CN110858292A - Subway card swiping method based on footstep triggering - Google Patents
Subway card swiping method based on footstep triggering Download PDFInfo
- Publication number
- CN110858292A CN110858292A CN201810976842.9A CN201810976842A CN110858292A CN 110858292 A CN110858292 A CN 110858292A CN 201810976842 A CN201810976842 A CN 201810976842A CN 110858292 A CN110858292 A CN 110858292A
- Authority
- CN
- China
- Prior art keywords
- image
- equipment
- filtering
- fingerprint
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
- G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
- G07B15/04—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems comprising devices to free a barrier, turnstile, or the like
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Business, Economics & Management (AREA)
- Finance (AREA)
- Image Input (AREA)
- Image Processing (AREA)
- Collating Specific Patterns (AREA)
Abstract
The invention relates to a subway card swiping method based on footstep triggering, which comprises the following steps of swiping a card by using a subway card swiping system based on footstep triggering, wherein the subway card swiping system based on footstep triggering comprises the following steps: the sound detection equipment is arranged at the subway entrance and used for detecting a sound signal at the subway entrance to be output as a field sound signal; the step analysis equipment is connected with the sound detection equipment, arranged at an entrance of a subway and used for receiving the field sound signal, analyzing the amplitude of a step component in the field sound signal and sending a scanning trigger signal when the amplitude of the step component in the field sound signal exceeds the limit; and the fingerprint identification equipment is arranged on a detection platform at the subway entrance and used for exiting from a power saving mode when receiving the scanning trigger signal, capturing the field data of the fingerprint on the detection platform to obtain a corresponding field fingerprint image and outputting the field fingerprint image.
Description
Technical Field
The invention relates to the field of characteristic analysis, in particular to a subway card swiping method based on footstep triggering.
Background
The development of fingerprint detection technology benefits from the research of modern electronic integrated manufacturing technology and fast and reliable algorithms. Although fingerprints are only a small portion of human skin, the amount of data used for identification is quite large, and comparing such data is not a simple equality or inequality problem, but rather uses a fuzzy matching algorithm that requires a large number of operations. Modern electronic integrated manufacturing technology enables the manufacture of rather small fingerprint image reading equipment, and the rapidly developed personal computer operation speed provides the possibility of performing comparison operation of two fingerprints on a microcomputer or even a single chip microcomputer.
In addition, the reliability of the matching algorithm is continuously improved, and the fingerprint identification technology is very practical.
Disclosure of Invention
In order to solve the technical problem that the subway card swiping intelligence level is not high, the invention provides a subway card swiping method based on footstep triggering, fingerprint features are extracted from an image, pass card numbers corresponding to the extracted fingerprint features are determined, account marking is carried out on corresponding pass cards based on the pass card numbers, so that the speed and the efficiency of subway charging are improved, more importantly, in image processing, amplitude analysis is carried out on various noises in the image, noise types with amplitudes exceeding a limited amount are used as main noise types, the number of main noise types in the image is determined, image quality grades corresponding to the main noise types in the image are mapped based on the number of the main noise types in the image, a fingerprint feature extraction mode is adopted when the image quality grades are high, and therefore unnecessary waste of operation resources is avoided; meanwhile, by utilizing the characteristic that the more the image edge information is, the more complex the image is, when the image edge information is more, the more accurate self-adaptive filtering equipment is selected for filtering processing, and when the image edge information is less, the WIENER filtering equipment with higher selective price ratio is selected for filtering processing.
