Image integrity determination method, device, electronic device, and medium

Abstract

The present invention relates to a method, device, electronic device, and medium for determining image integrity, comprising: receiving a corrected image, the corrected image including an image of a correction card, each of the four corners of the correction card being provided with a specific marker; preprocessing the corrected image to obtain a test image; identifying a specific marker area contained in the test image, the specific marker area being the imaging area of ​​the specific marker in the test image; dividing the four corners of the test image into four corner areas of preset sizes, and determining whether all four corner areas contain the specific marker area; if all four corner areas contain the specific marker area, and the image parameters of the specific marker areas in the four corner areas meet preset image parameter requirements, determining that the corrected image is complete. This solution achieves accurate judgment of image integrity by tracking changes in the specific markers at the corners of the correction card. It is not easily disturbed in judging the integrity of the fingerprint image, and the judgment result is stable and reliable.

Description

Technical Field

[0001] The present invention relates to the field of intelligent image recognition, and in particular to an image integrity determination method, device, electronic equipment and medium. Background Art

[0002] In existing fingerprint image intelligent recognition technology, it is not easy to determine whether the collected image to be tested is complete. If the collected image is incomplete, it will affect the accuracy of fingerprint recognition.

[0003] Specifically, due to optical path issues in fingerprint scanners, the collected results are often accompanied by severe optical distortion. This means that the collected results are easily disturbed, leaving traces behind, resulting in insufficient accuracy. Therefore, the industry urgently needs a technical solution that can achieve an effect that is not easily disturbed when determining the integrity of fingerprint images, that is, a stable and reliable result. Summary of the Invention

[0004] The technical problem to be solved by the present invention is: how to design an image integrity judgment method that is not easily disturbed in judging the integrity of a fingerprint image and the judgment result is stable and reliable.

[0005] To solve the above problems, embodiments of the present invention propose a method, device, electronic device, and medium for determining image integrity. By tracking changes in specific markers at the corners of a correction card and using preset image parameter requirements as a measurement standard, accurate judgment of image integrity is achieved. The key points of judgment throughout the entire process are focused on the specific markers at the corners, avoiding the central position that is easily disturbed, and will not be affected or interfered with by factors such as the optical path, humidity, and cleanliness. In other words, the method is not easily disturbed in determining the integrity of the fingerprint image, and the judgment results are stable and reliable.

[0006] In a first aspect, the present invention proposes a method for determining image integrity, the method comprising: receiving a corrected image, the corrected image comprising an image of a correction card, each of the four corners of the correction card being provided with a specific mark; preprocessing the corrected image to obtain an image to be tested; identifying a specific mark area contained in the image to be tested, the specific mark area being an imaging area of ​​the specific mark in the image to be tested; dividing the four corners of the image to be tested into four corner areas of preset sizes, and determining whether all four corner areas contain the specific mark area; if all four corner areas contain the specific mark area, determining whether image parameters of the specific mark areas of the four corner areas meet preset image parameter requirements; if the image parameters of the specific mark areas of the four corner areas all meet the preset image parameter requirements, determining that the corrected image is complete.

[0007] A further technical solution is that the corrected image is preprocessed to obtain the image to be tested, including: adding a border around the corrected image to obtain a border image, the color of the border being the same as the background color of the corrected image; binarizing the border image to obtain a binarized image; corroding the binarized image to obtain a corroded image; and dilating the corroded image to obtain the image to be tested.

[0008] A further technical solution is that the identifying the specific identification area contained in the image to be tested includes: identifying the specific identification area contained in the image to be tested by using a preset target detection algorithm.

[0009] Its further technical solution is that the judgment of whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements includes: calculating the first aspect ratio of the four specific identification areas; calculating the second aspect ratio of the four specific identifications; respectively calculating four deviation values ​​between the first aspect ratio of the four specific identification areas and the second aspect ratio of the four specific identifications, the deviation value being the absolute value of the difference between the first aspect ratio of the specific identification area and the second aspect ratio of the specific identification; judging whether the four deviation values ​​are all smaller than a preset deviation value threshold; if the four deviation values ​​are not all smaller than the preset deviation value threshold, judging that the image parameters do not meet the preset image parameter requirements.

