CN103955640A - Identity recognition system based on fuzzy control theory - Google Patents
Identity recognition system based on fuzzy control theory Download PDFInfo
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- CN103955640A CN103955640A CN201410149085.XA CN201410149085A CN103955640A CN 103955640 A CN103955640 A CN 103955640A CN 201410149085 A CN201410149085 A CN 201410149085A CN 103955640 A CN103955640 A CN 103955640A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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Abstract
The invention discloses an identity recognition system based on a fuzzy control theory. The identity recognition system comprises an acquisition unit, a fuzzification unit, a knowledge base, a logic unit and a de-fuzzification unit, wherein the acquisition unit is used for acquiring tested information; the fuzzification unit is used for receiving acquisition information output by the acquisition unit, performing fuzzification treatment on the acquisition information and outputting the information to the logic unit; the knowledge base is used for providing comparable data for logical judgment to the logic unit; the logic unit is used for receiving the data information output by the fuzzification unit, a database unit and a rule base unit, meanwhile performing analytical judgement on the received data information and outputting control signals; the de-fuzzification unit is used for receiving the control signals output by the logic unit, performing de-fuzzification treatment on the control signals and outputting the control signals. Compared with the prior art, the identity recognition system has the following advantages: the fuzzification unit, the knowledge base and the logic unit are adopted, so that fuzzy control can be performed on the acquired information, and the detection efficiency is improved.
Description
Technical field
The present invention relates to a kind of identity recognizing technology, relate in particular to a kind of identification system based on fuzzy control theory.
Background technology
Identity recognizing technology mainly refers to a kind of technology by mankind's biological character for identity authentication, the mankind's biological characteristic conventionally has uniqueness, can measure or can automatically identify and checking, heredity or the feature such as unchangeable, and therefore biometric authentication technology exists larger advantage compared with conventional authentication technology.And along with social development and scientific and technological progress, biological identification technology, particularly identity recognizing technology have obtained application in various occasions, and become a kind of important means of quick examination identity.This technology is associated with some biological properties of human body conventionally, as fingerprint, refer to vein, face, iris etc., under current application conditions, conventionally need to could identify these Human biology features by the perceptive mode of contact or semi-contact, not only need to meet certain distance, illumination, the environmental baselines such as temperature, also need tested personnel to coordinate, keep specific attitude and maintain a period of time, identify for equipment, detection mode is single, and measurand is had relatively high expectations, accuracy in detection is not high, particularly need to realize fast without bothering authentication at some, it is noncontact, in optional situation, this technology cannot obtain desirable effect.
Summary of the invention
The technical problem to be solved in the present invention is, for the above-mentioned defect of prior art, provides the identification system based on fuzzy control theory that a kind of detection speed is fast and accuracy is high.
Based on an identification system for fuzzy control theory, comprise
Collecting unit, has first signal input end, first signal output terminal;
Fuzzier unit, has first signal input end, first signal output terminal;
Knowledge base;
Logical block, has first signal input end, secondary signal input end, the 3rd signal input part, first signal output terminal and secondary signal output terminal;
Defuzzification unit, has first signal input end, first signal output terminal;
The first signal output terminal of described collecting unit connects the first signal input end of described fuzzier unit, and described collecting unit is used for gathering information measured;
The first signal output terminal of described fuzzier unit connects the first signal input end of described logical block; Described fuzzier unit, for receiving the Information Monitoring of described collecting unit output, is done Information Monitoring Fuzzy processing and is delivered to logical block;
Described knowledge base is for providing logic to judge the comparable data of use to logical block, described knowledge base comprises Database Unit and rule base unit, described Database Unit is stored the fuzzy vector value set of standard of collected information, and the output terminal of described Database Unit connects the secondary signal input end of described logical block; The error range vector value set that collected data allow is stored in described rule base unit, and the output terminal of described rule base unit connects described logical block the 3rd signal input part;
The first signal output terminal of described logical block connects described defuzzification unit first signal input end, described logical block is for receiving the data message of described fuzzier unit, described Database Unit, the output of described rule base unit, received data message is done and analyzes judgement simultaneously, and export control signal;
Described defuzzification unit, for receiving the control signal of described logical block output, does defuzzification to control signal and processes and export.
As further preferred version, also comprise topworks, the input end of described execution architecture connects the first signal output terminal of described defuzzification unit, the control signal that described topworks exports for receiving defuzzification unit, and carry out this control signal.
As further preferred version, collecting unit of the present invention is at least one in face recognition module, voiceprint identification module, height identification module.