According to an aspect of the invention, a subway card swiping method based on step triggering is provided, the method comprises the following steps of swiping the card by using a subway card swiping system based on step triggering, wherein the subway card swiping system based on step triggering comprises: the sound detection equipment is arranged at the subway entrance and used for detecting a sound signal at the subway entrance to be output as a field sound signal; the step analysis equipment is connected with the sound detection equipment, arranged at an entrance of a subway and used for receiving the field sound signal, analyzing the amplitude of a step component in the field sound signal and sending a scanning trigger signal when the amplitude of the step component in the field sound signal exceeds the limit; the fingerprint identification device is arranged on a detection platform at the subway entrance and used for exiting a power-saving mode when receiving the scanning trigger signal, capturing the field data of the fingerprint on the detection platform to obtain a corresponding field fingerprint image and outputting the field fingerprint image; the main noise extraction equipment is connected with the fingerprint identification equipment, is positioned near the fingerprint identification equipment, and is used for receiving the field fingerprint image, analyzing the amplitude of various types of noise in the field fingerprint image, determining the number of main noise types in the field fingerprint image by taking the noise type with the amplitude exceeding a limited amount as the main noise type, and mapping the corresponding image quality grade based on the number of the main noise types in the field fingerprint image; the target recovery device is respectively connected with the fingerprint identification device and the main noise extraction device and is used for carrying out target edge extension on each target adjacent to the image edge in the field fingerprint image when the image quality level is higher than a preset level threshold value so as to obtain an edge extension image corresponding to the field fingerprint image; the shape sharpening device is connected with the target recovery device and is used for acquiring each target shape in the edge extension image, and sharpening each target shape in the edge extension image to obtain and output a shape sharpened image corresponding to the edge extension image; the information detection device is connected with the appearance sharpening device and is used for receiving the appearance sharpened image, detecting whether each pixel point in the appearance sharpened image is an edge pixel point or not, and outputting the number of all pixel points of the appearance sharpened image and the number of all edge pixel points of the appearance sharpened image; the information analysis equipment is connected with the information detection equipment and used for receiving the number of all pixel points of the shape sharpened image and the number of all edge pixel points of the shape sharpened image and dividing the number of all pixel points of the shape sharpened image by the number of all edge pixel points of the shape sharpened image to obtain an edge reference multiple; the filtering switching equipment is connected with the information analysis equipment and used for receiving the edge reference multiple, sending a first filtering switching signal when the edge reference multiple exceeds a limit amount, and sending a second filtering switching signal when the edge reference multiple does not exceed the limit amount; the WIENER filtering device is respectively connected with the filtering switching device and the information detection device, and is used for entering a working state from a power saving state when receiving the second filtering switching signal, and executing the following operations in the working state: performing wavelet-domain WIENER filtering processing on the outline-sharpened image to obtain a corresponding filtered image to be output as a first filtered image; the self-adaptive filtering equipment is respectively connected with the filtering switching equipment and the information detection equipment, and is used for entering a working state from a power-saving state when the first filtering switching signal is received, and executing the following operations in the working state: performing wavelet segmentation on the outline sharpened image to obtain high-frequency coefficients from a first layer to a P layer and low-frequency coefficients from the P layer, setting the high-frequency coefficients with values lower than a preset threshold value to be zero, setting the high-frequency coefficients with values not lower than the preset threshold value to be one third of the original values, and reconstructing the image based on the low-frequency coefficients from the P layer and the processed high-frequency coefficients from the first layer to the P layer to obtain a filtered image corresponding to the outline sharpened image to be output as a second filtered image; the signal integration equipment is respectively connected with the WIENER filtering equipment and the self-adaptive filtering equipment and is used for taking the first filtering image or the second filtering image as a signal integration image and outputting the signal integration image; the power supply equipment is respectively connected with the WIENER filtering equipment and the adaptive filtering equipment and is used for supplying power to the WIENER filtering equipment and the adaptive filtering equipment; the dynamic range detection device is arranged at the subway entrance, is connected with the signal integration device and is used for receiving the signal integration image and detecting the current dynamic range of the signal integration image so as to obtain the current dynamic range; a dynamic range adjusting device connected to the dynamic range detecting device, configured to receive the signal integration image and the current dynamic range, and perform dynamic range adjustment on the signal integration image based on the current dynamic range, so that the dynamic range of the signal integration image is expanded to a preset dynamic range interval, and the dynamic range adjusting device outputs an adjusted range correction image; the number analyzing device is connected with the dynamic range adjusting device and used for receiving the range correction image, extracting fingerprint characteristics from the range correction image, determining a pass card number corresponding to the extracted fingerprint characteristics, and performing a billing action on the corresponding pass card based on the pass card number; when the image quality grade is less than or equal to a preset grade threshold value, the target recovery equipment enters a power saving mode; in the target recovery device, performing target edge extension on each target adjacent to an image edge in the live fingerprint image includes: and taking each target adjacent to the edge of the image in the live fingerprint image as a corresponding incomplete target, and performing predictive extension on the part of the incomplete target outside the live fingerprint image based on the appearance of the incomplete target in the live fingerprint image.