[0010] Its further technical solution is that the determination of whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements also includes: if the four deviation values ​​are all smaller than the preset deviation value threshold, determining whether the pixels of the four specific identification areas are all greater than the preset pixel threshold; if the pixels of the four specific identification areas are all greater than the preset pixel threshold, determining that the image parameters of the specific identification areas of the four corner areas all meet the preset image parameter requirements.

[0011] A further technical solution is that the calculation of the first aspect ratio of the four specific identification areas includes: obtaining a connected domain of the specific identification areas; calculating a minimum circumscribed rectangle matching the connected domain; and calculating the aspect ratio of the minimum circumscribed rectangle to obtain a first aspect ratio.

[0012] A further technical solution is that if the four corner areas do not all contain the specific identification area, the corrected image is determined to be incomplete; if the image parameters of the specific identification areas of the four corner areas do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete.

[0013] In a second aspect, the present invention provides an image integrity determination device, which includes a unit for executing the method described in the first aspect.

[0014] In a third aspect, the present invention provides an electronic device comprising: a memory for storing a computer program; and a processor for implementing the steps of the method described in the first aspect when executing the program stored in the memory.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, it can implement the method described in the first aspect.

[0016] Existing intelligent fingerprint image recognition technologies struggle to determine the integrity of captured images. Incomplete images can negatively impact fingerprint recognition accuracy. Specifically, due to optical path issues within the fingerprint scanner, the captured images often exhibit significant optical distortion, leaving traces of artifacts and resulting in inaccurate results. Currently, there are no effective technical solutions to mitigate the negative effects of these interference-induced inaccuracies.

[0017] The beneficial effect of this solution is that by tracking the changes in specific marks at the corners of the correction card and using the preset image parameter requirements as the measurement standard, an accurate judgment of the image integrity can be achieved. The key points of judgment in the entire process are focused on the specific marks at the corners, avoiding the central position that is easily disturbed, and will not be affected or interfered by factors such as light path, humidity, cleanliness, etc., that is, it is not easy to be disturbed in judging the integrity of the fingerprint image, and the judgment results are stable and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 A flowchart of a method for determining image integrity provided by an embodiment of the present invention.

[0021] Figure 2 Another flowchart of a method for determining image integrity provided by an embodiment of the present invention is shown.

[0022] Figure 3 A partial schematic diagram of an image integrity determination method provided by an embodiment of the present invention.

[0023] Figure 4 Another partial schematic diagram of an image integrity determination method provided by an embodiment of the present invention.

[0024] Figure 5 A schematic diagram of a correction card provided in an embodiment of the present invention.

[0025] Figure 6 A schematic diagram of a frame image provided by an embodiment of the present invention.

[0026] Figure 7 This is a block diagram of an image integrity determination device provided by an embodiment of the present invention.

[0027] Figure 8 A block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] It will be understood that when used in this specification and the appended claims, the terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or other features, integers, steps, operations, elements, components and / or collections thereof.

[0030] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0031] It should be further understood that the term "and / or" used in the present description and the appended claims refers to one or any combination and all possible combinations of the associated listed items, and includes these combinations.

[0032] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0033] Example 1

[0034] See also Figure 1 and Figure 5 , Figure 1 This is a flow chart of a method for determining image integrity provided by an embodiment of the present invention. The present invention provides a method for determining image integrity, which can be used in terminal devices such as fingerprint sensors. The method includes:

[0035] S101 : Receive a correction image, where the correction image includes an image of a correction card, and each of the four corners of the correction card is provided with a specific mark.

