An information processing method, device and storage medium

Abstract

The application discloses an information processing method, comprising: confirming at least one focus point based on a first target region in a first image; confirming at least one second image based on the at least one focus point; and confirming information in the at least one second image. The application also provides an information processing device and a storage medium. Based on the information processing method, device and storage medium, the accuracy of image information identification can be improved.

Description

Technical Field

[0001] This application relates to the field of image processing, and more particularly to an information processing method, apparatus, and storage medium. Background Technology

[0002] With the continuous expansion of application scenarios and underlying technologies of artificial intelligence, such as image recognition, information extraction, and computer system hardware upgrades, traditional work methods are rapidly transitioning towards artificial intelligence and information technology. We are currently in a stage where artificial intelligence and traditional work methods coexist. Properly handling the information integration and management between traditional and computer-based work methods will accelerate the development of information technology and effectively improve work efficiency.

[0003] In related technologies, information in images can be converted into digital information by combining image recognition technology and text recognition technology. However, the accuracy of the above methods is relatively low. Therefore, how to improve the accuracy of image information recognition is a technical problem that needs to be solved. Summary of the Invention

[0004] This application provides an information processing method, apparatus, and storage medium that can improve the accuracy of image information recognition.

[0005] The technical solution of this application embodiment is implemented as follows:

[0006] In a first aspect, this application provides an information processing method, the method comprising:

[0007] At least one focus point is identified based on the first target region in the first image;

[0008] At least one second image is confirmed based on the at least one focus point;

[0009] Confirm the information in at least one of the second images.

[0010] In the above scheme, identifying at least one focus point based on the first target region in the first image includes:

[0011] Confirm the first length and first width of the first target region;

[0012] A first value is determined based on the first step length and the first length; the first value represents the number of focus points in each row of the first target region;

[0013] A second value is determined based on the second step size and the first width; the second value represents the number of focus points in each column of the first target region;

[0014] Based on the first value and the second value, at least one focus point is identified.

[0015] In the above scheme, confirming at least one focus point based on the first value and the second value includes:

[0016] Based on the first value and the second value, the first target region is divided into at least two second target regions;

[0017] Based on the polar coordinate parameters of the at least two second target regions, determine the polar coordinate parameters of the focus point of each of the at least two second target regions.

[0018] In the above scheme, confirming the information in the at least one second image includes:

[0019] Confirm the border in any one of the at least one second image;

[0020] Identify the information within the border in any of the second images;

[0021] Store the information within the border in any of the identified second images.

[0022] In the above scheme, after confirming the information in the at least one second image, the method further includes:

[0023] Store at least one second image;

[0024] Establish a correspondence between the at least one second image and the information within the borders of the at least one second image;

[0025] Based on the correspondence and the information within the border in the second image, a second image corresponding to the information within the border in the second image can be determined.

[0026] The method in the above scheme further includes:

[0027] The first image is acquired based on the first focal length;

[0028] Determine whether the first target region can be obtained from the first image based on the pre-stored first border material;

[0029] If the first target region can be obtained from the first image based on the pre-stored first border material, then at least one focus point is confirmed based on the first target region in the first image;

[0030] Alternatively, if the first target region cannot be obtained from the first image based on the pre-stored first border material, then the first image is obtained based on the second focal length.

[0031] The method in the above scheme further includes:

[0032] Based on the sum of the first focal length and the third step length, obtain the third image;

[0033] A fourth image is obtained based on the difference between the first focal length and the third step length;

[0034] The first focal length is updated to the second focal length based on the sharpness of the third image and the fourth image.

[0035] In the above scheme, updating the first focal length to the second focal length based on the sharpness of the third image and the sharpness of the fourth image includes:

[0036] If the sharpness of the third image is greater than that of the fourth image, then the sum of the first focal length and the at least one third step length is determined as the second focal length.

[0037] Alternatively, if the sharpness of the third image is less than that of the fourth image, the difference between the first focal length and the at least one third step length is determined as the second focal length.

[0038] Secondly, this application also provides an information processing apparatus, the apparatus comprising:

[0039] A confirmation device is used to confirm at least one focus point based on a first target area in a first image; to confirm at least one second image based on the at least one focus point; and to confirm information in the at least one second image.

[0040] Thirdly, embodiments of this application provide a storage medium storing an executable program, which, when executed by a processor, implements the information processing method performed by the aforementioned device.