More specifically, in the subway card swiping system based on footstep triggering: the power consumption of the WIENER filtering equipment is different between the power saving state and the working state, and the power consumption of the adaptive filtering equipment is different between the power saving state and the working state.
More specifically, in the subway card swiping system based on footstep triggering: and the WIENER filtering equipment enters a power saving state from an operating state when receiving the first filtering switching signal.
More specifically, in the subway card swiping system based on footstep triggering: and when the WIENER filtering equipment enters a power saving state, stopping performing the WIENER filtering processing of a wavelet domain on the outline sharpened image, and directly outputting the outline sharpened image as a first filtered image.
More specifically, in the subway card swiping system based on footstep triggering: and the self-adaptive filtering equipment enters a power-saving state from a working state when receiving the second filtering switching signal.
More specifically, in the subway card swiping system based on footstep triggering: and when the self-adaptive filtering equipment enters a power-saving state, stopping performing wavelet segmentation on the shape sharpened image, and directly outputting the shape sharpened image as a second filtering image.
More specifically, in the subway card swiping system based on footstep triggering: the area of the edge extension image output by the target recovery device is larger than that of the field fingerprint image.
More specifically, in the subway card swiping system based on footstep triggering: in the dominant noise extraction apparatus, the smaller the number of dominant noise types in the live fingerprint image, the higher the corresponding image quality level.
More specifically, in the subway card swiping system based on footstep triggering:
the step analysis equipment is also used for sending out a scanning stop signal when the amplitude of the step component in the field sound signal is not over-limit; the fingerprint identification device is further used for entering a power saving mode when the scanning stop signal is received.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a configuration diagram of a subway card swiping system based on footstep triggering according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Fingerprint detection refers to the identification by comparing minutiae of different fingerprints.
Fingerprint detection technology relates to a plurality of subjects such as image processing, pattern recognition, computer vision, mathematical morphology, wavelet analysis and the like. The fingerprints of each person are different, namely the fingerprints are obviously different among the ten fingers of the same person, so that the fingerprints can be used for identity authentication. Because the directions of each time of stamping are not completely the same, different force points can bring different degrees of deformation, a large number of fuzzy fingerprints exist, and the key of the fingerprint identification technology is how to correctly extract the characteristics and realize correct matching.
In order to overcome the defects, the invention provides a subway card swiping method based on footstep triggering. The subway card swiping system based on footstep triggering can effectively solve the corresponding technical problem.
Fig. 1 is a configuration diagram of a subway card swiping system based on footstep triggering according to an embodiment of the present invention, the system comprising:
the sound detection equipment is arranged at the subway entrance and used for detecting a sound signal at the subway entrance to be output as a field sound signal;
the step analysis equipment is connected with the sound detection equipment, arranged at an entrance of a subway and used for receiving the field sound signal, analyzing the amplitude of a step component in the field sound signal and sending a scanning trigger signal when the amplitude of the step component in the field sound signal exceeds the limit;
the middle of the detection table mounting plate 1 is provided with two round holes for mounting the detection table, and the lower end of the detection table mounting plate is connected with the upper end of fingerprint identification equipment;
the fingerprint identification device 2 is arranged on a detection table at the subway entrance and used for exiting a power-saving mode when receiving the scanning trigger signal, capturing the field data of the fingerprint on the detection table to obtain a corresponding field fingerprint image and outputting the field fingerprint image;
the main noise extraction equipment is connected with the fingerprint identification equipment, is positioned near the fingerprint identification equipment, and is used for receiving the field fingerprint image, analyzing the amplitude of various types of noise in the field fingerprint image, determining the number of main noise types in the field fingerprint image by taking the noise type with the amplitude exceeding a limited amount as the main noise type, and mapping the corresponding image quality grade based on the number of the main noise types in the field fingerprint image;
the target recovery device is respectively connected with the fingerprint identification device and the main noise extraction device and is used for carrying out target edge extension on each target adjacent to the image edge in the field fingerprint image when the image quality level is higher than a preset level threshold value so as to obtain an edge extension image corresponding to the field fingerprint image;
