CN104537806A - Camera based real-time driving fatigue detection system - Google Patents
Camera based real-time driving fatigue detection system Download PDFInfo
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- CN104537806A CN104537806A CN201410630621.8A CN201410630621A CN104537806A CN 104537806 A CN104537806 A CN 104537806A CN 201410630621 A CN201410630621 A CN 201410630621A CN 104537806 A CN104537806 A CN 104537806A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
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Abstract
A camera based real-time fatigue detection system comprises a video image collection module, an image data storage module, a video image processing module and an alarm device. A camera of the video image collection module collects video images of a driver in the cab in real time, the video images are stored in the image data storage module, the video image processing module extract a driver fatigue evaluation parameter and a driver fatigue state identification standard from the video images in certain algorithm, different levels of fatigue results output by the detection system are determined, and the alarm device is controlled to emit corresponding alarm information. The detection system can be mounted in the automobile cab, advantages of the image detection method are fully played, interference in a monitored driver is little, the accuracy is higher, the anti-interference capability is high, the fatigue state of the driver can be detected before a key error is made, the requirement for instantaneity can be satisfied, and different level of alarm information can be emitted according to the quantified fatigue degrees.
Description
Technical field
The present invention relates to automotive safety to control, particularly relate to a kind of real-time detection system of fatigue driving based on camera.
Background technology
Vigilance and the safe driving ability of driver can decline along with the fatigue of driver, are necessary to detect in real time the fatigue state of driver, and real-time early warning, effectively to reduce the traffic hazard caused by driver tired driving.The existing method utilizing the physiological characteristics such as such as electroencephalogram, electroculogram, electromyogram, respiratory air flow and effect of breathing when detecting driver fatigue to monitor the fatigue state of driver, measurement result is more accurate, but cannot install and measure instrument in pilothouse, its measurement result can only be advanced or delayed.In addition, the method for monitoring the fatigue state of driver by detecting the driving behavior of driver is also difficult to detect before driver makes timely error and the fatigue state of driver can not meets the requirement of real-time.
Summary of the invention
Technical matters to be solved by this invention is the defect making up above-mentioned prior art, provides a kind of real-time detection system of fatigue driving based on camera.
Technical matters of the present invention is solved by the following technical programs.
This real-time detection system of fatigue driving based on camera, is mounted in the online real time image processing system of car steering indoor.
The feature of this real-time detection system of fatigue driving based on camera is:
Described real time image processing system comprises video image acquisition module, view data memory module, Computer Vision module, and warning device, the video image of the driver in pilothouse is gathered in real time by the camera of described video image acquisition module, be stored in described view data memory module, and by the driver fatigue evaluating in described Computer Vision module use algorithm extraction video image and driver fatigue state criterion of identification, judge the different brackets of the fatigue results that detection system exports, control described warning device again and send corresponding warning message.
Technical matters of the present invention is solved by following further technical scheme.
Described image capture module is by comprising complementary metal oxide semiconductor (CMOS) (Complementary Metal Oxide Semiconductor, initialism is CMOS) camera of image sensor chip and field programmable gate array (Field Programmable Gate Array, initialism is FPGA) composition, described cmos image sensor built-in chip type sensor array, analog/digital (Analog/Digital, initialism is A/D) converter and correlated double sampling circuit, the vedio data of the driver in described cmos image sensor chip Real-time Collection pilothouse, export the video interface of view data to FPGA of pattra leaves erg formula, respective digital of decoding again stream obtains view data, be automatically transferred in the storer of described video image memory module and store, red (R) wherein, green (G), blue (B) three color component RGB are adjusted by digital gain, feed back to described image processing module and carry out colors countenance or compression, described image capture module completes image data acquiring under FPGA controls, the pre-service of view data, rim detection, template area is mated, and carry out communication with described image processing module.
Described image processing module comprises STM32F417 microprocessor, complete data receiver simultaneously, state recognition and early warning, requirement of real time, described STM32F417 microprocessor is 32 digit flash memory microcontrollers based on ARM Cortex-M4 kernel, inner integrated DSP and FPU instruction, possess high performance signal transacting and floating-point operation ability, the also Flash of integrated 1 MB and the SRAM of 196 KB, the view data in the storer of described video image memory module is read by access, image is mated and arithmetic analysis, determine whether driver is in fatigue state, and parse the quantized value of driver's fatigue degree, by the data stream of correspondence by bus transfer extremely described warning device, described warning device selects different type of alarms according to corresponding data message.
Described video image memory module comprises storer, stores the signal digital after by video decode, A/D conversion and flows through the decoded image information of described image capture module, provide described image processing module to call simultaneously.
