Computer control system with identity recognition function

Abstract

The invention belongs to the field of computers, and discloses a computer control system with an identity recognition function, which comprises a fingerprint image acquisition module, a fingerprint image recognition module, a mode judgment module, a display module, a password input module, a password verification module and a startup control module, the fingerprint image acquisition module is used for acquiring a fingerprint image of a person using the computer; the fingerprint image recognition module is used for recognizing the fingerprint image and obtaining and judging whether fingerprint verification is passed or not; the mode judgment module is used for judging whether secondary verification is needed or not; the display module is used for displaying characters for prompting the personnel to input a password through the password input module; the password input module is used for acquiring a password input by the person; the password verification module is used for judging whether password verification is passed; and the startup control module is used for controlling the display module to display an operation interface of the computer when secondary verification is not needed or password verification is passed. According to the invention, the security of the computer is improved.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular, to a computer control system with an identity recognition function. Background Art

[0002] During the computer startup process, identity recognition is usually performed first. After successful recognition, the computer desktop will be entered. The traditional identity recognition method is achieved by entering a password. With the development of technology, fingerprint recognition devices have gradually been integrated into many computers. When the computer power is turned on, the user will be prompted to perform fingerprint verification. Fingerprint verification is obviously more efficient than traditional password verification. The user only needs to place a finger near the fingerprint sensor, without having to repeatedly type the password on the keyboard. However, the fingerprint sensor also has a defect, that is, fingerprints may be illegally copied, resulting in the computer being illegally started and the data in the computer being leaked. Therefore, when using fingerprint recognition for computer identity recognition, how to further improve security has become a technical problem to be solved. Summary of the Invention

[0003] The purpose of the present invention is to disclose a computer control system with an identity recognition function to solve the technical problems raised in the background art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] The present invention provides a computer control system with an identity recognition function, including a fingerprint image acquisition module, a fingerprint image recognition module, a mode judgment module, a display module, a password input module, a password verification module, and a startup control module;

[0006] The fingerprint image acquisition module is used to acquire the fingerprint image of the person using the computer;

[0007] The fingerprint image recognition module is used to recognize the fingerprint image acquired by the fingerprint image acquisition module to obtain a judgment on whether the fingerprint verification is passed;

[0008] The mode judgment module is used to judge whether secondary verification is required when the person passes the fingerprint verification;

[0009] The display module is used to display text for prompting the person to input a password through the password input module when secondary verification is required;

[0010] The password input module is used to acquire the password input by the person;

[0011] The password verification module is used to judge whether the password verification is passed based on the password input by the person;

[0012] The power-on control module is used to control the display module to display the operation interface of the computer when secondary verification is not required or when password verification is passed;

[0013] Among them, the mode judgment module includes a time recognition unit, a time storage unit, and a comparison unit;

[0014] The time recognition unit is used to obtain the first acquisition time of the fingerprint image newly obtained by the fingerprint image acquisition module;

[0015] The time storage unit is used to store the second acquisition time of the historical fingerprint images obtained by the fingerprint image acquisition module;

[0016] The comparison unit is used to judge whether secondary verification is required based on the first acquisition time and the second acquisition time.

[0017] Preferably, the fingerprint image recognition module includes a storage unit, a feature extraction unit, and a feature comparison unit;

[0018] The storage unit is used to store the pre-entered fingerprint images;

[0019] The feature extraction unit is used to obtain the image feature Z1 of the pre-entered fingerprint image, and to obtain the image feature Z2 of the fingerprint image obtained by the fingerprint image acquisition module;

[0020] The feature comparison unit is used to calculate the similarity between Z1 and Z2, and to judge whether fingerprint verification is passed based on the similarity.

[0021] Preferably, for the fingerprint image q, the process of obtaining the image feature of the fingerprint image q includes:

[0022] Perform grayscale processing on the fingerprint image q to obtain the image grayq;

[0023] Perform noise reduction processing on the image grayq to obtain the image lowq;

[0024] Obtain the image feature of lowq.

[0025] Preferably, performing noise reduction processing on the image grayq to obtain the image lowq includes:

[0026] Detect the image grayq, obtain the set P1 of significant pixel points in grayq, and store the remaining pixel points in grayq into the set P2;

[0027] In the image grayq, perform noise reduction processing on the pixel points in the set U1 to obtain the image midq;

[0028] Obtain the set L2 of the coordinates of the pixel points in P2;

[0029] In midq, denoise the pixel points corresponding to the coordinates in set L2 to obtain image lowq.