As further preferred version, the present invention also comprises feedback unit, and the input end of described feedback unit connects the secondary signal output terminal of described logical block, and the signal output part of described feedback unit connects the first signal input end of described collecting unit.
As further preferred version, logical block of the present invention is any one in CPU, single-chip microcomputer, PLC.
As further preferred version, the error range of rule base of the present invention unit is 0～± 5.
beneficial effect:
Compared with prior art, the present invention has the following advantages:
1) adopt fuzzier unit, knowledge base, logical block, can do fuzzy control to the information gathering, reduced the requirement of the distance to measurand, angle, light in measuring process, improved detection efficiency.
2) collecting unit is at least one in face recognition module, voiceprint identification module, height identification module, collection approach is comprehensive, avoided because of face there is scar because of injuring unexpectedly, because of the uncomfortable sound the causing None-identified phenomenon that unexpected factor causes such as change voice, improved the accuracy of detection.
Brief description of the drawings
Fig. 1 is a kind of block scheme of the identification system based on fuzzy control theory.
Embodiment
Below in conjunction with the drawings and specific embodiments, the invention will be further described, but not as limiting to the invention.
As shown in Figure 1, a kind of identification system based on fuzzy control theory, comprises
Collecting unit, has first signal input end, first signal output terminal;
Fuzzier unit, has first signal input end, first signal output terminal;
Knowledge base;
Logical block, has first signal input end, secondary signal input end, the 3rd signal input part, first signal output terminal and secondary signal output terminal;
Defuzzification unit, has first signal input end, first signal output terminal;
The first signal output terminal of described collecting unit connects the first signal input end of described fuzzier unit, and described collecting unit is used for gathering information measured;
The first signal output terminal of described fuzzier unit connects the first signal input end of described logical block; Described fuzzier unit, for receiving the Information Monitoring of described collecting unit output, is done Information Monitoring Fuzzy processing and is delivered to logical block;
Described knowledge base is for providing logic to judge the comparable data of use to logical block, described knowledge base comprises Database Unit and rule base unit, described Database Unit is stored the fuzzy vector value set of standard of collected information, and the output terminal of described Database Unit connects the secondary signal input end of described logical block; The error range vector value set that collected data allow is stored in described rule base unit, and the output terminal of described rule base unit connects described logical block the 3rd signal input part;
The first signal output terminal of described logical block connects described defuzzification unit first signal input end, described logical block is for receiving the data message of described fuzzier unit, described Database Unit, the output of described rule base unit, received data message is done and analyzes judgement simultaneously, and export control signal;
Described defuzzification unit, for receiving the control signal of described logical block output, does defuzzification to control signal and processes and export.
Known by above implementer's formula: collecting unit image data of the present invention, and send data to fuzzier unit, fuzzier unit image data is carried out Fuzzy processing and is transferred to logical block, logical block is according to the information of fuzzier unit transmission, information in conjunction with knowledge base transmission is carried out decision analysis, transfer analysis result to control signal, and control signal is delivered to defuzzification unit does defuzzification processing, the control signal of processing through ambiguity solution words transfers to topworks and carries out, gatherer process keeps specific facial expression without collected object, attitude gets final product image data, logical block is provided with certain error range, Information Monitoring within this error range all can be identified, do not need collected object to carry out information acquisition for the second time, the speed gathering is high, and detection efficiency is high.
As further preferred implementation, the present invention can comprise topworks, the input end of described execution architecture connects the first signal output terminal of described defuzzification unit, the control signal that described topworks exports for receiving defuzzification unit, and carry out this control signal.
As further preferred implementation, collecting unit of the present invention can be at least one in face recognition module, voiceprint identification module, height identification module.Collection approach is comprehensive, avoided because of face there is scar because of injuring unexpectedly, because of the uncomfortable sound the causing None-identified phenomenon that unexpected factor causes such as change voice, improved the accuracy of detection.
As further preferred implementation, the present invention can comprise feedback unit, and the input end of described feedback unit connects the secondary signal output terminal of described logical block, and the signal output part of described feedback unit connects the first signal input end of described collecting unit.Allow certain error for the information gathering, and permissible error wide-ultra has gone out the zone of reasonableness that rule base unit arranges, can carry out for the second time or information acquisition for the third time by feedback unit, avoid the testing result that causes because of the carelessness of collected object inaccurate, the accuracy that has improved testing result.
As further preferred implementation, logical block of the present invention is any one in CPU, single-chip microcomputer, PLC.