[0041] Fourthly, embodiments of this application provide an information processing apparatus, wherein the three-dimensional modeling device enables a processor to execute the above-described information processing method.

[0042] The information processing method, apparatus, and storage medium provided in this application embodiment identify at least one focus point based on a first target region in a first image; identify at least one second image based on the at least one focus point; and identify information in the at least one second image. This can improve the accuracy of image information recognition. Attached Figure Description

[0043] Figure 1 A schematic diagram of an optional flow chart for the information processing method provided in this application;

[0044] Figure 2 A schematic diagram of another optional process for the information identification method provided in the embodiments of this application;

[0045] Figure 3 This is a schematic diagram illustrating the display of a movable floating notification box on an electronic device screen according to an embodiment of this application.

[0046] Figure 4 An optional schematic diagram for dividing a first target region provided in an embodiment of this application;

[0047] Figure 5 Another optional schematic diagram for dividing the first target region provided in the embodiments of this application;

[0048] Figure 6 A schematic diagram of another optional flow of the information processing method provided in the embodiments of this application;

[0049] Figure 7 This is a schematic diagram of an optional structure of the information processing apparatus provided in an embodiment of this application;

[0050] Figure 8 This is a schematic diagram of another optional structure of the information processing apparatus provided in the embodiments of this application;

[0051] Figure 9 This is a schematic diagram of the hardware structure of the information processing device according to an embodiment of this application. Detailed Implementation

[0052] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the scope of the present application.

[0053] With the continuous expansion of application scenarios and underlying technologies of artificial intelligence, such as image recognition, information extraction, and computer system hardware upgrades, traditional work methods are rapidly transitioning towards artificial intelligence and information technology. We are currently in a stage where artificial intelligence and traditional work methods coexist. Properly handling the information integration and management between traditional and computer-based work methods will accelerate the development of information technology and effectively improve work efficiency.

[0054] Agile development is a prevalent information management and interaction method in the software development industry, and a key aspect of management involving direct interaction between traditional handwritten notes and computer information. In this scenario, teams primarily record tasks in two ways: through agile management software and by posting task notes on whiteboards. Each method has its own advantages and disadvantages. A drawback of posting task notes on whiteboards is that historical data cannot be archived and is easily lost, making it difficult for management teams to perform statistical analysis and prediction of team tasks using quantifiable data. Therefore, there is an urgent need for a system based on card-based handwriting recognition to convert the task note data from the whiteboard into agile management software for data analysis and prediction. However, posting task notes offers advantages such as a simple and efficient task interaction process and alignment with the work habits of a large proportion of employees.

[0055] In order to integrate the direct interaction, storage, and collaborative work between task notes and computer-based information software, a technology is needed to solve the problem of efficient and accurate interaction between task notes on the Kanban board and the information system.

[0056] The existing solution is to use image recognition technology as a foundation, combined with modules such as text recognition to extract the content of the task slips. In order to improve the recognition accuracy, a neural network algorithm is introduced for training and generating a model.

[0057] The main problem is that neural network-trained models typically recognize text line by line. If adjacent task slips exist, the same line from two slips can easily be identified as the result of the same task, leading to a significant discrepancy between the recognized task content and the actual result. In other words, it cannot accurately capture the information on the task slips.

[0058] Furthermore, when existing image acquisition technologies are applied in this scenario, the acquired photos are partially blurred due to camera focus bias, which in turn makes the recognition process highly dependent on the algorithm's performance, and key indicators such as the non-recognition rate and recognition error rate also far exceed the standards.

[0059] Existing methods for identifying task cards based on neural networks have the following drawbacks:

[0060] 1. After the recognition algorithm is modeled, the recognition scenarios will be limited. Since the object being recognized is an image acquired in real time, and the accuracy of image recognition will be affected by the different background, lighting, content, etc. of the image, the modeling will face the contradiction between the large size and large amount of computation required for adapting to multiple scenarios and the limited adaptability to scenarios.

[0061] 2. General text recognition can extract text content, but it cannot extract and store it based on the actual task. Extracting and recognizing content based on the task is the most basic requirement.

[0062] 3. Existing image acquisition technologies, as the foundation, are unlikely to provide complete image materials required for information extraction. This will lead to significant manual verification costs or higher investment costs in software and hardware computing power for the information entry of task cards.

[0063] Based on the problems existing in current image recognition methods, this application proposes an information processing method that can solve the technical problems and shortcomings that cannot be solved in existing technical solutions.