[0036] In the above steps, the corrected image may include an image of the main body and an image of the correction card; the image of the main body is the image to be measured in the image detection technology; the image of the main body may specifically be a fingerprint image; the correction card is pre-set in a terminal device such as a fingerprint meter.

[0037] See Figure 5 The calibration card includes a specific mark 10 at each of its four corners. The calibration card also includes a square with a grid pattern. Four specific marks 10 are located next to the four corners of the square. In one embodiment, the specific marks 10 are square in shape and black in color. The four specific marks 10 are symmetrical about the geometric center of the square.

[0038] S102: Preprocess the corrected image to obtain an image to be tested.

[0039] Among them, the step of preprocessing the corrected image may include binarization processing, corrosion processing, and expansion processing to obtain a more reasonable image to be tested, thereby improving the accuracy of subsequent steps; its technical effect is that unnecessary image features can be suppressed through preprocessing, or certain image features that are important for subsequent processing can be enhanced.

[0040] S103 : Identify a specific identification area included in the image to be tested, where the specific identification area is an imaging area of ​​the specific identification in the image to be tested.

[0041] The imaging area of ​​the specific marker in the image to be measured, that is, the specific marker is the body, and the specific marker area is the imaging of the specific marker; the specific marker area belongs to the image to be measured, which is equivalent to the specific marker belonging to the corrected image.

[0042] If the specific mark is a square, the specific mark area is also a square, or a figure close to a square, the difference or deviation between the specific mark and the specific mark area may be very small and not easily detected by the naked eye, and needs to be identified and verified through a detection algorithm.

[0043] S104 , dividing the four corners of the image to be measured into four corner areas of preset sizes, and determining whether all of the four corner areas contain the specific identification area.

[0044] Among them, the size of the corner area can be preset according to actual conditions, and the size of the corner area is larger than the size of the specific identification area; since the positions of the four corner areas are separated, the standard for judging whether the four corner areas all contain the specific identification area is that there is no corner area that does not contain the specific identification area, that is, the specific identification area corresponds to the corner area one by one; its technical effect is that whether the image of the main body is complete can be judged by detecting whether the four corners are complete.

[0045] In one embodiment, the image to be tested may be divided into a standard nine-square grid, where the four corners of the nine-square grid are four corner areas of preset sizes. This division scheme has reasonable sizes of the corner areas, which is conducive to accurately determining the position of the specific identification area.

[0046] S105 : If the four corner areas all include the specific identification area, determine whether the image parameters of the specific identification areas of the four corner areas meet preset image parameter requirements.

[0047] The preset image parameter requirements may be a type of image parameter that is prone to deviation; the technical effect is that the image parameters of the four specific identified areas can be determined instead of the image parameters of the entire image to be tested, thereby achieving a more accurate determination result with fewer resources. In step S105, if the four corner areas do not all contain the specific identified areas, the corrected image is determined to be incomplete. In one embodiment, if three of the corner areas contain the specific identified areas, but one corner area does not, the corrected image is determined to be incomplete.

[0048] S106: If the image parameters of the specific marked areas in the four corner areas all meet the preset image parameter requirements, it is determined that the corrected image is complete.

[0049] The specific identification areas in the four corner regions meet the positional requirements, thus avoiding image incompleteness caused by excessive positional deviation; and the specific identification areas in the four corner regions meet the image parameter requirements, thus avoiding image incompleteness caused by excessive parameter deviation. In step S106, if the image parameters of the specific identification areas in the four corner regions do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete. In one embodiment, if all four corner regions contain the specific identification areas, but the image parameters of the specific identification areas in the four corner regions do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete.

[0050] The beneficial effect of the above scheme is that by tracking the changes of specific marks in the corners of the correction card and using the preset image parameter requirements as the measurement standard, the accurate judgment of the image integrity can be achieved. The key points of judgment in the whole process are focused on the specific marks in the corners, avoiding the central position that is easily disturbed, and will not be affected or interfered by factors such as light path, humidity, cleanliness, etc., that is, it is not easy to be disturbed in judging the integrity of the fingerprint image, and the judgment results are stable and reliable.