[0030] Preferably, in image grayq, denoise the pixel points in set U1 to obtain image midq, including:

[0031] In grayq, use the non-local means filtering algorithm to denoise the pixel points in U1 to obtain image midq.

[0032] Preferably, in midq, denoise the pixel points corresponding to the coordinates in set L2 to obtain image lowq, including:

[0033] In midq, use the bilateral filtering algorithm to denoise the pixel points corresponding to the coordinates in set L2 to obtain image lowq.

[0034] Preferably, judge whether password verification is passed based on the password input by the person, including:

[0035] Compare the password input by the person with the pre-stored password to judge whether they are the same. If so, it means that password verification is passed; if not, password verification is not passed.

[0036] Preferably, the historical fingerprint images include all the fingerprint images obtained in the most recent month except for the most recently obtained fingerprint image.

[0037] Preferably, both the first acquisition time and the second acquisition time are in 24-hour format and accurate to the minute.

[0038] Preferably, judge whether secondary verification is required based on the first acquisition time and the second acquisition time, including:

[0039] Store the second acquisition time of the historical fingerprint images in set T1;

[0040] Filter the second acquisition times in T1 to obtain set T2;

[0041] Obtain the median of the acquisition times in T2;

[0042] Calculate the time length between the first acquisition time and the median of the acquisition times in T2;

[0043] Judge whether the time length is greater than the set time duration. If so, it means that secondary verification is required.

[0044] Beneficial effects:

[0045] In the process of booting up the computer for identity recognition, the present invention does not solely judge whether to display the operation interface based on the fingerprint image because the security of this method is not high enough. By additionally adding the judgment of obtaining the time, the present invention makes an auxiliary judgment on whether the booting behavior is legal from another aspect, thereby effectively enhancing the security of the computer. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for describing the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0047] Figure 1 It is a schematic diagram of a computer control system with an identity recognition function according to the present invention.

[0048] Figure 2 It is a schematic diagram of the process for the present invention to judge whether secondary verification is required. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, rather than all, embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0050] The present invention provides a computer control system with an identity recognition function, including a fingerprint image acquisition module, a fingerprint image recognition module, a mode judgment module, a display module, a password input module, a password verification module, and a boot control module;

[0051] The fingerprint image acquisition module is used to acquire the fingerprint image of the person using the computer;

[0052] The fingerprint image recognition module is used to recognize the fingerprint image acquired by the fingerprint image acquisition module to obtain a judgment on whether the fingerprint verification is passed;

[0053] The mode judgment module is used to judge whether secondary verification is required when the person passes the fingerprint verification;

[0054] The display module is used to display the text for prompting the person to input the password through the password input module when secondary verification is required;

[0055] The password input module is used to acquire the password input by the person;

[0056] The password verification module is used to determine whether the password verification is passed based on the password input by the person;

[0057] The power-on control module is used to control the display module to display the operation interface of the computer when secondary verification is not required or when the password verification is passed;

[0058] The operation interface here refers to the interface where the user can freely operate using the keyboard and mouse, such as the desktop of the Windows system.

[0059] Among them, the mode judgment module includes a time recognition unit, a time storage unit, and a comparison unit;

[0060] The time recognition unit is used to obtain the first acquisition time of the fingerprint image newly obtained by the fingerprint image acquisition module;

[0061] The time storage unit is used to store the second acquisition time of the historical fingerprint images obtained by the fingerprint image acquisition module;

[0062] The comparison unit is used to determine whether secondary verification is required based on the first acquisition time and the second acquisition time.

[0063] Here, both the first acquisition time and the second acquisition time refer to the acquisition time of the fingerprint image, but they are distinguished as the newly obtained and the historically obtained fingerprint images by the first and the second respectively.

[0064] Since for the same user, the power-on time is similar, therefore, when it is found that the power-on time is too different from the usual power-on time, by performing secondary verification, the security of the computer can be effectively improved.

[0065] Preferably, the fingerprint image recognition module includes a storage unit, a feature extraction unit, and a feature comparison unit;

[0066] The storage unit is used to store the pre-entered fingerprint images;

[0067] The feature extraction unit is used to obtain the image feature Z1 of the pre-entered fingerprint image, and to obtain the image feature Z2 of the fingerprint image obtained by the fingerprint image acquisition module;

[0068] The feature comparison unit is used to calculate the similarity between Z1 and Z2, and to determine whether the fingerprint verification is passed based on the similarity.