[0064] Figure 1 A schematic diagram of an alternative flow chart of the information processing method provided in this application is shown, and the steps will be explained accordingly.

[0065] Step S101: Identify at least one focus point based on the first target region in the first image.

[0066] In some embodiments, the information processing device (hereinafter referred to as the device) identifies at least one focus point based on a first target region in a first image. The first image includes a border and a first target region within the border. Optionally, the first target region includes at least two second target regions.

[0067] In specific implementation, the device confirms a first length and a first width of the first target area; determines a first value based on the first step length and the first length; the first value represents the number of focus points in each row of the first target area; determines a second value based on the second step length and the first width; the second value represents the number of focus points in each column of the first target area; and confirms at least one focus point based on the first value and the second value.

[0068] Specifically, after determining the first value and the second value, the device divides the first target region into at least two second target regions based on the first value and the second value; and determines the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the at least two second target regions.

[0069] The first step length and the second step length can be determined based on the size of the at least one second target region and the position of the at least one second target region within the first target region.

[0070] Step S102: Confirm at least one second image based on the at least one focus point.

[0071] In some embodiments, the device confirms at least one second image based on the at least one focus point.

[0072] In specific implementation, the device can acquire a third image based on the at least one focus point, and segment the third image into at least one second image based on the first step length, the second step length, the first value, and the second value.

[0073] Alternatively, in a specific implementation, the device can directly acquire the at least one second image based on the at least one focus point.

[0074] Step S103: Confirm the information in the at least one second image.

[0075] In some embodiments, the device confirms information in the at least one second image.

[0076] In specific implementation, the device can identify the border in any one of the at least one second image; and identify the information within the border in any one of the second images based on image recognition technology or text recognition technology. Optionally, after identifying the information within the border in any one of the second images, the device can also store the identified information within the border in any one of the second images.

[0077] In some optional embodiments, the device may further store the at least one second image; establish a correspondence between the at least one second image and the information within the borders of the at least one second image; and, based on the correspondence and the information within the borders of the second image, determine a second image corresponding to the information within the borders of the second image. Thus, a second image corresponding to the information within the borders of any given second image can be determined based on the information within the borders of any given second image. If the information within the borders of a second image is not accurately identified, a corresponding second image can be obtained based on the correspondence and the information within the borders of the second image to further confirm the information within the borders of the second image.

[0078] Thus, by using the information processing method provided in this application embodiment, at least one focus point is identified based on the first target area in the first image; at least one second image is identified based on the at least one focus point; the clarity of each acquired second image can be guaranteed, thereby improving the accuracy of identifying information in the at least one second image.

[0079] Figure 2 This illustration shows another optional flowchart of the information identification method provided in the embodiments of this application, which will be explained step by step.

[0080] Step S201: Acquire the first image based on the first focal length.

[0081] In some embodiments, the information recognition device acquires the first image based on a first focal length.

[0082] In specific implementation, the device can acquire the first image through steps S301 to S302.

[0083] Figure 3 A schematic diagram of an optional process for obtaining a first image provided in an embodiment of this application is shown, and the process will be explained step by step.

[0084] Step S301: Acquire the first image based on the first focal length.

[0085] In some embodiments, the apparatus determines a first image based on the first focal length.

[0086] In specific implementation, the device can determine the first focal length based on an automatic focal length search method; when the device can obtain any one of the pre-stored first border materials from the first image based on the first focal length, the first image is obtained based on the first focal length. The first border material includes at least one of the following: at least one border material material, at least one material representing the color of the border material, and at least one material representing the presentation form of the border material under different light spectra and illumination angles.

[0087] For example, taking a whiteboard and task stickers on the whiteboard as an example, the device acquires all or part of the image of the whiteboard's border based on a first focal length. If any border material in the pre-stored first border material can be found in the image, the first image is acquired based on the first focal length.

[0088] Alternatively, if no border material matching any of the pre-stored first border materials can be found in the image, then the first focal length is updated;

[0089] If a border element matching any of the pre-stored first border elements can be found in the image acquired based on the updated first focal length, then the first image is acquired based on the updated first focal length; if a border element matching any of the pre-stored first border elements cannot be found in the image acquired based on the updated first focal length, then the first image is acquired based on any focal length.