[0051] Example 2

[0052] See also Figure 2 、 Figure 5 、 Figure 6 , Figure 2 A schematic flow chart of another method for determining image integrity provided by an embodiment of the present invention.

[0053] S201 : Receive a correction image, where the correction image includes an image of a correction card, and each of the four corners of the correction card is provided with a specific mark.

[0054] In the above steps, the corrected image may include an image of the main body and an image of the correction card; the image of the main body is the image to be measured in the image detection technology; the image of the main body may specifically be a fingerprint image; the correction card is pre-set in a terminal device such as a fingerprint meter.

[0055] See Figure 5 The calibration card includes a specific mark 10 at each of its four corners. The calibration card also includes a square with a grid pattern. Four specific marks 10 are located next to the four corners of the square. In one embodiment, the specific marks 10 are square in shape and black in color. The four specific marks 10 are symmetrical about the geometric center of the square.

[0056] S202 : Adding a frame around the corrected image to obtain a frame image, wherein the color of the frame is the same as the background color of the corrected image.

[0057] In the above steps, please refer to Figure 5-Figure 6 The corrected image can include an image of the main body and an image of the correction card; the frame 20 can be a rectangular frame. The frame 20 is added around the corrected image, and the color of the frame 20 is the same as the background color of the corrected image. After adding the frame 20, the overall area of ​​the image increases, which is equivalent to the specific mark 10 moving from the edge of the image to the center. The technical effect is that because the color of the frame 20 is the same as the background color of the corrected image, it is not easily confused with the color of the specific mark 10. Adding the frame 20 can prevent the specific mark 10 from appearing at the edge of the corrected image, causing errors in the binarization process in the next step.

[0058] S203: Binarize the frame image to obtain a binary image.

[0059] The binarization process performed on the frame image can make the entire image appear in obvious black and white, thereby highlighting the outline of the frame image.

[0060] S204: performing corrosion processing on the binary image to obtain a corroded image.

[0061] The binary image is corroded by using a corrosion algorithm, scanning each pixel of the binary image with a convolution kernel, and performing an "AND" operation with the convolution kernel and the binary image covered by the convolution kernel, thereby reducing the binary image and converting it into a corroded image.

[0062] S205 , performing dilation processing on the eroded image to obtain an image to be tested.

[0063] The eroded image is then dilated using a dilation algorithm. This involves scanning each pixel of the eroded image with a convolution kernel and performing an AND operation with the kernel and the overlaid eroded image, ultimately expanding the eroded image to form the image to be tested. The erosion-then-dilation process after binarization helps remove small interference points along the image edge.

[0064] S206: Identify a specific identification area included in the image to be detected by using a preset target detection algorithm.

[0065] Among them, the specific identification area is the imaging area of ​​the specific identification in the image to be tested; the target detection algorithm is preset, and can locate and classify the targets in the image, and finally obtain the categories of multiple targets in the image and the positions in the image; the imaging area of ​​the specific identification in the image to be tested, that is, the specific identification is the body, and the specific identification area is the imaging of the specific identification; the specific identification area belongs to the image to be tested, which is equivalent to the specific identification belonging to the corrected image.

[0066] S207 , dividing the four corners of the image to be measured into four corner areas of preset sizes, and determining whether all of the four corner areas contain the specific identification area.

[0067] Among them, the size of the corner area can be preset according to actual conditions, and the size of the corner area is larger than the size of the specific identification area; since the positions of the four corner areas are separated, the standard for judging whether the four corner areas all contain the specific identification area is that there is no corner area that does not contain the specific identification area, that is, the specific identification area corresponds to the corner area one by one; its technical effect is that whether the image of the main body is complete can be judged by detecting whether the four corners are complete.