the shape sharpening device is connected with the target recovery device and is used for acquiring each target shape in the edge extension image, and sharpening each target shape in the edge extension image to obtain and output a shape sharpened image corresponding to the edge extension image;
the information detection device is connected with the appearance sharpening device and is used for receiving the appearance sharpened image, detecting whether each pixel point in the appearance sharpened image is an edge pixel point or not, and outputting the number of all pixel points of the appearance sharpened image and the number of all edge pixel points of the appearance sharpened image;
the information analysis equipment is connected with the information detection equipment and used for receiving the number of all pixel points of the shape sharpened image and the number of all edge pixel points of the shape sharpened image and dividing the number of all pixel points of the shape sharpened image by the number of all edge pixel points of the shape sharpened image to obtain an edge reference multiple;
the filtering switching equipment is connected with the information analysis equipment and used for receiving the edge reference multiple, sending a first filtering switching signal when the edge reference multiple exceeds a limit amount, and sending a second filtering switching signal when the edge reference multiple does not exceed the limit amount;
the WIENER filtering device is respectively connected with the filtering switching device and the information detection device, and is used for entering a working state from a power saving state when receiving the second filtering switching signal, and executing the following operations in the working state: performing wavelet-domain WIENER filtering processing on the outline-sharpened image to obtain a corresponding filtered image to be output as a first filtered image;
the self-adaptive filtering equipment is respectively connected with the filtering switching equipment and the information detection equipment, and is used for entering a working state from a power-saving state when the first filtering switching signal is received, and executing the following operations in the working state: performing wavelet segmentation on the outline sharpened image to obtain high-frequency coefficients from a first layer to a P layer and low-frequency coefficients from the P layer, setting the high-frequency coefficients with values lower than a preset threshold value to be zero, setting the high-frequency coefficients with values not lower than the preset threshold value to be one third of the original values, and reconstructing the image based on the low-frequency coefficients from the P layer and the processed high-frequency coefficients from the first layer to the P layer to obtain a filtered image corresponding to the outline sharpened image to be output as a second filtered image;
the signal integration equipment is respectively connected with the WIENER filtering equipment and the self-adaptive filtering equipment and is used for taking the first filtering image or the second filtering image as a signal integration image and outputting the signal integration image;
the power supply equipment is respectively connected with the WIENER filtering equipment and the adaptive filtering equipment and is used for supplying power to the WIENER filtering equipment and the adaptive filtering equipment;
the dynamic range detection device is arranged at the subway entrance, is connected with the signal integration device and is used for receiving the signal integration image and detecting the current dynamic range of the signal integration image so as to obtain the current dynamic range;
a dynamic range adjusting device connected to the dynamic range detecting device, configured to receive the signal integration image and the current dynamic range, and perform dynamic range adjustment on the signal integration image based on the current dynamic range, so that the dynamic range of the signal integration image is expanded to a preset dynamic range interval, and the dynamic range adjusting device outputs an adjusted range correction image;
the number analyzing device is connected with the dynamic range adjusting device and used for receiving the range correction image, extracting fingerprint characteristics from the range correction image, determining a pass card number corresponding to the extracted fingerprint characteristics, and performing a billing action on the corresponding pass card based on the pass card number;
when the image quality grade is less than or equal to a preset grade threshold value, the target recovery equipment enters a power saving mode;
in the target recovery device, performing target edge extension on each target adjacent to an image edge in the live fingerprint image includes: and taking each target adjacent to the edge of the image in the live fingerprint image as a corresponding incomplete target, and performing predictive extension on the part of the incomplete target outside the live fingerprint image based on the appearance of the incomplete target in the live fingerprint image.
Next, the detailed structure of the subway card swiping system based on step triggering according to the invention will be further described.
In the subway card swiping system based on footstep triggering: the power consumption of the WIENER filtering equipment is different between the power saving state and the working state, and the power consumption of the adaptive filtering equipment is different between the power saving state and the working state.
In the subway card swiping system based on footstep triggering: and the WIENER filtering equipment enters a power saving state from an operating state when receiving the first filtering switching signal.