[0090] In specific implementation, updating the first focal length of the device may include: acquiring a third image based on the sum of the first focal length and the third step length; acquiring a fourth image based on the difference between the first focal length and the third step length; updating the first focal length to a second focal length based on the sharpness of the third image and the sharpness of the fourth image; wherein the updated first focal length is the second focal length.

[0091] Specifically, if the sharpness of the third image is greater than that of the fourth image, the sum of the first focal length and the at least one third step length is determined as the second focal length; or, if the sharpness of the third image is less than that of the fourth image, the difference between the first focal length and the at least one third step length is determined as the second focal length.

[0092] Step S301 is repeated based on the second focal length until a border material matching any of the pre-stored first border materials can be found in the image obtained based on the updated focal length (which may be the first focal length, the second focal length, or the updated second focal length). Then, the first image is obtained based on the second focal length.

[0093] Step S302: Determine whether at least one second target region can be obtained from the first image based on the pre-stored second border material.

[0094] In some embodiments, the device identifies at least one second border included in the first image based on pre-stored second border material, and obtains the at least one second target region based on the at least one second border.

[0095] Taking the whiteboard and the task stickers on the whiteboard as an example again, the second border material may include the border of the paper. If at least one second target area can be obtained from the first image based on the pre-stored second border material, the process of step S302 ends and step S202 is executed; if at least one second target area cannot be obtained from the first image based on the pre-stored second border material, the first focal length (or the second focal length) is updated.

[0096] Specifically, a fifth image is obtained based on the sum of the first focal length (or the second focal length) and the fourth step length; a sixth image is obtained based on the difference between the first focal length (or the second focal length) and the fourth step length; and the first focal length (or the second focal length) is updated based on the sharpness of the fifth image and the sharpness of the sixth image.

[0097] If the clarity of the fifth image is greater than that of the sixth image, a first set of focal lengths is generated using the sum of the first focal length (or the second focal length) and the at least one fourth step length; or, if the clarity of the fifth image is less than that of the sixth image, a first set of focal lengths is generated using the difference between the first focal length (or the second focal length) and the at least one fourth step length.

[0098] Wherein, the first focal length (or the second focal length) is represented by φ2, and the fourth step length is represented by d2. If the first focal length set is generated using the sum of the first focal length (or the second focal length) and the at least one fourth step length, then the first focal length set includes at least: φ2+d2, φ2+2*d2, ..., φ2+k*d2, ..., φ2+n*d2; if the first focal length set is generated using the difference between the first focal length (or the second focal length) and the at least one fourth step length, then the first focal length set includes at least: φ2-d2, φ2-2*d2, ..., φ2-k*d2, ..., φ2-n*d2. k and n are both positive integers, k < n. The selectable step length d2 can be any value from 5 cm to 20 cm.

[0099] Steps S301 to S302 are repeated for each focal length in the first focal length set until at least one second target region can be obtained from the first image based on the pre-stored second border material.

[0100] Step S202: Identify at least one focus point based on the first target region in the first image.

[0101] In some embodiments, after acquiring the first image, the device identifies a first target region in the first image and divides the first target region into at least one second target region.

[0102] Figure 4 This illustration shows an optional schematic diagram of dividing a first target region according to an embodiment of this application. Figure 5 This illustration shows another optional schematic diagram of the division of the first target region provided by an embodiment of this application.

[0103] In specific implementation, the device determines the first length and first width of the first target area based on the first target area; for example... Figure 4 As shown, the first length of the first target region is confirmed to be L, and the first width is M.

[0104] Specifically, the device determines a first value c based on a first step length l and a first length L; the first value c represents the number of focus points in each row of the first target region; a second value d is determined based on a second step length m and a first width M; the second value d represents the number of focus points in each column of the first target region; and at least one focus point is confirmed based on the first value c and the second value d. Optionally, the first step length l and the second step length m can be determined based on information within a second target region.

[0105] Optionally, the first value c and the second value d can be determined based on c*l≤L≤(c+1)*l and d*m≤M≤(d+1)*m.

[0106] In some embodiments, the device divides the first target region into at least two second target regions based on the first value and the second value; such as Figure 5 As shown, taking a whiteboard and task stickers on the whiteboard as an example, the first target area within the whiteboard border is divided into at least one second target area.

[0107] In some embodiments, the device determines the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the at least two second target regions.

[0108] In specific implementation, the device determines the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the edges and the polar coordinate parameters of the vertices of each of the at least two second target regions.

[0109] like Figure 4 As shown, the number of at least one focus point is c*d, and focus point M is determined. 11 To focus point M dc .

