CN114212050A - Control method for unlocking vehicle door based on capacitive sensing - Google Patents
Control method for unlocking vehicle door based on capacitive sensing Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
- B60R25/20—Means to switch the anti-theft system on or off
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
- B60R25/20—Means to switch the anti-theft system on or off
- B60R25/25—Means to switch the anti-theft system on or off using biometry
- B60R25/252—Fingerprint recognition
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Human Computer Interaction (AREA)
- Lock And Its Accessories (AREA)
Abstract
The invention discloses a control method for unlocking a vehicle door based on capacitive sensing, which aims to solve the technical problems that in the prior art, the capacitive sensing function is not available, and when a user approaches the vehicle door, the system cannot be controlled in an annular mode, so that the time consumed for unlocking the vehicle door is long, fingerprints cannot be processed, and the fingerprint comparison precision is reduced. The control method comprises the following steps: s1: when the hand of a user approaches to the door handle, the capacitance of the sensor in the handle changes, the control system recognizes the capacitance change of the sensor and then wakes up the control system; s2: and sending the input fingerprint to a comparison unit, comparing the acquired input fingerprint with the template fingerprint, and verifying the identity of the user. The control method adopts a capacitive sensing design, and wakes up the control system when a user approaches the door handle, so that the unlocking time of the door is effectively shortened, and the intelligent degree of the unlocking instruction sent to the door lock execution mechanism by the control system is higher.
Description
Technical Field
The invention belongs to the technical field of automobile door lock control, and particularly relates to a control method for unlocking an automobile door based on capacitive sensing.
Background
With the improvement of living standard, the automobile is widely used in daily life, in order to improve the anti-theft performance of the automobile, the automobile needs to be equipped with a door lock, and with the continuous development of technology, a key is not needed, so that the opening of an automobile door is realized.
At present, the invention patent with the patent number CN201910144916.7 discloses an automobile unlocking system relating to biometric identification and NFC authentication, which comprises a fingerprint acquisition terminal, an NFC communication module and a circuit control system. The fingerprint acquisition terminal comprises a living fingerprint identification module and an indicator light; the NFC communication module comprises a mobile phone terminal with an NFC function and an electronic signature module, and stores the fingerprint characteristic information of the driver in an NFC emitter and a reader; the circuit control system comprises a microprocessor and a data storage unit. The device is mainly divided into three modes corresponding to three security levels. The automobile door unlocking method has the advantages that the automobile door unlocking is realized through biological identification and NFC authentication, but the control method does not have the function of capacitance induction, and when a user approaches the automobile door, the system cannot be controlled in an annular mode, so that the time consumed for unlocking the automobile door is long, fingerprints cannot be processed, and the fingerprint comparison precision is reduced.
Therefore, it is necessary to solve the above-mentioned problem without capacitance sensing function to improve the use scene of the automobile.
Disclosure of Invention
(1) Technical problem to be solved
Aiming at the defects of the prior art, the invention aims to provide a control method for unlocking a vehicle door based on capacitive sensing, which aims to solve the technical problems that the prior art does not have the function of capacitive sensing, and when a user approaches the vehicle door, the system cannot be controlled in an annular mode, so that the time consumed for unlocking the vehicle door is long, the fingerprint cannot be processed, and the fingerprint comparison precision is reduced.