Described warning device comprises audible alarm circuit and hummer, controlled by Computer Vision module, the different fatigue degree quantized value of the driver exported with described image processing module carries out mating reports to the police, different sound is sent with different frequencies by hummer, when driver is in slight fatigue driving state, hummer sends short and rapid beep sound, provides warning to driver; When during driver is in, sever fatigue driving condition time, hummer sends continuous print roar, the rest until driver is stopped.
Technical matters of the present invention is solved by the following technical programs more further.
Noise in the picture signal that FPGA in described image capture module adopt Gaussian smoothing filter algorithm effectively to remove simulating signal that described camera exports obtains through decoded respective digital stream; and smoothed image signal; improve the quality of picture signal; the edge of available protecting picture signal and details; to be directly used in image recognition and detection, avoid illumination variation to restrict the performance of real-time detection system of fatigue driving simultaneously.
FPGA in described image capture module carries out rim detection to image, adopt the edge detection operator of topography's differential technology to carry out rim detection to image, to find the information about shape and reflection or transmittance in image, improve the precision of real-time detection system of fatigue driving further.
STM32F417 microprocessor in described image processing module mates image, will change insensitive information as matching characteristic to gradation of image entirety, to improve the real-time of about real-time detection system of fatigue driving, the described texture insensitive information of gradation of image entirety change being comprised to the unique point of image, the edge of image and image.
STM32F417 microprocessor in described image processing module carries out arithmetic analysis to image, adopt the relevant tired information of fuzzy neural network algorithm extraction to organically blend into an entirety to carry out fatigue detecting, to strengthen the robustness of real-time detection system of fatigue driving, prevent from causing the failure of whole real-time detecting system because of a feature extraction failure.
The quantized value of driver's fatigue degree resolved by STM32F417 microprocessor in described image processing module, that the degree of fatigue of driver is quantified as five grades, wherein one, two grades are in abnormal driving state for driver, three grades are slight fatigue driving state for driver is in, four grades are in moderate fatigue driving state for driver, and five grades are in sever fatigue driving condition for driver.
The present invention's beneficial effect is compared with prior art:
The present invention carries out treatment and analysis by the video image information exported camera, by machine vision applications in fatigue driving detecting system, not only structure is simple, lightweight, cost is low, take up room little, be adapted at the indoor installation of car steering, and given full play to the noncontact that image detecting method has, high speed, the advantage of informative and relative inexpensiveness, disturb little to monitored driver, accuracy is stronger, antijamming capability is good, particularly its fatigue state can be detected before driver makes timely error, meet the requirement of real-time, corresponding warning message can also be sent according to the different brackets of the degree of fatigue quantized.
Accompanying drawing explanation
Accompanying drawing 1 is the hardware structure diagram of the specific embodiment of the invention.
Embodiment
Contrast accompanying drawing below in conjunction with embodiment the present invention will be described.
A kind of as shown in drawings based on the real-time detection system of fatigue driving of camera, be mounted in the online real time image processing system of car steering indoor, comprise video image acquisition module, view data memory module, Computer Vision module, and warning device 6.
Image capture module is made up of the camera 1 and on-site programmable gate array FPGA 2 comprising cmos image sensor chip, cmos image sensor built-in chip type sensor array, A/D converter 3 and correlated double sampling circuit, the vedio data of the driver in cmos image sensor chip Real-time Collection pilothouse, export the video interface of view data to FPGA 2 of pattra leaves erg formula, respective digital of decoding again stream obtains view data, be automatically transferred in the storer 4 of video image memory module and store, red (R) wherein, green (G), blue (B) three color component RGB are adjusted by digital gain, feed back to image processing module and carry out colors countenance or compression, image capture module completes image data acquiring under FPGA 2 controls, the pre-service of view data, rim detection, template area is mated, and carry out communication with image processing module.Noise in the picture signal that FPGA2 adopt Gaussian smoothing filter algorithm effectively to remove simulating signal that camera 1 exports obtains through decoded respective digital stream; and smoothed image signal; improve the quality of picture signal; the edge of available protecting picture signal and details; to be directly used in image recognition and detection, avoid illumination variation to restrict the performance of real-time detection system of fatigue driving simultaneously.FPGA2 carries out rim detection to image, is to adopt the edge detection operator of topography's differential technology to carry out rim detection to image, to find the information about shape and reflection or transmittance in image, improves the precision of real-time detection system of fatigue driving further.