[0110] In some embodiments, the apparatus may further modify the shape of the first target region to a standard rectangle and perform step S202 based on the modified first target region.

[0111] Step S203: Confirm at least one second image based on the at least one focus point.

[0112] In some embodiments, the device confirms at least one second image based on the at least one focus point.

[0113] In specific implementation, the device can acquire a third image based on the at least one focus point, and segment the third image into at least one second image based on the first step length, the second step length, the first value, and the second value.

[0114] Alternatively, in a specific implementation, the device can directly acquire the at least one second image based on the at least one focus point.

[0115] Step S204: Confirm the information in the at least one second image.

[0116] In some embodiments, the device confirms information in the at least one second image.

[0117] In specific implementation, the device can identify the border in any one of the at least one second image; and identify the information within the border in any one of the second images based on image recognition technology or text recognition technology. Optionally, after identifying the information within the border in any one of the second images, the device can also store the identified information within the border in any one of the second images.

[0118] Step S205: Manage the information in the at least one second image.

[0119] In some embodiments, the device can further establish a correspondence between the at least one second image and the information within the borders of the at least one second image; based on the correspondence and the information within the borders of the second image, a second image corresponding to the information within the borders of the second image can be determined. Thus, a second image corresponding to the information within the borders of any second image can be determined based on the information within the borders of any second image. If the information within the borders of a second image is not accurately identified, a corresponding second image can be obtained based on the correspondence and the information within the borders of the second image to further confirm the information within the borders of the second image.

[0120] Thus, through the embodiments of this application, during the image acquisition process, the focus point of each second image can be determined based on the first image, thereby improving the quality of the acquired images. At the same time, it can also avoid the decline in image quality caused by individual differences in shooting, and improve the accuracy of information in the subsequently acquired images.

[0121] Figure 6 This illustration shows another alternative flowchart of the information processing method provided in the embodiments of this application, which will be described step by step.

[0122] Step S401: Obtain the first target area.

[0123] In some embodiments, the apparatus acquires a first target region of a first image based on a first focal length.

[0124] The first focal length can be determined based on an automatic focal length search method. Specifically, the device can adjust the first focal length based on a random step size until the device can obtain any one of the pre-stored first border materials from the first image and determine the focal length at this time as the first focal length.

[0125] The pre-stored first border material is used to store at least one border material object. The border material object can be the border material and color of the signboard, as well as the presentation of the border material under different light spectra and illumination angles.

[0126] In some embodiments, the device extracts at least one second target region from the first image that matches a preset target region template. The preset target region template may be the border of a strip of paper, the border of a piece of cardboard, or the border corresponding to each block of content in a handwritten newspaper, etc.

[0127] If the device can extract at least one second target region in the first image that is consistent with the preset target region template, then step S402 is executed; or, if the device cannot extract at least one second target region in the first image that is consistent with the preset target region template, the first focal length is updated.

[0128] In specific implementation, the device obtains two sets of primary focal lengths by adding a fourth step length d2 to the first focal length and subtracting a fourth step length d2 from the first focal length, respectively. The sharpness of the image objects obtained under the two sets of primary focal lengths is compared (for example, edge information can be extracted and the edge lengths in the image can be accumulated and compared). The sharper image object is defined as the positive direction. The focusing distance (focal length) is obtained by adding or subtracting n*d2 in the manner corresponding to the positive direction (first focal length plus fourth step length d2 or first focal length minus fourth step length d2), thus generating n sets of execution focal lengths for backup (first focal length set). Step S401 is repeated based on the n sets of backup execution focal lengths until at least one second target region can be obtained from the first image based on the pre-stored second border material.

[0129] In some alternative embodiments, the fourth step length d2 ranges from 5 cm to 20 cm.

[0130] Step S402: Identify at least one focus point based on the first target area.

[0131] In some embodiments, after acquiring the first image, the device identifies a first target region in the first image and divides the first target region into at least one second target region.

[0132] Figure 4 This illustration shows an optional schematic diagram of dividing a first target region according to an embodiment of this application. Figure 5 This illustration shows another optional schematic diagram of the division of the first target region provided by an embodiment of this application.

[0133] In specific implementation, the device determines the first length and first width of the first target area based on the first target area; for example... Figure 4 As shown, the first length of the first target region is confirmed to be L, and the first width is M.