In the subway card swiping system based on footstep triggering: and when the WIENER filtering equipment enters a power saving state, stopping performing the WIENER filtering processing of a wavelet domain on the outline sharpened image, and directly outputting the outline sharpened image as a first filtered image.
In the subway card swiping system based on footstep triggering: and the self-adaptive filtering equipment enters a power-saving state from a working state when receiving the second filtering switching signal.
In the subway card swiping system based on footstep triggering: and when the self-adaptive filtering equipment enters a power-saving state, stopping performing wavelet segmentation on the shape sharpened image, and directly outputting the shape sharpened image as a second filtering image.
In the subway card swiping system based on footstep triggering: the area of the edge extension image output by the target recovery device is larger than that of the field fingerprint image.
In the subway card swiping system based on footstep triggering: in the dominant noise extraction apparatus, the smaller the number of dominant noise types in the live fingerprint image, the higher the corresponding image quality level.
In the subway card swiping system based on footstep triggering:
the step analysis equipment is also used for sending out a scanning stop signal when the amplitude of the step component in the field sound signal is not over-limit;
the fingerprint identification device is further used for entering a power saving mode when the scanning stop signal is received.
In addition, the number resolution device is implemented by a PLD device. A programmable logic device pld (programmable logic device) is an important branch of an ASIC, and is a semi-custom circuit produced by a manufacturer as a general-purpose device, and a user can program the device to implement a desired function. Programmable logic array PLA (programmable logic array), and appeared in the middle of the 70's of the 20 th century, consists of a programmable AND array and a programmable OR array. Programmable Array Logic (PAL) devices, which were introduced first by MMI corporation of the United states in 1977, have become popular because of their flexible design and wide variety of output structures.
The basic structure of a PAL device feeds a programmable and array output product term to an or array, and the logic expression implemented by the PAL device has the form of a sum of products, and thus can describe any boolean transfer function. PAL devices are built internally of five basic types: (1) a basic array structure; (2) a programmable I/O structure; (3) a register output structure with feedback; (4) an exclusive or structure: (5) an arithmetic functional structure.
The subway card swiping system based on footstep triggering is adopted, and aiming at the technical problem that the subway card swiping mechanism principle in the prior art is too lagged, the fingerprint features are extracted from the image, the pass card number corresponding to the extracted fingerprint features is determined, the corresponding pass card is subjected to the account marking action based on the pass card number, so that the speed and the efficiency of subway charging are improved, more importantly, in the image processing, the amplitude analysis is carried out on various noises in the image, the noise types with the amplitude exceeding the limited quantity are used as main noise types, the number of main noise types in the image is determined, the corresponding image quality grade is mapped based on the number of the main noise types in the image, and the fingerprint feature extraction mode is adopted when the image quality grade is higher, so that the waste of unnecessary operation resources is avoided; meanwhile, by utilizing the characteristic that the more the image edge information is, the more the image is complex, when the image edge information is more, the more accurate self-adaptive filtering equipment is selected for filtering processing, and when the image edge information is less, the WIENER filtering equipment with higher selective price ratio is selected for filtering processing, so that the technical problem is solved.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (9)
1. A subway card swiping method based on footstep triggering, which comprises the step of swiping a card by using a subway card swiping system based on footstep triggering, and is characterized in that the subway card swiping system based on footstep triggering comprises:
the sound detection equipment is arranged at the subway entrance and used for detecting a sound signal at the subway entrance to be output as a field sound signal;
the step analysis equipment is connected with the sound detection equipment, arranged at an entrance of a subway and used for receiving the field sound signal, analyzing the amplitude of a step component in the field sound signal and sending a scanning trigger signal when the amplitude of the step component in the field sound signal exceeds the limit;
the fingerprint identification device is arranged on a detection platform at the subway entrance and used for exiting a power-saving mode when receiving the scanning trigger signal, capturing the field data of the fingerprint on the detection platform to obtain a corresponding field fingerprint image and outputting the field fingerprint image;
the main noise extraction equipment is connected with the fingerprint identification equipment, is positioned near the fingerprint identification equipment, and is used for receiving the field fingerprint image, analyzing the amplitude of various types of noise in the field fingerprint image, determining the number of main noise types in the field fingerprint image by taking the noise type with the amplitude exceeding a limited amount as the main noise type, and mapping the corresponding image quality grade based on the number of the main noise types in the field fingerprint image;