(2) Technical scheme
In order to solve the technical problem, the invention provides a control method for unlocking a vehicle door based on capacitive sensing, which comprises the following steps:
s1: when the hand of a user approaches to the door handle, the capacitance of the sensor in the handle changes, the control system recognizes the capacitance change of the sensor, then the control system is awakened, the user presses the hand at the sensing position of the door handle, and the sensing position collects the input fingerprint of the user;
s2: the input fingerprint is sent to a comparison unit, the acquired input fingerprint is compared with the template fingerprint, and the identity of the user is verified:
s21: image enhancement: dividing the image into areas of size W x W, calculating local orientation of ridges on each area to determine orientation pattern, then adding a filter to make it suitable for all pixels on the image, the filter enhancing the orientation of ridges in the same direction according to the local orientation of ridges at each pixel, and at the same position, attenuating any orientation different from ridges, the latter containing noise across ridges whose incorrect bridges perpendicular to the local orientation of ridges are filtered out by the filter;
s22: and (3) calculating a directional diagram: calculating statistic of each point in each direction in the original gray-scale fingerprint image, and determining the direction of the point according to the difference of the statistic in each direction;
s23: and (3) binarization processing: calculating an adaptive threshold value, wherein the calculation formula is TT-R- (T-R)/2, and filtering the image by adopting a generalized Laplacian algorithm;
s24: thinning: reducing the width of the ridge to a single pixel width;
s25: extracting fingerprint characteristic points;
s26: comparing the feature points, arranging an allowable frame around the feature points, and presetting a matching index threshold value X;
s3: after the identity authentication is passed, the control system sends an unlocking instruction to the door lock execution mechanism, the door lock controller provides unlocking pulse current, and the lock catch connecting rod is controlled to move left and right, so that the unlocking of the vehicle door is realized.
Preferably, the S2 comparison unit is provided with a fingerprint database for storing template fingerprints.
Preferably, the statistics in S22 include gray scale differences and gradients.
Preferably, in S23, R is an average value obtained by removing the maximum and minimum points in the direction, T is an average value of the maximum and minimum points, and (T-R)/2 is a correction value.
Preferably, the fingerprint feature points in S25 include termination points, bifurcation points, isolated points, ring points, striae, direction, curvature and position.
Preferably, the step of extracting the fingerprint feature points in S25 includes: extracting image features and removing pseudo feature points in the extracted feature points, wherein the types of the pseudo feature points mainly comprise: burrs, short lines, pinholes, false bridges, and broken lines.
Preferably, the specific step of comparing the feature points in S26 is: converting the coordinates of the characteristic points into polar coordinates, finding two points with the same type in the template fingerprint and the input fingerprint respectively as reference points, penetrating the input points in the template and the polar coordinates as symbols, connecting each point according to the increasing order of polar angles, adding 1 to the matching index if the input characteristic points are in the corresponding allowable frames, and judging that the matching is successful if the matching index is greater than a preset matching index threshold value X for a fingerprint image.
Preferably, the S3 lock controller has a timing function.
(3) Advantageous effects
Compared with the prior art, the invention has the beneficial effects that: the control method provided by the invention adopts a capacitive sensing design, and the control system is awakened when a user approaches a door handle, so that the unlocking time of the door is effectively shortened, meanwhile, the input fingerprint is collected and processed, the input fingerprint is convenient to compare with the template fingerprint, the identity of the user is verified, the door is prevented from being opened by a stranger, potential safety hazards are avoided, an unlocking instruction is sent to a door lock execution mechanism through the control system, then, the door lock controller provides unlocking pulse current, and the lock catch connecting rod is controlled to move left and right, so that the unlocking of the door is realized, the unlocking is convenient, and the intelligent degree is higher.
Detailed Description
In order to make the technical means, the original characteristics, the achieved purposes and the effects of the invention easily understood and obvious, the technical solutions in the embodiments of the present invention are clearly and completely described below to further illustrate the invention, and obviously, the described embodiments are only a part of the embodiments of the present invention, but not all the embodiments.
Example 1
The specific embodiment is a control method for unlocking a vehicle door based on capacitive sensing, and the control method comprises the following steps:
s1: when the hand of a user approaches to the door handle, the capacitance of the sensor in the handle changes, the control system recognizes the capacitance change of the sensor, then the control system is awakened, the user presses the hand at the sensing position of the door handle, and the sensing position collects the input fingerprint of the user;
s2: the input fingerprint is sent to a comparison unit, the acquired input fingerprint is compared with the template fingerprint, and the identity of the user is verified:
s21: image enhancement: dividing the image into areas of size W x W, calculating local orientation of ridges on each area to determine orientation pattern, then adding a filter to make it suitable for all pixels on the image, the filter enhancing the orientation of ridges in the same direction according to the local orientation of ridges at each pixel, and at the same position, attenuating any orientation different from ridges, the latter containing noise across ridges whose incorrect bridges perpendicular to the local orientation of ridges are filtered out by the filter;
s22: and (3) calculating a directional diagram: calculating statistic of each point in each direction in the original gray-scale fingerprint image, and determining the direction of the point according to the difference of the statistic in each direction;
s23: and (3) binarization processing: calculating an adaptive threshold value, wherein the calculation formula is TT-R- (T-R)/2, and filtering the image by adopting a generalized Laplacian algorithm;
s24: thinning: reducing the width of the ridge to a single pixel width;
s25: extracting fingerprint characteristic points;
s26: comparing the feature points, arranging an allowable frame around the feature points, and presetting a matching index threshold value X;
s3: after the identity authentication is passed, the control system sends an unlocking instruction to the door lock execution mechanism, the door lock controller provides unlocking pulse current, and the lock catch connecting rod is controlled to move left and right, so that the unlocking of the vehicle door is realized.