[0134] Specifically, the device determines a first value c based on a first step length l and a first length L; the first value c represents the number of focus points in each row of the first target region; a second value d is determined based on a second step length m and a first width M; the second value d represents the number of focus points in each column of the first target region; and at least one focus point is confirmed based on the first value c and the second value d. Optionally, the first step length l and the second step length m can be determined based on information within the second target region. Optionally, the values ​​of l and m can both be less than 30 centimeters to obtain at least one clearer second image.

[0135] Optionally, the first value c and the second value d can be determined based on c*l≤L≤(c+1)*l and d*m≤M≤(d+1)*m.

[0136] In some embodiments, the device divides the first target region into at least two second target regions based on the first value and the second value; such as Figure 5 As shown, taking a whiteboard and task stickers on the whiteboard as an example, the first target area within the whiteboard border is divided into at least one second target area.

[0137] In some embodiments, the device determines the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the at least two second target regions.

[0138] In specific implementation, the device determines the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the edges and the polar coordinate parameters of the vertices of each of the at least two second target regions.

[0139] like Figure 4 As shown, the number of at least one focus point is c*d, and focus point M is determined. 11 To focus point M dc .

[0140] In some embodiments, the apparatus may further modify the shape of the first target region to a standard rectangle and perform step S402 based on the modified first target region.

[0141] Step S403: Confirm at least one second image based on the at least one focus point.

[0142] In some embodiments, the device confirms at least one second image based on the at least one focus point.

[0143] In specific implementation, the device can acquire a third image based on the at least one focus point, and segment the third image into at least one second image based on the first step length, the second step length, the first value, and the second value.

[0144] Alternatively, in a specific implementation, the device can directly acquire the at least one second image based on the at least one focus point.

[0145] In this way, a second image can be obtained that is fully in focus in the first target area.

[0146] Step S404: Confirm the information in the at least one second image.

[0147] In some embodiments, the device confirms information in the at least one second image.

[0148] In specific implementation, the device can identify the border in any one of the at least one second image; and identify the information within the border in any one of the second images based on image recognition technology or text recognition technology. Optionally, after identifying the information within the border in any one of the second images, the device can also store the identified information within the border in any one of the second images.

[0149] Step S405: Manage the information in the at least one second image.

[0150] In some embodiments, the device can further establish a correspondence between the at least one second image and the information within the borders of the at least one second image; based on the correspondence and the information within the borders of the second image, a second image corresponding to the information within the borders of the second image can be determined. Thus, a second image corresponding to the information within the borders of any second image can be determined based on the information within the borders of any second image. If the information within the borders of a second image is not accurately identified, a corresponding second image can be obtained based on the correspondence and the information within the borders of the second image to further confirm the information within the borders of the second image.

[0151] Optionally, resource links can be generated, through which users can directly jump from the information within the border of the image to the original image used to identify and generate the current content.

[0152] Thus, the novel method for capturing unformatted information, along with the shooting strategy generation algorithm within that method, provided in this application embodiment, solves the problems of poor or extremely unstable image quality, as well as individual technical differences caused by the photographer, in scenarios requiring precise acquisition of unformatted information. These differences are at the forefront of the system's information processing, representing the raw data from which the system processes and formats the unformatted information. This instability significantly complicates the formatting process. This algorithmic improvement addresses these issues, providing the system with stable, high-quality raw image data.

[0153] Figure 7 This is a schematic diagram of an optional structure of the information processing device provided in the embodiments of this application, and will be described according to each part.

[0154] In some embodiments, the information processing device 500 includes: a shooting unit 501.

[0155] The shooting unit 501 includes a software system and a hardware system that execute the above steps S101, S201, S301 to S302 and S401, and can be installed on a handheld smart terminal as an application.

[0156] The shooting unit 501 includes an image acquisition unit, a focus adjustment unit, a calculation unit, and a storage unit. The storage unit stores the computer program, business data, and calculation process data. The computer program includes the strategy calculation program required to execute steps S102, S202, and S402. The calculation unit can calculate the focus points M through this program. 11 To M dc The polar coordinate parameters relative to the current position of the image acquisition unit can be output to control the focus adjustment unit, thereby adjusting the focus position of the image acquisition unit.

[0157] Considering the consistency of the computation adjustment process requirements in such scenarios (basically all users have the same requirements), the preferred solution is automatic execution, that is, starting the program through a trigger and then automatically completing the entire process from steps S101 to S102, steps S201 to S203, and steps S401 to S403.