[0069] The entry of the fingerprint image can be performed after the fingerprint verification when there is only the means of fingerprint verification, or can be directly entered by a person with administrative authority.

[0070] Preferably, the image features of the fingerprint image can be extracted by a method based on the Directional Gradient Histogram (DGH). By calculating the gradient direction and intensity of each pixel point in the fingerprint image, a directional gradient histogram is constructed, thereby extracting the ridge features of the fingerprint.

[0071] Preferably, for the fingerprint image q, the process of obtaining the image features of the fingerprint image q includes:

[0072] Perform grayscale processing on the fingerprint image q to obtain the image grayq;

[0073] Perform noise reduction processing on the image grayq to obtain the image lowq;

[0074] Obtain the image features of lowq.

[0075] Converting the fingerprint image to a grayscale image reduces the data volume, lowers the computational complexity, weakens the color noise and focuses on the brightness change, making the application more efficient and accurate.

[0076] Image noise reduction processing can reduce the noise in the image and improve the image quality. Noise will interfere with the visual effect of the image, making the image appear blurred. By reducing noise, the clarity and authenticity of the image can be enhanced, making the image easier to observe and analyze. At the same time, it is also beneficial to subsequent image processing and analysis work, improving the accuracy and efficiency of processing.

[0077] Preferably, performing noise reduction processing on the image grayq to obtain the image lowq includes:

[0078] Detect the image grayq, obtain the set P1 of significant pixel points in grayq, and store the remaining pixel points in grayq in the set P2;

[0079] In the image grayq, perform noise reduction processing on the pixel points in the set U1 to obtain the image midq;

[0080] Obtain the set L2 of the coordinates of the pixel points in P2;

[0081] In midq, perform noise reduction processing on the pixel points corresponding to the coordinates in the set L2 to obtain the image lowq.

[0082] The present invention does not perform noise reduction processing only based on the image grayq, because this is likely to suppress the significance of the pixel points at the edges of the connected regions in the image after noise reduction, resulting in the loss of more edge information. Therefore, after identifying the significant pixel points, the present invention first performs noise reduction on the pixel points in P1 in the image grayq, and then performs noise reduction on the remaining pixel points in midq. On the one hand, it can achieve noise reduction for all pixel points, and on the other hand, it can preferentially perform noise reduction on the pixel points belonging to the edges of the connected regions, retaining more image edge information. On the other hand, when performing noise reduction on the pixel points corresponding to the coordinates in L2, the noise reduction can be based on the gray values of more pixel points that have been noise-reduced, further improving the accuracy of the noise reduction result.

[0083] Preferably, the image grayq is detected to obtain the set P1 of significant pixel points in grayq, including:

[0084] Let q represent the pixel points in grayq, and store the pixel points in the 8-neighborhood of q into the set nuq;

[0085] Calculate the judgment value jud of the pixel point q q :

[0086]

[0087] Gry q and Gry i are the gray values of the pixel points q and i respectively, Gry ma is the maximum value of the gray values of the pixel points in nuq, ns represents the number of pixel points in nuq whose similarity with the pixel point q meets the set conditions, and λ is the weight;

[0088] Judge whether jud q is greater than the set value. If so, store q into P1.

[0089] The present invention calculates the judgment value through two aspects: the gray value and the number of pixel points whose similarity meets the conditions. When the difference between the gray value of q and the average value of the gray values in the 8-neighborhood is larger, and the number of pixel points in the 8-neighborhood whose similarity with q meets the set conditions is more, the probability that q is stored into P1 is greater. This can not only screen out the pixel points that are significantly different from the surrounding pixel points, but also effectively reduce the probability that the noise pixel points are recognized as significant pixel points. As a result, the noise pixel points have a higher probability of being noise-reduced in midq. Since the pixel points belonging to the edges of the connected regions in midq have already been noise-reduced, the noise reduction process of the noise pixel points can be based on a more accurate neighborhood gray distribution, making the noise reduction result more accurate.