The S2 comparison unit is provided with a fingerprint library for storing template fingerprints, the statistics in S22 include gray level difference and gradient, R in S23 is an average value of maximum and minimum points removed in the direction, T is an average value of the maximum and minimum points, and (T-R)/2 is a correction value.
Meanwhile, the fingerprint feature points in S25 include termination points, bifurcation points, isolated points, ring points, striae, direction, curvature and position, and the step of extracting fingerprint feature points in S25 includes: extracting image features and removing pseudo feature points in the extracted feature points, wherein the types of the pseudo feature points mainly comprise: burrs, short lines, pinholes, false bridges, and broken lines.
In addition, the specific steps of comparing the feature points in S26 are as follows: converting the coordinates of the characteristic points into polar coordinates, finding two points with the same type in the template fingerprint and the input fingerprint respectively as reference points, penetrating the input points in the template and the polar coordinates as symbols, connecting each point according to the increasing order of polar angles, adding 1 to the matching index if the input characteristic points are in the corresponding allowable frames, and judging that the matching is successful if the matching index is greater than a preset matching index threshold value X for a fingerprint image.
Further, the door lock controller in S3 has a timing function.
When the control method of the technical scheme is used, S1: when the hand of a user approaches to the door handle, the capacitance of the sensor in the handle changes, the control system recognizes the capacitance change of the sensor, then the control system is awakened, the user presses the hand at the sensing position of the door handle, and the sensing position collects the input fingerprint of the user; s2: will input the fingerprint and send to the unit of comparing, compare and be equipped with the fingerprint storehouse that is used for saving the template fingerprint in the unit, compare with the input fingerprint of gathering and template fingerprint, verify user's identity: s21: image enhancement: dividing the image into areas of size W x W, calculating local orientation of ridges on each area to determine orientation pattern, then adding a filter to make it suitable for all pixels on the image, the filter enhancing the orientation of ridges in the same direction according to the local orientation of ridges at each pixel, and at the same position, attenuating any orientation different from ridges, the latter containing noise across ridges whose incorrect bridges perpendicular to the local orientation of ridges are filtered out by the filter; s22: and (3) calculating a directional diagram: calculating statistic of each point in each direction in the original gray-scale fingerprint image, wherein the statistic comprises gray-scale difference and gradient, and determining the direction of the point according to the difference of the statistic in each direction; s23: and (3) binarization processing: calculating an adaptive threshold value, wherein the calculation formula is TT-R- (T-R)/2, R is an average value of the maximum point and the minimum point removed in the direction, T is an average value of the maximum point and the minimum point, and (T-R)/2 is a correction value, and filtering the image by adopting a generalized Laplace algorithm; s24: thinning: reducing the width of the ridge to a single pixel width; s25: extracting fingerprint feature points, wherein the fingerprint feature points comprise termination points, bifurcation points, isolated points, ring points, short stripes, directions, curvatures and positions, and the step of extracting the fingerprint feature points comprises the following steps: extracting image features and removing pseudo feature points in the extracted feature points, wherein the types of the pseudo feature points mainly comprise: burrs, short lines, small holes, false small bridges and broken lines; s26: comparing the feature points, arranging an allowable frame around the feature points, presetting a matching index threshold value X, and specifically comparing the feature points as follows: converting the coordinates of the characteristic points into polar coordinates, finding two points with the same type in the template fingerprint and the input fingerprint as reference points respectively, using the input points in the template fingerprint and the polar coordinates as symbols to pass through, connecting each point according to the increasing order of polar angles, adding 1 to the matching index if the input characteristic points are in the corresponding allowable frames, and judging that the matching is successful if the matching index is greater than a preset matching index threshold value X for a fingerprint image; s3: after the identity authentication is passed, the control system sends an unlocking instruction to the door lock execution mechanism, the door lock controller provides unlocking pulse current to control the lock catch connecting rod to move left and right, and therefore unlocking of the vehicle door is achieved, and the door lock controller has a timing function.