As further preferred implementation, the error range of rule base of the present invention unit is 0～± 5.This error range can be adjusted as required voluntarily.
The foregoing is only preferred embodiment of the present invention; not thereby limit embodiments of the present invention and protection domain; to those skilled in the art; the scheme that being equal to of should recognizing that all utilizations instructions of the present invention and diagramatic content done replaces and apparent variation obtains, all should be included in protection scope of the present invention.
Claims (6)
1. the identification system based on fuzzy control theory, is characterized in that: comprise
---collecting unit, has first signal input end, first signal output terminal;
---fuzzier unit, has first signal input end, first signal output terminal;
---knowledge base;
---logical block, has first signal input end, secondary signal input end, the 3rd signal input part, first signal output terminal and secondary signal output terminal;
---defuzzification unit, has first signal input end, first signal output terminal;
The first signal output terminal of described collecting unit connects the first signal input end of described fuzzier unit, and described collecting unit is used for gathering information measured;
The first signal output terminal of described fuzzier unit connects the first signal input end of described logical block; Described fuzzier unit, for receiving the Information Monitoring of described collecting unit output, is done Information Monitoring Fuzzy processing and is delivered to logical block;
Described knowledge base is for providing logic to judge the comparable data of use to logical block, described knowledge base comprises Database Unit and rule base unit, described Database Unit is stored the fuzzy vector value set of standard of collected information, and the output terminal of described Database Unit connects the secondary signal input end of described logical block; The error range vector value set that collected data allow is stored in described rule base unit, and the output terminal of described rule base unit connects described logical block the 3rd signal input part;
The first signal output terminal of described logical block connects described defuzzification unit first signal input end, described logical block is for receiving the data message of described fuzzier unit, described Database Unit, the output of described rule base unit, received data message is done and analyzes judgement simultaneously, and export control signal;
Described defuzzification unit, for receiving the control signal of described logical block output, does defuzzification to control signal and processes and export.
2. a kind of identification system based on fuzzy control theory according to claim 1, it is characterized in that: also comprise topworks, the input end of described execution architecture connects the first signal output terminal of described defuzzification unit, the control signal that described topworks exports for receiving defuzzification unit, and carry out this control signal.
3. a kind of identification system based on fuzzy control theory according to claim 1, is characterized in that: described collecting unit is at least one in face recognition module, voiceprint identification module, height identification module.
4. a kind of identification system based on fuzzy control theory according to claim 3, it is characterized in that: also comprise feedback unit, the input end of described feedback unit connects the secondary signal output terminal of described logical block, and the signal output part of described feedback unit connects the first signal input end of described collecting unit.
5. a kind of identification system based on fuzzy control theory according to claim 1, is characterized in that: described logical block is any one in CPU, single-chip microcomputer, PLC.
6. a kind of identification system based on fuzzy control theory according to claim 1, is characterized in that: the error range of described rule base unit is 0～± 5.
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| CN201410149085.XA CN103955640B (en) | 2014-04-14 | 2014-04-14 | Identity recognition system based on fuzzy control theory |
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| CN201410149085.XA CN103955640B (en) | 2014-04-14 | 2014-04-14 | Identity recognition system based on fuzzy control theory |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107423606A (en) * | 2017-08-01 | 2017-12-01 | 黄河科技学院 | A kind of identification system based on fuzzy control theory |
| CN111047757A (en) * | 2019-10-23 | 2020-04-21 | 中交武汉港湾工程设计研究院有限公司 | Guide service system and guide service method based on entrance face recognition |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080133433A1 (en) * | 2006-11-30 | 2008-06-05 | Maryam Khanbaghi | Fuzzy logic control for process with large dead time |
| CN203350635U (en) * | 2013-06-09 | 2013-12-18 | 苏州经贸职业技术学院 | Dynamic fuzzy control system |
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- 2014-04-14 CN CN201410149085.XA patent/CN103955640B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080133433A1 (en) * | 2006-11-30 | 2008-06-05 | Maryam Khanbaghi | Fuzzy logic control for process with large dead time |
| CN203350635U (en) * | 2013-06-09 | 2013-12-18 | 苏州经贸职业技术学院 | Dynamic fuzzy control system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107423606A (en) * | 2017-08-01 | 2017-12-01 | 黄河科技学院 | A kind of identification system based on fuzzy control theory |
| CN111047757A (en) * | 2019-10-23 | 2020-04-21 | 中交武汉港湾工程设计研究院有限公司 | Guide service system and guide service method based on entrance face recognition |
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| CN103955640B (en) | 2017-02-15 |
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