[0158] In some embodiments, the information processing device 500 further includes a focal length adjustment unit 502, used to update the first focal length in steps S202, S301 to S302 and S401.

[0159] In some embodiments, the information processing apparatus 500 further includes a region identification unit 503, used to implement the step of confirming at least one second image in steps S102, S203, S303, and S304 described above.

[0160] The region recognition unit 503, based on the acquisition of at least one second image, adds a note segmentation unit to cut out handwritten notes recording specific matters from the second image as note units. The segmentation algorithm uses the edge extraction of the note as the segmentation line. After the note unit is segmented, the system's text recognition system recognizes and stores the note content to form formatted content.

[0161] In some embodiments, the information processing device 500 further includes an identification unit 504. The identification unit 504 is used to identify text information and image information in the at least one second image, and to store the text information and image information in a formatted manner.

[0162] In some embodiments, the information processing device 500 further includes a task unit 505. The task unit is configured to convert the text information and image information into corresponding tasks, which are then incorporated into the system for viewing, editing, and marking.

[0163] In some embodiments, the information processing device 500 further includes a management unit 506. The management unit is used to ensure the accuracy of information viewing and to achieve system tolerance to unknown errors. After generating and storing formatted content, it generates resource links using part or all of the formatted content as objects, or using specific buttons near the formatted content as objects. These resource links allow direct access to the original image used to identify and generate the currently formatted content.

[0164] Figure 8 This is a schematic diagram of another optional structure of the information processing device provided in the embodiments of this application, which will be described according to each part.

[0165] In some embodiments, the information processing device 600 includes: a confirmation unit 601.

[0166] The confirmation unit 601 is used to confirm at least one focus point based on a first target area in a first image; to confirm at least one second image based on the at least one focus point; and to confirm information in the at least one second image.

[0167] In some embodiments, the confirmation unit 601 is specifically configured to: confirm a first length and a first width of the first target region; determine a first value based on the first step length and the first length; the first value represents the number of focus points in each row of the first target region; determine a second value based on the second step length and the first width; the second value represents the number of focus points in each column of the first target region; and confirm at least one focus point based on the first value and the second value.

[0168] In some embodiments, the confirmation unit 601 is specifically configured to: divide the first target region into at least two second target regions based on the first value and the second value; and determine the polar coordinate parameters of the focus point of each of the at least two second target regions based on the polar coordinate parameters of the at least two second target regions.

[0169] In some embodiments, the confirmation unit 601 is specifically used to: confirm the border in any one of the at least one second image; identify the information within the border in the any one second image; and store the identified information within the border in the any one second image.

[0170] In some embodiments, the information processing device 600 may further include a storage unit 602.

[0171] The storage unit 602 is used to store the at least one second image; and to establish a correspondence between the at least one second image and the information within the border of the at least one second image;

[0172] Based on the correspondence and the information within the border in the second image, a second image corresponding to the information within the border in the second image can be determined.

[0173] In some embodiments, the information processing device 600 may further include an acquisition unit 603.

[0174] The acquisition unit 603 is configured to acquire the first image based on a first focal length; determine whether the first target region can be acquired from the first image based on a pre-stored first border material; if the first target region can be acquired from the first image based on the pre-stored first border material, then at least one focus point is confirmed based on the first target region in the first image; or, if the first target region cannot be acquired from the first image based on the pre-stored first border material, then the first image is acquired based on a second focal length.

[0175] In some embodiments, the information processing apparatus 600 may further include an update unit 604.

[0176] The updating unit 604 is used to obtain a third image based on the sum of the first focal length and the third step length; obtain a fourth image based on the difference between the first focal length and the third step length; and update the first focal length based on the sharpness of the third image and the sharpness of the fourth image; wherein the updated first focal length is the second focal length.

[0177] The updating unit 604 is specifically configured to update the first focal length using the sum of the first focal length and the at least one third step length if the clarity of the third image is greater than that of the fourth image; or, if the clarity of the third image is less than that of the fourth image, update the first focal length using the difference between the first focal length and the at least one third step length.

[0178] Figure 9 This is a schematic diagram of the hardware structure of an information processing device according to an embodiment of this application. The information processing device 700 includes at least one processor 701, a memory 702, and at least one network interface 704. The various components in the information processing device 700 are coupled together through a bus system 705. It is understood that the bus system 705 is used to implement communication between these components. In addition to a data bus, the bus system 705 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 9 The general labeled all buses as Bus System 705.