Having thus described the principal technical features and basic principles of the invention, and the advantages associated therewith, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, but is capable of other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present description is described in terms of various embodiments, not every embodiment includes only a single embodiment, and such descriptions are provided for clarity only, and those skilled in the art will recognize that the embodiments described herein can be combined as a whole to form other embodiments as would be understood by those skilled in the art.
Claims (8)
1. A control method for unlocking a vehicle door based on capacitive sensing comprises the following steps:
s1: when the hand of a user approaches to the door handle, the capacitance of the sensor in the handle changes, the control system recognizes the capacitance change of the sensor, then the control system is awakened, the user presses the hand at the sensing position of the door handle, and the sensing position collects the input fingerprint of the user;
s2: the input fingerprint is sent to a comparison unit, the acquired input fingerprint is compared with the template fingerprint, and the identity of the user is verified:
s21: image enhancement: dividing the image into areas of size W x W, calculating local orientation of ridges on each area to determine orientation pattern, then adding a filter to make it suitable for all pixels on the image, the filter enhancing the orientation of ridges in the same direction according to the local orientation of ridges at each pixel, and at the same position, attenuating any orientation different from ridges, the latter containing noise across ridges whose incorrect bridges perpendicular to the local orientation of ridges are filtered out by the filter;
s22: and (3) calculating a directional diagram: calculating statistic of each point in each direction in the original gray-scale fingerprint image, and determining the direction of the point according to the difference of the statistic in each direction;
s23: and (3) binarization processing: calculating an adaptive threshold value, wherein the calculation formula is TT-R- (T-R)/2, and filtering the image by adopting a generalized Laplacian algorithm;
s24: thinning: reducing the width of the ridge to a single pixel width;
s25: extracting fingerprint characteristic points;
s26: comparing the feature points, arranging an allowable frame around the feature points, and presetting a matching index threshold value X;
s3: after the identity authentication is passed, the control system sends an unlocking instruction to the door lock execution mechanism, the door lock controller provides unlocking pulse current, and the lock catch connecting rod is controlled to move left and right, so that the unlocking of the vehicle door is realized.
2. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein a fingerprint library for storing template fingerprints is arranged in the S2 comparison unit.
3. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein the statistics in S22 include gray scale difference and gradient.
4. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein R in S23 is an average value of the maximum and minimum points removed in the direction, T is an average value of the maximum and minimum points, and (T-R)/2 is a correction value.
5. The control method for unlocking a vehicle door based on capacitive sensing of claim 1, wherein the fingerprint feature points in S25 include termination points, bifurcation points, isolated points, ring points, striae, direction, curvature and position.
6. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein the step of extracting the fingerprint feature points in the step S25 includes: extracting image features and removing pseudo feature points in the extracted feature points, wherein the types of the pseudo feature points mainly comprise: burrs, short lines, pinholes, false bridges, and broken lines.
7. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein the specific step of comparing the characteristic points in the step S26 is as follows: converting the coordinates of the characteristic points into polar coordinates, finding two points with the same type in the template fingerprint and the input fingerprint respectively as reference points, penetrating the input points in the template and the polar coordinates as symbols, connecting each point according to the increasing order of polar angles, adding 1 to the matching index if the input characteristic points are in the corresponding allowable frames, and judging that the matching is successful if the matching index is greater than a preset matching index threshold value X for a fingerprint image.
8. The control method for unlocking the vehicle door based on the capacitive sensing as claimed in claim 1, wherein the door lock controller in S3 has a timing function.
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