[0068] In one embodiment, the image to be tested may be divided into a standard nine-square grid, where the four corners of the nine-square grid are four corner areas of preset sizes. This division scheme has reasonable sizes of the corner areas, which is conducive to accurately determining the position of the specific identification area.

[0069] S208: If the four corner areas all include the specific identification area, determine whether the image parameters of the specific identification areas of the four corner areas meet preset image parameter requirements.

[0070] In one embodiment, the step S208 of determining whether the image parameters of the specific identification areas of the four corner areas meet preset image parameter requirements includes:

[0071] S301: Calculate a first aspect ratio of the four specific identification areas.

[0072] The first aspect ratio is calculated by first obtaining a connected domain of the specific identification area; then calculating a minimum bounding rectangle matching the connected domain; and finally calculating the aspect ratio of the minimum bounding rectangle to obtain the first aspect ratio.

[0073] S302: Calculate the second aspect ratio of the four specific marks.

[0074] The second aspect ratio is derived from the specific mark, which is provided on the calibration card. The second aspect ratio of the specific mark can be obtained by dividing the length of the specific mark by the width of the specific mark.

[0075] S303 , respectively calculating four deviation values ​​between the first aspect ratios of the four specific mark areas and the second aspect ratios of the four specific marks, where the deviation value is the absolute value of the difference between the first aspect ratio of the specific mark area and the second aspect ratio of the specific mark.

[0076] The first aspect ratios of the four specific identification regions can be 1.05, 1.15, 1.08, and 1.12, and the second aspect ratios of the four specific identification regions can be 1, 1, 1, and 1. Calculated deviations are 0.05, 0.15, 0.08, and 0.12, meaning that the absolute values ​​of the four deviations are all greater than zero. The first aspect ratio is derived from the specific identification region imaged by the specific identification in the image to be measured. Therefore, the value of the first aspect ratio is unpredictable by the user, while the value of the second aspect ratio is predictable by the user. A larger deviation indicates a greater deviation of the first aspect ratio from the second aspect ratio, meaning a greater degree of change in the specific identification region relative to the image to be measured.

[0077] S304: Determine whether the four deviation values ​​are all smaller than a preset deviation value threshold.

[0078] Among them, if the four deviation values ​​obtained through calculation are 0.05, 0.15, 0.08, and 0.12, and the preset deviation value threshold is 0.2, then the four deviation values ​​are all smaller than the preset deviation value threshold.

[0079] S305: If the four deviation values ​​are not all smaller than the preset deviation value threshold, it is determined that the image parameter does not meet the preset image parameter requirement.

[0080] In one embodiment, the preset deviation value threshold is 0.3, that is, the allowable deviation value is relatively large, which is suitable for scenarios with low accuracy requirements; in another embodiment, the preset deviation value threshold is 0.05, that is, the allowable deviation value is relatively small, which is suitable for scenarios with high accuracy requirements.

[0081] The technical effect of the above steps S301-S305 is to achieve accurate judgment of image integrity by tracking the changes of specific marks at the corners of the correction card and using the deviation value of the preset aspect ratio as a measurement standard. The influence or interference of the deviation value is more direct and representative than other parameters. Relying on the deviation value to judge image integrity takes into account both accuracy and resource cost.

[0082] In another embodiment, the step S208 of determining whether the image parameters of the specific identification areas of the four corner areas meet preset image parameter requirements includes:

[0083] S401: Calculate a first aspect ratio of the four specific identification areas.

[0084] The first aspect ratio is calculated by first obtaining a connected domain of the specific identification area; then calculating a minimum bounding rectangle matching the connected domain; and finally calculating the aspect ratio of the minimum bounding rectangle to obtain the first aspect ratio.

[0085] S402: Calculate the second aspect ratio of the four specific marks.

[0086] The second aspect ratio is derived from the specific mark, which is provided on the calibration card. The second aspect ratio of the specific mark can be obtained by dividing the length of the specific mark by the width of the specific mark.

