Application of fingerprint identification for controlling charging pile to start and stop charging

Abstract

The invention discloses application of fingerprint identification to control starting and stopping of charging of a charging pile. A switching signal is output through a fingerprint module: charging is started successfully when fingerprint identification is performed once, and charging is paused, interrupted or ended successfully when fingerprint identification is performed again; performing signal identification before the charging pile is started; information query is carried out through fingerprints in the charging process; and charging pause, interruption or charging ending is realized through fingerprint identification. According to the invention, the charging pile is controlled to start and stop charging through fingerprints; the non-linear adaptive filter is used for removing a black area around the white points and an isolated area around the black points to guarantee the uniformity of fingerprint line amplitude; the filtering is realized by combining a linear filter and an intermediate value nonlinear filter; the problem that many false characteristic quantities appear in the prior art is solved; and the problem that the place connected with the fingerprint is broken is also solved.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile start-stop control, and in particular to an application of fingerprint recognition for controlling the start and stop of charging of a charging pile. Background Art

[0002] When the charging pile is charging an external electric vehicle, as the vehicle battery status changes, the electric vehicle's charging needs will also change accordingly. Therefore, the charging pile needs to continuously adjust the charging output, which involves frequent switching operations between the charging modules in the charging pile.

[0003] The existing charging piles do not have an application to control the start and stop of the charging piles by fingerprints. Therefore, we propose an application of fingerprint recognition to control the start and stop of charging piles. In addition, when there is no physical button function in the input part, it is necessary to determine the moment of fingerprint collection.

[0004] The fingerprint recognition in the prior art also has the following problems:

[0005] 1. The fingerprint entry part captures the background based on the pressure of the finger and the position where the finger touches. If a local area of ​​the fingerprint is extracted, the fingerprint recognition rate may be reduced. Therefore, it is very important to extract the actual effective area.

[0006] 2. In the input image, when the fingerprint amplitude changes or there are many isolated points (holes), many false features may appear when detecting feature points; and false features may also be detected when the filtering processing is improper; for example, the fingerprint lines are connected, or the places that should be connected are broken.

[0007] 3. At present, most of the feature quantity selection methods include methods based on refinement, methods based on ensuring the uniformity of fingerprint line width, etc. The disadvantage of the above methods is that the processing time is too long. Summary of the invention

[0008] The purpose of the present invention is to provide an application of fingerprint recognition for controlling the start and stop of charging of a charging pile to solve the problems in the prior art.

[0009] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a fingerprint recognition is used to control the application of charging pile to start and stop charging, and a switch signal is output through a fingerprint module: the charging is successfully started by recognizing the fingerprint once, and the charging is successfully paused, interrupted or ended by recognizing the fingerprint again;

[0010] Signal recognition before charging pile starts;

[0011] Information query is performed through fingerprints during the charging process;

[0012] Fingerprint recognition can be used to pause, interrupt or end charging.

[0013] Preferably, fingerprint identification comprises the following steps:

[0014] S1: Input fingerprint;

[0015] S2: Extracting fingerprint area: First, the fingerprint area is divided into several blocks of a certain size, and then the density distribution information of the blocks is used to extract the fingerprint edge;

[0016] S3: Automatic imaging: using the concentration distribution map of a part of the fingerprint area;

[0017] S4: Digital processing: The image block’s average density information and background density are automatically processed;

[0018] S5: Classification of fingerprint morphology;

[0019] S6: Nonlinear adaptive filter: removes the black area around the white point and the isolated area around the black point to ensure the uniformity of the fingerprint line width;

[0020] S7: center direction of fingerprint;

[0021] S8: determine the fingerprint block direction vector;

[0022] S9: Determination of feature quantity: Minutia is directly determined based on the digital processing value;

[0023] S10: High-speed comparison algorithm.

[0024] Preferably, the S1 input fingerprint is a black and white image with an image size of 256X256PIX input from a CCD input module.

[0025] Preferably, the S5 fingerprint morphological classification refers to 99% of the identification features among the four morphological classifications based on the fingerprint center and taking into account the characteristics of vector area distribution.