Image processing module comprises STM32F417 microprocessor 5, complete data receiver simultaneously, state recognition and early warning, requirement of real time, STM32F417 microprocessor 5 is 32 digit flash memory microcontrollers based on ARM Cortex-M4 kernel, inner integrated DSP and FPU instruction, possess high performance signal transacting and floating-point operation ability, the also Flash of integrated 1 MB and the SRAM of 196 KB, the view data in the storer 4 of video image memory module is read by access, image is mated and arithmetic analysis, determine whether driver is in fatigue state, and parse the quantized value of driver's fatigue degree, by the data stream of correspondence by bus transfer to warning device 6.STM32F417 microprocessor 5 pairs of images mate, will change insensitive information as matching characteristic to gradation of image entirety, to improve the real-time of about real-time detection system of fatigue driving, the insensitive information of gradation of image entirety change is comprised to the texture of the unique point of image, the edge of image and image.STM32F417 microprocessor 5 pairs of images carry out arithmetic analysis, adopt the relevant tired information of fuzzy neural network algorithm extraction to organically blend into an entirety to carry out fatigue detecting, to strengthen the robustness of real-time detection system of fatigue driving, prevent from causing the failure of whole real-time detecting system because of a feature extraction failure.The quantized value of driver's fatigue degree resolved by STM32F417 micro-process 5 device, that the degree of fatigue of driver is quantified as five grades, wherein one, two grades are in abnormal driving state for driver, three grades are slight fatigue driving state for driver is in, four grades are in moderate fatigue driving state for driver, and five grades are in sever fatigue driving condition for driver.
Video image memory module comprises storer 4, stores the signal digital after by video decode, A/D conversion and flows through the decoded image information of image capture module, provide image processing module to call simultaneously.
Warning device 6 comprises audible alarm circuit and hummer, controlled by Computer Vision module, the different fatigue degree quantized value of the driver exported with image processing module carries out mating reports to the police, different sound is sent with different frequencies by hummer, when driver is in slight fatigue driving state, hummer sends short and rapid beep sound, provides warning to driver; When during driver is in, sever fatigue driving condition time, hummer sends continuous print roar, the rest until driver is stopped.
The real-time testing process of this embodiment is as follows:
The video image of the driver in pilothouse is gathered in real time by the camera 1 of video image acquisition module, be stored in the storer 4 of view data memory module, and by the driver fatigue evaluating in Computer Vision module use algorithm extraction video image and driver fatigue state criterion of identification, judge the different brackets of the fatigue results that detection system exports, then control the warning message that warning device 6 sends correspondence.
Above content is in conjunction with concrete preferred implementation further description made for the present invention, can not assert that specific embodiment of the invention is confined to these explanations.For general technical staff of the technical field of the invention; make some equivalent alternative or obvious modification without departing from the inventive concept of the premise; and performance or purposes identical, all should be considered as belonging to the scope of patent protection that the present invention is determined by submitted to claims.
Claims (10)
1., based on a real-time detection system of fatigue driving for camera, be mounted in the online real time image processing system of car steering indoor, it is characterized in that:
Described real time image processing system comprises video image acquisition module, view data memory module, Computer Vision module, and warning device, the video image of the driver in pilothouse is gathered in real time by the camera of described video image acquisition module, be stored in described view data memory module, and by the driver fatigue evaluating in described Computer Vision module use algorithm extraction video image and driver fatigue state criterion of identification, judge the different brackets of the fatigue results that detection system exports, control described warning device again and send corresponding warning message.
2., as claimed in claim 1 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
Described image capture module is made up of the camera and on-site programmable gate array FPGA comprising complementary metal oxide semiconductor (CMOS) cmos image sensor chip, described cmos image sensor built-in chip type sensor array, analog/digital A/D converter and correlated double sampling circuit, the vedio data of the driver in described cmos image sensor chip Real-time Collection pilothouse, export the video interface of view data to FPGA of pattra leaves erg formula, respective digital of decoding again stream obtains view data, be automatically transferred in the storer of described video image memory module and store, wherein red, green, blue three color component RGB are adjusted by digital gain, feed back to described image processing module and carry out colors countenance or compression, described image capture module completes image data acquiring under FPGA controls, the pre-service of view data, rim detection, template area is mated, and carry out communication with described image processing module.
3., as claimed in claim 1 or 2 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
Described image processing module comprises STM32F417 microprocessor, complete data receiver simultaneously, state recognition and early warning, requirement of real time, described STM32F417 microprocessor is 32 digit flash memory microcontrollers based on ARM Cortex-M4 kernel, inner integrated DSP and FPU instruction, the also Flash of integrated 1 MB and the SRAM of 196 KB, the view data in the storer of described video image memory module is read by access, image is mated and arithmetic analysis, determine whether driver is in fatigue state, and parse the quantized value of driver's fatigue degree, by the data stream of correspondence by bus transfer extremely described warning device.
