, determine integrity of the target card included in the card image based on the predicted position information of the plurality of key points of the target card, and determine whether to store the card image based at least in part on the integrity of the target card included in the card image, thereby detecting image integrity and improving accuracy of image recognition and information extraction.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the electronic device 400 includes a processor 401 and a memory 402, wherein the electronic device 400 may further include a bus 403, the processor 401 and the memory 402 may be connected to each other through the bus 403, and the bus 403 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus 403 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus. Electronic device 400 may also include input-output device 404, where input-output device 404 may include a display screen, such as a liquid crystal display screen. The memory 402 is used to store computer programs; the processor 401 is adapted to invoke a computer program stored in the memory 402 to perform some or all of the method steps mentioned above in the embodiments of fig. 1 and 3.
With the electronic device 400 shown in fig. 6 implemented, the electronic device 400 may perform key point detection on an acquired card image to obtain predicted position information of a plurality of key points of a target card in the card image, determine integrity of the target card included in the card image based on the predicted position information of the plurality of key points of the target card, and determine whether to store the card image based at least in part on the integrity of the target card included in the card image, which may detect image integrity and improve accuracy of image recognition and information extraction.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium is used to store a computer program, and the computer program enables a computer to execute part or all of the steps of any one of the image processing methods as described in the above method embodiments.
Embodiments of the present application also provide a computer program product containing instructions, which when run on a computer, cause the computer to perform some or all of the steps of any of the image processing methods as described in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units (modules) described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash memory disks, read-only memory, random access memory, magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An image processing method, characterized in that the method comprises:
performing key point detection on the acquired card image to acquire predicted position information of a plurality of key points of a target card in the card image;
determining the integrity of the target card contained in the card image based on predicted position information of a plurality of key points of the target card;
determining whether to store the card image based at least in part on an integrity of the target card contained in the card image.
2. The image processing method of claim 1, wherein the plurality of keypoints for the target card comprise a plurality of vertices for the target card.
3. The image processing method according to claim 2, wherein the determining the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card comprises:
determining whether a plurality of key points of the target card are located within the card image based on predicted position information of the plurality of key points and boundary position information of the card image;
determining an integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image.
4. The image processing method of claim 3, wherein the determining the integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image comprises:
determining that the target card contained in the card image is missing in response to at least one keypoint of the plurality of keypoints not being within the card image.
5. The image processing method of claim 3, wherein the determining the integrity of the target card contained in the card image based on whether the plurality of keypoints is located within the card image comprises:
In response to at least one first keypoint of the plurality of keypoints not being within the card image, obtaining a minimum distance of the at least one first keypoint to a boundary of the target card;
determining that the target card contained in the card image is absent in response to the presence of a keypoint of the at least one first keypoint whose minimum distance to the boundary of the target card is greater than the preset threshold.
6. The image processing method according to claim 5, characterized in that the method further comprises:
determining that the target card contained in the card image is complete in response to the minimum distances from the at least one first keypoint to the boundary of the target card being less than or equal to the preset threshold.
7. The image processing method according to any one of claims 1 to 6, further comprising, before the determining the integrity of the target card contained in the card image based on the predicted position information of the plurality of key points of the target card,:
performing correction processing on the card image to obtain the card image subjected to correction processing;
the determining whether to store the card image includes:
And determining whether to store the card image after the correction processing.
8. An image processing apparatus characterized by comprising: a prediction module, an integrity detection module, and a storage module, wherein:
the prediction module is used for detecting key points of the acquired card image to acquire predicted position information of a plurality of key points of a target card in the card image;
the integrity detection module is used for determining the integrity of the target card contained in the card image based on the predicted position information of a plurality of key points of the target card;
the storage module is configured to determine whether to store the card image based at least in part on an integrity of the target card included in the card image.
9. An electronic device, comprising a processor and a memory for storing a computer program configured to be executed by the processor for performing the method of any one of claims 1-6.
10. A computer-readable storage medium for storing a computer program, wherein the computer program causes a computer to perform the method of any one of claims 1-6.
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