[0026] Preferably, the filtering in S6 is achieved by combining a linear filter and a median nonlinear filter.

[0027] Preferably, the S7 first divides the fingerprint image into four regions based on the center, and then defines a central direction using the direction distribution of each region.

[0028] Preferably, the entire area of ​​the S8 fingerprint is divided into 16 directions, and the Pike and 8-direction Mask that appear are removed.

[0029] Preferably, the S10 combines the relative distance, direction difference and type of the Minutia positions for comparison.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. Control the charging pile to start and stop charging through fingerprint;

[0032] 2. First, divide the fingerprint area into several blocks of a certain size, and then use the concentration distribution information of the blocks to extract the fingerprint edge; using the concentration distribution map of a part of the fingerprint area, fingerprint morphology classification refers to the four morphological classifications with 99% recognition features based on the fingerprint center and considering the distribution characteristics of the vector area; it is very effective for fingerprint recognition;

[0033] 3. Nonlinear adaptive filter: removes the black area around the white spot and the isolated area around the black spot to ensure the uniformity of the fingerprint line width; filtering is achieved by combining the linear filter and the median nonlinear filter; it solves the problem of many false feature quantities in the prior art; it also solves the problem of the fingerprint being broken at the connected part;

[0034] 4. Fingerprint recognition algorithm directly determines Minutia based on digital processing value (filtered wave). The characteristic of this method is that it can quickly determine the starting point and end point of the fingerprint line, the feature points that may become bifurcation points, and remove virtual feature points with reference to the direction vector; the above method shortens the entire recognition time;

[0035] 5. The characteristic of the comparison algorithm is to use an evaluation function suitable for rotation at any angle to complete comparison and retrieval through the least calculation, that is, to reasonably combine the relative distance, direction difference and type of the Minutia position for comparison and improve the recognition effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0037] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention.

[0039] See also Figure 1 In an embodiment of the present invention, a fingerprint recognition is used to control the application of starting and stopping charging of a charging pile, and a switch signal is output through a fingerprint module: a fingerprint is recognized once to successfully start charging, and a fingerprint is recognized again to successfully pause, interrupt or end charging;

[0040] Signal recognition before charging pile starts;

[0041] Information query is performed through fingerprints during the charging process;

[0042] Fingerprint recognition can be used to pause, interrupt or end charging.

[0043] Fingerprint recognition includes the following steps:

[0044] S1: Input fingerprint; the image size input from the CCD input module is a black and white image of 256X256PIX (pixels);

[0045] S2: Extracting fingerprint area: First, the fingerprint area is divided into several blocks of a certain size, and then the density distribution information of the blocks is used to extract the fingerprint edge;

[0046] S3: Automatic imaging: using the concentration distribution map of a part of the fingerprint area, implemented by program;

[0047] S4: Digital processing: The image block’s average density information and background density are automatically processed;

[0048] S5: Classification of fingerprint morphology; fingerprint morphology classification refers to the classification of 4 morphologies based on the fingerprint center and considering the characteristics of vector area distribution, which has 99% recognition features; it is very effective based on the feature recognition degree and false recognition rate of fingerprint morphology;

[0049] S6: Nonlinear adaptive filter: removes the black area around the white point and the isolated area around the black point to ensure the uniformity of the fingerprint line amplitude; the filtering is achieved by combining the linear filter and the median nonlinear filter;

[0050] S7: The center direction of the fingerprint. The center direction of the fingerprint is one of the important feature quantities to cope with arbitrary angle rotation. Processing method: First, the fingerprint image is divided into four areas based on the center, and then a center direction is defined using the direction distribution of each area.