[0090] Preferably, the statistical process of the number of pixel points in nuq whose similarity to pixel point q meets the set conditions includes:

[0091] Calculate the ratio between the gray value of each pixel point in nuq and the gray value of pixel point q respectively;

[0092] Store the pixel points with a ratio greater than the set ratio threshold into set Bq;

[0093] Take the number of pixel points in Bq as the number of pixel points in nuq whose similarity to pixel point q meets the set conditions.

[0094] By calculating the ratio of gray values, pixel points with a relatively high probability of being noise pixel points can be initially excluded from P1. Because the gray values of noise pixel points are usually significantly greater than those of surrounding pixel points, and there are usually few pixel points with similar gray values in the 8-neighborhood.

[0095] Preferably, the set ratio threshold is 0.9.

[0096] Preferably, the value of λ is 0.3.

[0097] Preferably, the set value is 0.6.

[0098] Preferably, in the image grayq, perform noise reduction processing on the pixel points in set U1 to obtain the image midq, including:

[0099] In grayq, use the non-local mean filtering algorithm to perform noise reduction processing on the pixel points in U1 to obtain the image midq.

[0100] The non-local mean noise reduction algorithm can utilize the non-local similarity of pixels in the image, that is, there are many similar image patches in the image, and noise reduction is achieved by calculating the weighted average of these similar patches. While removing noise, this algorithm can better retain the details and texture information of the image and has a good removal effect on common noise types such as Gaussian noise.

[0101] Preferably, in midq, perform noise reduction processing on the pixel points corresponding to the coordinates in set L2 to obtain the image lowq, including:

[0102] In midq, use the bilateral filtering algorithm to perform noise reduction processing on the pixel points corresponding to the coordinates in set L2 to obtain the image lowq.

[0103] The bilateral filtering algorithm can effectively retain the edge details of the image while removing image noise. The following are the key features of the bilateral filtering algorithm:

[0104] Spatial proximity: The filter takes into account the spatial distance between a pixel and its surrounding pixels. The closer the distance, the greater the impact of the pixel on the filtering result.

[0105] Pixel similarity: The filter also considers the similarity of pixel values, that is, the difference in pixel grayscale values or color values. Pixels with higher similarity have a greater impact on the filtering result.

[0106] Weighted average: By calculating the weighted average of the surrounding pixels, the weights are jointly determined by the spatial distance and pixel similarity, thereby achieving a smoothing effect.

[0107] Preserving edge details: Bilateral filtering can smooth the image while preserving or even enhancing the edge details of the image, avoiding the edge blurring problem that may be caused by traditional filters (such as Gaussian filtering).

[0108] Flexibility: The filtering effect can be controlled by adjusting parameters (such as the standard deviation in the spatial domain and the standard deviation in the value domain) to meet different image processing requirements.

[0109] Preferably, judging whether the password verification is passed based on the password input by the person includes:

[0110] Comparing the password input by the person with the pre-stored password to determine whether they are the same. If so, it means the password verification is passed; if not, the password verification fails.

[0111] Preferably, the historical fingerprint images include all the fingerprint images obtained in the most recent month except for the latest obtained fingerprint image.

[0112] In the present invention, the latest obtained fingerprint image is the fingerprint image of the user to be verified. Therefore, the historical fingerprint images cannot include this fingerprint image.

[0113] Preferably, both the first acquisition time and the second acquisition time are in 24-hour format and accurate to the minute.

[0114] The structure of the acquisition time in the present invention is xx:xx. For example, 8:30, 9:00, etc.

[0115] Preferably, as Figure 2 shown, judging whether secondary verification is required based on the first acquisition time and the second acquisition time includes:

[0116] Storing the second acquisition time of the historical fingerprint images into the set T1;

[0117] Filtering the second acquisition times in T1 to obtain the set T2;

[0118] Obtaining the median of the acquisition times in T2;

[0119] Calculate the time length between the first acquisition time and the median of the acquisition times in T2;

[0120] Determine whether the time length is greater than the set duration. If so, it indicates that secondary verification is required.

[0121] By performing screening, the second acquisition times with excessive deviations can be eliminated, making the obtained median more accurate.

[0122] Preferably, screen the second acquisition times in T1 to obtain a set T2, including:

[0123] Sort the second acquisition times in T1 in ascending order to obtain a sequence L;

[0124] Delete the first M second acquisition times and the last M second acquisition times in the sequence L from T1 to obtain the set T2.

[0125] Preferably, the value of M is one-tenth of the total number of the second acquisition times in T1.