[0087] S403 , respectively calculating four deviation values ​​between the first aspect ratios of the four specific mark areas and the second aspect ratios of the four specific marks, wherein the deviation value is the absolute value of the difference between the first aspect ratio of the specific mark area and the second aspect ratio of the specific mark.

[0088] The first aspect ratios of the four specific identification regions can be 1.05, 1.15, 1.08, and 1.12, and the second aspect ratios of the four specific identification regions can be 1, 1, 1, and 1. Calculated deviations are 0.05, 0.15, 0.08, and 0.12, meaning that the absolute values ​​of the four deviations are all greater than zero. The first aspect ratio is derived from the specific identification region imaged by the specific identification in the image to be measured. Therefore, the value of the first aspect ratio is unpredictable by the user, while the value of the second aspect ratio is predictable by the user. A larger deviation indicates a greater deviation of the first aspect ratio from the second aspect ratio, meaning a greater degree of change in the specific identification region relative to the image to be measured.

[0089] S404: Determine whether the four deviation values ​​are all smaller than a preset deviation value threshold.

[0090] Among them, if the four deviation values ​​obtained through calculation are 0.05, 0.15, 0.08, and 0.12, and the preset deviation value threshold is 0.2, then the four deviation values ​​are all smaller than the preset deviation value threshold.

[0091] S405: If the four deviation values ​​are all smaller than the preset deviation value threshold, determine whether the pixels of the four specific identification areas are all larger than the preset pixel threshold.

[0092] Among them, the pixels in the specific identification area belong to a type of image parameters that are prone to deviations; its technical effect is that by judging whether the pixels in the four specific identification areas belong to the preset pixel threshold, it can replace the judgment of the pixels of the entire image to be tested, thereby achieving more accurate judgment results with smaller resources.

[0093] S406 : If the pixels of the four specific identification areas are all greater than the preset pixel threshold, it is determined that the image parameters of the specific identification areas of the four corner areas all meet the preset image parameter requirements.

[0094] The technical effect of the above steps S401-S406 is that by tracking the changes of the specific marks at the corners of the correction card, the aspect ratio deviation value and pixel value, which are the two factors that have the greatest impact on accuracy, are used as measurement standards. In a technical scenario with sufficient resource costs, a more accurate judgment result can be obtained.

[0095] S209: If the image parameters of the specific marked areas in the four corner areas all meet the preset image parameter requirements, it is determined that the corrected image is complete.

[0096] If the image parameters of the specific identified areas in the four corner regions do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete. In one embodiment, if the four corner regions all contain the specific identified areas, but the image parameters of the specific identified areas in the four corner regions do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete.

[0097] The technical effect of the above embodiment is that by tracking the changes of specific marks at the corners of the correction card and using preset image parameter requirements as a measurement standard, an accurate judgment of the image integrity is achieved. The key points of judgment in the entire process are focused on the specific marks at the corners, avoiding the central position that is easily interfered with, and will not be affected or interfered by factors such as light path, humidity, and cleanliness. In addition, the preprocessing of the corrected image includes the steps of first corroding and then dilating after binarization, which is conducive to removing small interference points on the edge of the image, further improving the accuracy from the source of the corrected image and the correction card.

[0098] Example 3

[0099] See also Figure 7 , Figure 7 This is a block diagram of an image integrity determination device according to another embodiment of the present invention. Corresponding to the above image integrity determination method, the present invention further provides an image integrity determination device 70. The image integrity determination device 70 includes a unit for executing the above image integrity determination method. The device can be configured in a terminal device and specifically includes:

[0100] The image receiving unit 71 is used to receive a correction image, wherein the correction image includes an image of a correction card, and each of the four corners of the correction card is provided with a specific mark.

[0101] The image preprocessing unit 72 is used to preprocess the corrected image to obtain an image to be measured.

[0102] The image recognition unit 73 is configured to recognize a specific identification area included in the image to be tested, where the specific identification area is an imaging area of ​​the specific identification in the image to be tested.