[0051] S8: Determine the direction vector of the fingerprint block; the fingerprint block vector plays an auxiliary role in determining the fingerprint center direction and correctly selecting the minutia; processing method: the entire fingerprint area is divided into 16 directions, and the Pike (spike) and 8-direction Mask that appear are removed; based on the block direction vector, it is easier to solve the new method of fingerprint center;

[0052] S9: Determination of feature quantity: Minutia is directly determined based on the digital processing value; the fingerprint recognition algorithm directly determines the Minutia based on the digital processing value (filtered); the characteristics of this method are that it can quickly determine the starting point and end point of the fingerprint line, the feature points that may become the bifurcation point, and remove virtual feature points with reference to the direction vector; shorten the entire recognition time;

[0053] S10: High-speed comparison algorithm; Processing method: The characteristic of the comparison algorithm is to use an evaluation function applicable to rotation at any angle to complete comparison and retrieval through the least calculation, that is, to reasonably combine the relative distance, direction difference and type of the Minutia position for comparison to improve the recognition effect.

[0054] The fingerprint recognition algorithm has distinct characteristics in the method of selecting the feature quantity and the feature quantity that remains unchanged when rotated at any angle: the recognition speed is 0.5s and the feature information of a single finger is 256Bytes; the rejection rate is 0.01% and the false recognition rate is 0.0001%.

[0055] The fingerprint module outputs a switch signal: a successful fingerprint recognition starts charging, and a successful fingerprint recognition again pauses, interrupts or ends charging

[0056] According to the charging action requirements, output the required logic signal:

[0057] 1. Identify the signal before the charging pile is started (notification of successful fingerprint recognition, user information query and other information of the charging pile);

[0058] 2. Information query during charging (such as current battery power, charging voltage, current, electricity price, etc.) is performed through fingerprints;

[0059] 3. Pause, interrupt or end charging through fingerprint recognition.

[0060] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An application of fingerprint recognition to control the start and stop of charging of a charging pile, characterized by: Output switch signal through fingerprint module: successfully recognize fingerprint once to start charging, and successfully recognize fingerprint again to pause, interrupt or end charging; Signal recognition before charging pile starts; Information query is performed through fingerprints during the charging process; Fingerprint recognition can be used to pause, interrupt or end charging.

2. The fingerprint recognition according to claim 1 is used to control the charging pile to start and stop charging, characterized in that: Fingerprint recognition includes the following steps: S1: Input fingerprint; S2: Extracting fingerprint area: First, the fingerprint area is divided into several blocks of a certain size, and then the density distribution information of the blocks is used to extract the fingerprint edge; S3: Automatic imaging: using the concentration distribution map of a part of the fingerprint area; S4: Digital processing: The image block’s average density information and background density are automatically processed; S5: Classification of fingerprint morphology; S6: Nonlinear adaptive filter: removes the black area around the white point and the isolated area around the black point to ensure the uniformity of the fingerprint line width; S7: center direction of fingerprint; S8: determine the fingerprint block direction vector; S9: Determination of feature quantity: Minutia is directly determined based on the digital processing value; S10: High-speed comparison algorithm.

3. The application of fingerprint recognition for controlling the start and stop of charging of a charging pile according to claim 2 is characterized in that: The S1 input fingerprint is a black and white image with an image size of 256X256PIX input from the CCD input module.

4. The fingerprint recognition method according to claim 2 is used to control the start and stop of charging of a charging pile, characterized in that: The S5 fingerprint morphological classification refers to the 4 morphological classifications that take the fingerprint center as the benchmark and consider the vector area distribution characteristics and have 99% of the identification features.

5. The application of fingerprint recognition for controlling the start and stop of charging of a charging pile according to claim 2 is characterized in that: The filtering in S6 is achieved by combining a linear filter and a median nonlinear filter.

6. The fingerprint recognition method according to claim 2 is used to control the start and stop of charging of a charging pile, characterized in that: The S7 first divides the fingerprint image into four regions based on the center, and then defines a central direction using the direction distribution of each region.

7. The fingerprint recognition method according to claim 2 is used to control the start and stop of charging of a charging pile, characterized in that: The entire area of ​​the S8 fingerprint is divided into 16 directions, and the Pike and 8-direction Mask that appear are removed.

8. The fingerprint recognition method according to claim 2 is used to control the start and stop of charging of a charging pile, characterized in that: The S10 combines the relative distance, direction difference and type of the Minutia positions for comparison.

Images