[0126] Preferably, the set duration is 0.5 hours.

[0127] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A computer control system with identity recognition function, characterized in that: It includes a fingerprint image acquisition module, a fingerprint image recognition module, a mode judgment module, a display module, a password input module, a password verification module and a power-on control module; The fingerprint image acquisition module is used to obtain the fingerprint image of the person using the computer; The fingerprint image recognition module is used to recognize the fingerprint image collected by the fingerprint image acquisition module and determine whether the fingerprint verification has been passed; The mode determination module is used to determine whether a secondary verification is required when the person passes the fingerprint verification; The display module is used to display text for prompting the person to input a password through the password input module when a secondary verification is required; The password input module is used to obtain the password input by the personnel; The password verification module is used to determine whether the password verification is passed based on the password input by the person; The power-on control module is used to control the display module to display the computer operation interface when secondary verification is not required or when password verification is passed; Wherein, the mode judgment module includes a time recognition unit, a time storage unit and a comparison unit; The time recognition unit is used to obtain the first acquisition time of the fingerprint image most recently obtained by the fingerprint image acquisition module; The time storage unit is used to store the second acquisition time of the historical fingerprint image obtained by the fingerprint image acquisition module; The comparison unit is used to determine whether secondary verification is required based on the first acquisition time and the second acquisition time.

2. A computer control system with identity recognition function according to claim 1, characterized in that: The fingerprint image recognition module includes a storage unit, a feature extraction unit and a feature comparison unit; The storage unit is used to store the pre-recorded fingerprint image; The feature extraction unit is used to obtain the image feature Z1 of the pre-recorded fingerprint image, and is used to obtain the image feature Z2 of the fingerprint image obtained by the fingerprint image acquisition module; The feature comparison unit is used to calculate the similarity between Z1 and Z2, and determine whether the fingerprint verification is passed based on the similarity.

3. A computer control system with identity recognition function according to claim 2, characterized in that: For a fingerprint image q, the process of obtaining the image features of the fingerprint image q includes: Perform grayscale processing on the fingerprint image q to obtain the image grayq; Perform noise reduction on the image grayq to obtain the image lowq; Get lowq image features.

4. A computer control system with identity recognition function according to claim 3, characterized in that: Perform noise reduction on the image grayq to obtain the image lowq, including: Detect the image grayq, obtain the set P1 of significant pixels in grayq, and store the remaining pixels in grayq into the set P2; In the image grayq, the pixels in the set U1 are subjected to noise reduction processing to obtain the image midq; Get the set L2 of coordinates of the pixel points in P2; In midq, the pixel points corresponding to the coordinates in the set L2 are subjected to noise reduction processing to obtain the image lowq.

5. A computer control system with identity recognition function according to claim 4, characterized in that: In the image grayq, the pixels in the set U1 are subjected to noise reduction processing to obtain the image midq, including: In grayq, the non-local mean filtering algorithm is used to reduce the noise of the pixels in U1 to obtain the image midq.

6. A computer control system with identity recognition function according to claim 4, characterized in that: In midq, the pixel points corresponding to the coordinates in the set L2 are subjected to noise reduction processing to obtain the image lowq, including: In midq, a bilateral filtering algorithm is used to perform noise reduction on the pixel points corresponding to the coordinates in the set L2 to obtain the image lowq.

7. A computer control system with identity recognition function according to claim 1, characterized in that: Determining whether the password verification is passed based on the password input by the person includes: The password entered by the person is compared with the pre-stored password to determine whether the two are consistent. If so, it means that the password verification has passed, if not, it means that the password verification has not passed.

8. The computer control system with identity recognition function according to claim 1, characterized in that: The historical fingerprint images include all fingerprint images obtained in the latest month except the latest fingerprint image.

9. A computer control system with identity recognition function according to claim 8, characterized in that: The first acquisition time and the second acquisition time are both in 24-hour format, accurate to the minute.

10. A computer control system with identity recognition function according to claim 9, characterized in that: Determining whether secondary verification is required based on the first acquisition time and the second acquisition time includes: Store the second acquisition time of the historical fingerprint image into set T1; Filter the second acquisition time in T1 to obtain set T2; Get the median acquisition time in T2; Calculate the time interval between the first acquisition time and the median of the acquisition time in T2; Determine whether the time length is greater than the set time length. If so, it means that secondary verification is required.

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