the target recovery device is respectively connected with the fingerprint identification device and the main noise extraction device and is used for carrying out target edge extension on each target adjacent to the image edge in the field fingerprint image when the image quality level is higher than a preset level threshold value so as to obtain an edge extension image corresponding to the field fingerprint image;
the shape sharpening device is connected with the target recovery device and is used for acquiring each target shape in the edge extension image, and sharpening each target shape in the edge extension image to obtain and output a shape sharpened image corresponding to the edge extension image;
the information detection device is connected with the appearance sharpening device and is used for receiving the appearance sharpened image, detecting whether each pixel point in the appearance sharpened image is an edge pixel point or not, and outputting the number of all pixel points of the appearance sharpened image and the number of all edge pixel points of the appearance sharpened image;
the information analysis equipment is connected with the information detection equipment and used for receiving the number of all pixel points of the shape sharpened image and the number of all edge pixel points of the shape sharpened image and dividing the number of all pixel points of the shape sharpened image by the number of all edge pixel points of the shape sharpened image to obtain an edge reference multiple;
the filtering switching equipment is connected with the information analysis equipment and used for receiving the edge reference multiple, sending a first filtering switching signal when the edge reference multiple exceeds a limit amount, and sending a second filtering switching signal when the edge reference multiple does not exceed the limit amount;
the WIENER filtering device is respectively connected with the filtering switching device and the information detection device, and is used for entering a working state from a power saving state when receiving the second filtering switching signal, and executing the following operations in the working state: performing wavelet-domain WIENER filtering processing on the outline-sharpened image to obtain a corresponding filtered image to be output as a first filtered image;
the self-adaptive filtering equipment is respectively connected with the filtering switching equipment and the information detection equipment, and is used for entering a working state from a power-saving state when the first filtering switching signal is received, and executing the following operations in the working state: performing wavelet segmentation on the outline sharpened image to obtain high-frequency coefficients from a first layer to a P layer and low-frequency coefficients from the P layer, setting the high-frequency coefficients with values lower than a preset threshold value to be zero, setting the high-frequency coefficients with values not lower than the preset threshold value to be one third of the original values, and reconstructing the image based on the low-frequency coefficients from the P layer and the processed high-frequency coefficients from the first layer to the P layer to obtain a filtered image corresponding to the outline sharpened image to be output as a second filtered image;
the signal integration equipment is respectively connected with the WIENER filtering equipment and the self-adaptive filtering equipment and is used for taking the first filtering image or the second filtering image as a signal integration image and outputting the signal integration image;
the power supply equipment is respectively connected with the WIENER filtering equipment and the adaptive filtering equipment and is used for supplying power to the WIENER filtering equipment and the adaptive filtering equipment;
the dynamic range detection device is arranged at the subway entrance, is connected with the signal integration device and is used for receiving the signal integration image and detecting the current dynamic range of the signal integration image so as to obtain the current dynamic range;
a dynamic range adjusting device connected to the dynamic range detecting device, configured to receive the signal integration image and the current dynamic range, and perform dynamic range adjustment on the signal integration image based on the current dynamic range, so that the dynamic range of the signal integration image is expanded to a preset dynamic range interval, and the dynamic range adjusting device outputs an adjusted range correction image;
the number analyzing device is connected with the dynamic range adjusting device and used for receiving the range correction image, extracting fingerprint characteristics from the range correction image, determining a pass card number corresponding to the extracted fingerprint characteristics, and performing a billing action on the corresponding pass card based on the pass card number;
when the image quality grade is less than or equal to a preset grade threshold value, the target recovery equipment enters a power saving mode;
in the target recovery device, performing target edge extension on each target adjacent to an image edge in the live fingerprint image includes: and taking each target adjacent to the edge of the image in the live fingerprint image as a corresponding incomplete target, and performing predictive extension on the part of the incomplete target outside the live fingerprint image based on the appearance of the incomplete target in the live fingerprint image.
2. The method of claim 1, wherein:
the power consumption of the WIENER filtering equipment is different between the power saving state and the working state, and the power consumption of the adaptive filtering equipment is different between the power saving state and the working state.