[0103] The first judging unit 74 is configured to divide the four corners of the image to be measured into four corner areas of preset sizes, and judge whether all of the four corner areas contain the specific identification area.

[0104] The second judging unit 75 is configured to judge whether the image parameters of the specific marking areas of the four corner areas meet preset image parameter requirements if all four corner areas include the specific marking area.

[0105] The integrity determination unit 76 is configured to determine that the corrected image is complete if the image parameters of the specific marked areas in the four corner areas all meet preset image parameter requirements.

[0106] In one embodiment, the preprocessing of the corrected image to obtain the image to be tested includes: adding a border around the corrected image to obtain a border image, wherein the color of the border is the same as the background color of the corrected image; binarizing the border image to obtain a binarized image; corroding the binarized image to obtain a corroded image; and dilating the corroded image to obtain the image to be tested.

[0107] In another embodiment, the identifying the specific identification area included in the image to be tested includes: identifying the specific identification area included in the image to be tested using a preset target detection algorithm.

[0108] In another embodiment, the determination of whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements includes: calculating the first aspect ratio of the four specific identification areas; calculating the second aspect ratio of the four specific identifications; respectively calculating four deviation values ​​between the first aspect ratio of the four specific identification areas and the second aspect ratio of the four specific identifications, the deviation value being the absolute value of the difference between the first aspect ratio of the specific identification area and the second aspect ratio of the specific identification; determining whether the four deviation values ​​are all smaller than a preset deviation value threshold; if the four deviation values ​​are not all smaller than the preset deviation value threshold, determining that the image parameters do not meet the preset image parameter requirements.

[0109] In another embodiment, the determination of whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements further includes: if the four deviation values ​​are all smaller than the preset deviation value threshold, determining whether the pixels of the four specific identification areas are all greater than the preset pixel threshold; if the pixels of the four specific identification areas are all greater than the preset pixel threshold, determining that the image parameters of the specific identification areas of the four corner areas all meet the preset image parameter requirements.

[0110] In another embodiment, calculating the first aspect ratio of the four specific identification areas includes: obtaining a connected domain of the specific identification areas; calculating a minimum circumscribed rectangle matching the connected domain; and calculating the aspect ratio of the minimum circumscribed rectangle to obtain a first aspect ratio.

[0111] In another embodiment, if the four corner areas do not all contain the specific identification area, the corrected image is determined to be incomplete; if the image parameters of the specific identification areas of the four corner areas do not all meet the preset image parameter requirements, the corrected image is determined to be incomplete.

[0112] The technical effect is to propose an image integrity judgment device, which achieves accurate judgment of image integrity by tracking the changes of specific marks at the corners of the correction card and using preset image parameter requirements as a measurement standard. The key points of judgment in the entire process are focused on the specific marks at the corners, avoiding the central position that is easily disturbed, and will not be affected or interfered by factors such as light path, humidity, and cleanliness. That is, it is not easily disturbed in judging the integrity of the fingerprint image, and the judgment results are stable and reliable.

[0113] Example 4

[0114] See also Figure 8 , Figure 8 This is a block diagram of an electronic device provided by the present invention. The electronic device can be a terminal or a server. The terminal can be a smartphone, tablet computer, laptop computer, desktop computer, personal digital assistant, wearable device, or other electronic device with communication capabilities. The server can be a standalone server or a server cluster.

[0115] It includes a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other via the communication bus 114;

[0116] Memory 113, for storing computer programs;

[0117] In one embodiment of the present invention, the processor 111 is configured to implement the method provided by any one of the aforementioned method embodiments when executing a program stored in the memory 113 .

[0118] It should be understood that in the embodiment of the present application, the processor 111 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0119] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0120] Therefore, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method provided in any one of the aforementioned method embodiments are implemented.

[0121] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a magnetic disk, or an optical disk, etc. Any physical storage medium capable of storing program code can be non-volatile or volatile.