[0179] It is understood that memory 702 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM). The memory 702 described in this application embodiment is intended to include, but is not limited to, these and any other suitable types of memory.

[0180] The memory 702 in this embodiment is used to store various types of data to support the operation of the information processing device 700. Examples of such data include any computer program, such as application program 722, for operation on the information processing device 700. A program implementing the method of this embodiment may be included in application program 722.

[0181] The methods disclosed in the embodiments of this application can be applied to processor 701, or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in software form. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 701 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 702. Processor 701 reads the information in memory 702 and combines it with its hardware to complete the steps of the aforementioned method.

[0182] In an exemplary embodiment, the information processing apparatus 700 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, MPUs, or other electronic components to perform the aforementioned method.

[0183] This application also provides a storage medium for storing computer programs.

[0184] Optionally, the storage medium can be applied to the first client in the embodiments of this application, and the computer program causes the computer to execute the corresponding processes in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0185] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0186] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0187] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0188] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An information processing method, characterized in that, The method includes: At least one focus point is identified based on a first target area in a first image; wherein, the first image includes a border and a first target area within the border, the first target area includes at least two second target areas, and the second target areas include areas containing one or more of a strip of paper, cardboard, and handwritten newspaper; At least one second image is confirmed based on the at least one focus point; Confirm the information in at least one of the second images.

2. The method according to claim 1, characterized in that, The process of identifying at least one focus point based on a first target region in the first image includes: Confirm the first length and first width of the first target region; A first value is determined based on the first step length and the first length; the first value represents the number of focus points in each row of the first target region; A second value is determined based on the second step size and the first width; the second value represents the number of focus points in each column of the first target region; Based on the first value and the second value, at least one focus point is identified.

3. The method according to claim 2, characterized in that, The confirmation of at least one focus point based on the first value and the second value includes: Based on the first value and the second value, the first target region is divided into at least two second target regions; Based on the polar coordinate parameters of the at least two second target regions, determine the polar coordinate parameters of the focus point of each of the at least two second target regions.

4. The method according to claim 1, characterized in that, The confirmation of information in the at least one second image includes: Confirm the border in any one of the at least one second image; Identify the information within the border in any of the second images; Store the information within the border in any of the identified second images.

5. The method according to any one of claims 1 to 4, characterized in that, After confirming the information in the at least one second image, the method further includes: Store at least one second image; Establish a correspondence between the at least one second image and the information within the borders of the at least one second image; Based on the correspondence and the information within the border in the second image, a second image corresponding to the information within the border in the second image can be determined.

6. The method according to claim 1, characterized in that, The method further includes: The first image is acquired based on the first focal length; Determine whether the first target region can be obtained from the first image based on the pre-stored first border material; If the first target region can be obtained from the first image based on the pre-stored first border material, then at least one focus point is confirmed based on the first target region in the first image; Alternatively, if the first target region cannot be obtained from the first image based on the pre-stored first border material, then the first image is obtained based on the second focal length.

7. The method according to claim 6, characterized in that, The method further includes: Based on the sum of the first focal length and the third step length, obtain the third image; A fourth image is obtained based on the difference between the first focal length and the third step length; The first focal length is updated to the second focal length based on the sharpness of the third image and the fourth image.

8. The method according to claim 7, characterized in that, The step of updating the first focal length to the second focal length based on the sharpness of the third image and the sharpness of the fourth image includes: If the sharpness of the third image is greater than that of the fourth image, then the sum of the first focal length and the at least one third step length is determined as the second focal length. Alternatively, if the sharpness of the third image is less than that of the fourth image, the difference between the first focal length and the at least one third step length is determined as the second focal length.

9. An information processing device, characterized in that, The device includes: A confirmation device is configured to confirm at least one focus point based on a first target area in a first image; confirm at least one second image based on the at least one focus point; and confirm information in the at least one second image; wherein the first image includes a border and a first target area within the border, the first target area includes at least two second target areas, and the second target areas include areas containing one or more of a strip of paper, cardboard, and handwritten newspaper.

10. A storage medium storing an executable program, characterized in that, When the executable program is executed by the processor, it implements the information processing method according to any one of claims 1 to 8.

11. An information processing apparatus, comprising a memory, a processor, and an executable program stored in the memory and executable by the processor, characterized in that, When the processor runs the executable program, it performs the steps of the information processing method as described in any one of claims 1 to 8.

Images