3. The method of claim 2, wherein:
and the WIENER filtering equipment enters a power saving state from an operating state when receiving the first filtering switching signal.
4. The method of claim 3, wherein:
and when the WIENER filtering equipment enters a power saving state, stopping performing the WIENER filtering processing of a wavelet domain on the outline sharpened image, and directly outputting the outline sharpened image as a first filtered image.
5. The method of claim 4, wherein:
and the self-adaptive filtering equipment enters a power-saving state from a working state when receiving the second filtering switching signal.
6. The method of claim 5, wherein:
and when the self-adaptive filtering equipment enters a power-saving state, stopping performing wavelet segmentation on the shape sharpened image, and directly outputting the shape sharpened image as a second filtering image.
7. The method of claim 6, wherein:
the area of the edge extension image output by the target recovery device is larger than that of the field fingerprint image.
8. The method of claim 7, wherein:
in the dominant noise extraction apparatus, the smaller the number of dominant noise types in the live fingerprint image, the higher the corresponding image quality level.
9. The method of any of claims 1-8, wherein:
the step analysis equipment is also used for sending out a scanning stop signal when the amplitude of the step component in the field sound signal is not over-limit;
the fingerprint identification device is further used for entering a power saving mode when the scanning stop signal is received.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810976842.9A CN110858292A (en) | 2018-08-26 | 2018-08-26 | Subway card swiping method based on footstep triggering |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810976842.9A CN110858292A (en) | 2018-08-26 | 2018-08-26 | Subway card swiping method based on footstep triggering |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110858292A true CN110858292A (en) | 2020-03-03 |
Family
ID=69635808
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810976842.9A Withdrawn CN110858292A (en) | 2018-08-26 | 2018-08-26 | Subway card swiping method based on footstep triggering |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110858292A (en) |
-
2018
- 2018-08-26 CN CN201810976842.9A patent/CN110858292A/en not_active Withdrawn
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Jain et al. | Fingerprint matching using minutiae and texture features | |
| Jiang et al. | Detecting the fingerprint minutiae by adaptive tracing the gray-level ridge | |
| Ryu et al. | Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance | |
| Bansal et al. | Effective morphological extraction of true fingerprint minutiae based on the hit or miss transform | |
| Liu et al. | Palm-line detection | |
| Pakutharivu et al. | A comprehensive survey on fingerprint recognition systems | |
| Chaudhari et al. | A study and review on fingerprint image enhancement and minutiae extraction | |
| Sharma | Fingerprint biometric system: a survey | |
| CN110858292A (en) | Subway card swiping method based on footstep triggering | |
| Moganeshwaran et al. | Fingerprint-fingervein multimodal biometric authentication system in field programmable gate array | |
| Kankrale et al. | Template level concatenation of iris and fingerprint in multimodal biometric identification systems | |
| Rajbhoj et al. | An Improved binarization based algorithm using minutiae approach for Fingerprint Identification | |
| William et al. | Finger Vein verification using local histogram of hybrid texture descriptors | |
| Kashyap et al. | Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach | |
| De Zhi et al. | FingerCode for identity verification using fingerprint and smart card | |
| Yu et al. | Fingerprint image preprocessing based on whole-hand image captured by digital camera | |
| Stephen et al. | Removal of false minutiae with fuzzy rules from the extracted minutiae of fingerprint image | |
| Shekhar et al. | Robust approach for palm (Roi) extraction in palmprint recognition system | |
| Marcialis et al. | Multimodal fingerprint verification by score-level fusion: An experimental investigation | |
| Kanchana et al. | Robust approach for palm (Roi) extraction in palmprint recognition system | |
| Ezhilmaran et al. | Finger vein biometric system with type-2 fuzzy enhancement and minutiae matching | |
| Wang et al. | An improved square-based palmprint segmentation method | |
| Gunasekaran et al. | Implementation of multimodal biometric authentication using soft computing techniques | |
| Ibrahim et al. | Evaluation on palm-print ROI selection techniques for smart phone based touch-less biometric system | |
| Popović et al. | Fingerprint minutiae filtering based on multiscale directional information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20200303 |