[0122] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0123] In the several embodiments provided herein, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the various units is merely a logical functional division, and actual implementation may employ other division methods. For example, units or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0124] The steps in the methods of the embodiments of the present invention may be adjusted in order, combined, or deleted as needed. The units in the devices of the embodiments of the present invention may be combined, divided, or deleted as needed. Furthermore, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0125] If this integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, terminal, or network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present invention.

[0126] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0127] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, to the extent such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to encompass such changes and modifications.

[0128] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for determining image integrity, characterized in that: The method comprises: receiving a correction image, the correction image including an image of a correction card, wherein each of the four corners of the correction card is provided with a specific mark, and the specific mark is in a square shape; Preprocessing the corrected image to obtain an image to be measured; Identifying a specific identification area included in the image to be tested, where the specific identification area is an imaging area of ​​the specific identification in the image to be tested; Dividing four corner areas of preset sizes at the four corners of the image to be tested, and determining whether the four corner areas all contain the specific identification area, wherein the size of the corner area is larger than the size of the specific identification area; If all four corner areas include the specific identification area, determining whether image parameters of the specific identification areas of the four corner areas meet preset image parameter requirements; If the image parameters of the specific marked areas in the four corner areas all meet the preset image parameter requirements, it is determined that the corrected image is complete.

2. The image integrity determination method according to claim 1, wherein: The preprocessing of the corrected image to obtain the image to be measured includes: Adding a frame around the corrected image to obtain a frame image, wherein the color of the frame is the same as the background color of the corrected image; performing a binarization process on the frame image to obtain a binarized image; performing corrosion processing on the binary image to obtain a corroded image; The eroded image is expanded to obtain an image to be tested.

3. The image integrity determination method according to claim 1, wherein: The identifying of a specific identification area included in the image to be tested includes: The specific identification area contained in the image to be detected is identified by a preset target detection algorithm.

4. The image integrity determination method according to claim 1, wherein: The determining whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements includes: Calculating a first aspect ratio of the four specific identification areas; Calculating a second aspect ratio of the four specific marks; Calculating four deviation values ​​between the first aspect ratios of the four specific mark areas and the second aspect ratios of the four specific marks respectively, wherein the deviation value is the absolute value of the difference between the first aspect ratio of the specific mark area and the second aspect ratio of the specific mark; Determining whether the four deviation values ​​are all less than a preset deviation value threshold; If the four deviation values ​​are not all smaller than the preset deviation value threshold, it is determined that the image parameter does not meet the preset image parameter requirement.

5. The image integrity determination method according to claim 4, wherein: The determining whether the image parameters of the specific identification areas of the four corner areas meet the preset image parameter requirements also includes: If the four deviation values ​​are all smaller than the preset deviation value threshold, determining whether the pixels of the four specific identification areas are all larger than the preset pixel threshold; If the pixels of the four specific marking areas are all greater than the preset pixel threshold, it is determined that the image parameters of the specific marking areas in the four corner areas all meet the preset image parameter requirements.

6. The image integrity determination method according to claim 5, characterized in that: Calculating the first aspect ratio of the four specific identification areas includes: Obtaining a connected domain of the specific identified area; Calculating a minimum bounding rectangle that matches the connected domain; The aspect ratio of the minimum circumscribed rectangle is calculated to obtain a first aspect ratio.

7. The image integrity determination method according to claim 1, wherein: If the four corner areas do not all include the specific marking area, it is determined that the corrected image is incomplete; If the image parameters of the specific marked areas in the four corner areas do not all meet the preset image parameter requirements, it is determined that the corrected image is incomplete.

8. An image integrity judgment device, characterized in that: The image integrity judgment device includes a unit for executing the method according to any one of claims 1 to 7.

9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the method according to any one of claims 1 to 7 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the computer program can implement the method according to any one of claims 1 to 7.

Images