4., as claimed in claim 3 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
Described video image memory module comprises storer, stores the signal digital after by video decode, A/D conversion and flows through the decoded image information of described image capture module, provide described image processing module to call simultaneously.
5., as claimed in claim 4 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
Described warning device comprises audible alarm circuit and hummer, is controlled by Computer Vision module, and the different fatigue degree quantized value of the driver exported with described image processing module carries out mating reports to the police, and sends different sound by hummer with different frequencies.
6., as claimed in claim 5 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
Noise in the picture signal that FPGA in described image capture module adopt Gaussian smoothing filter algorithm effectively to remove simulating signal that described camera exports obtains through decoded respective digital stream, and smoothed image signal.
7., as claimed in claim 6 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
FPGA in described image capture module carries out rim detection to image, is to adopt the edge detection operator of topography's differential technology to carry out rim detection to image.
8., as claimed in claim 7 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
STM32F417 microprocessor in described image processing module mates image, will change insensitive information as matching characteristic to gradation of image entirety, the described texture insensitive information of gradation of image entirety change being comprised to the unique point of image, the edge of image and image.
9., as claimed in claim 8 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
STM32F417 microprocessor in described image processing module carries out arithmetic analysis to image, is to adopt the relevant tired information of fuzzy neural network algorithm extraction to organically blend into an entirety to carry out fatigue detecting.
10., as claimed in claim 9 based on the real-time detection system of fatigue driving of camera, it is characterized in that:
The quantized value of driver's fatigue degree resolved by STM32F417 microprocessor in described image processing module, that the degree of fatigue of driver is quantified as five grades, wherein one, two grades are in abnormal driving state for driver, three grades are slight fatigue driving state for driver is in, four grades are in moderate fatigue driving state for driver, and five grades are in sever fatigue driving condition for driver.
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Cited By (12)
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| CN105828026A (en) * | 2016-02-23 | 2016-08-03 | 华北理工大学 | Reading fatigue intelligent detection system based on educational psychology and reading fatigue intelligent detection method thereof |
| CN108352119A (en) * | 2015-11-06 | 2018-07-31 | 大陆汽车***公司 | The enhancing sound for quiet vehicle with vehicle-to-vehicle communication ability generates |
| CN108460284A (en) * | 2017-02-17 | 2018-08-28 | 广州亿三电子科技有限公司 | A kind of computer critical data protection system and method |
| CN108491858A (en) * | 2018-02-11 | 2018-09-04 | 南京邮电大学 | Method for detecting fatigue driving based on convolutional neural networks and system |
| CN108509923A (en) * | 2018-03-30 | 2018-09-07 | 百度在线网络技术（北京）有限公司 | Classroom attention detection method, device, equipment and computer-readable medium |
| CN109493565A (en) * | 2018-11-02 | 2019-03-19 | 南京泰晟科技实业有限公司 | A kind of timely fatigue alarm set |
| CN110381288A (en) * | 2019-04-14 | 2019-10-25 | 泰州悦诚科技信息咨询中心 | Signal receives reply system |
| CN110910610A (en) * | 2019-11-22 | 2020-03-24 | 辽宁工程技术大学 | Fatigue driving early warning system based on DSP |
| WO2020082242A1 (en) * | 2018-10-23 | 2020-04-30 | 黄正民 | Fpga+arm control-based driver fatigue monitoring system |
| CN111709396A (en) * | 2020-07-08 | 2020-09-25 | 六盘水达安驾驶培训有限公司 | Driving skill subject two and three examination auxiliary evaluation method based on human body posture |
| CN112581509A (en) * | 2020-12-25 | 2021-03-30 | 北京环境特性研究所 | SOPC-based unmanned aerial vehicle-mounted ground target real-time tracking system and method |
| CN113558621A (en) * | 2021-07-23 | 2021-10-29 | 福州数据技术研究院有限公司 | Method and system for detecting and reminding fatigue of driver |
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108352119A (en) * | 2015-11-06 | 2018-07-31 | 大陆汽车***公司 | The enhancing sound for quiet vehicle with vehicle-to-vehicle communication ability generates |
| CN105828026A (en) * | 2016-02-23 | 2016-08-03 | 华北理工大学 | Reading fatigue intelligent detection system based on educational psychology and reading fatigue intelligent detection method thereof |
| CN108460284A (en) * | 2017-02-17 | 2018-08-28 | 广州亿三电子科技有限公司 | A kind of computer critical data protection system and method |
| CN108460284B (en) * | 2017-02-17 | 2023-12-29 | 广州亿三电子科技有限公司 | Computer key data protection system and method |
| CN108491858A (en) * | 2018-02-11 | 2018-09-04 | 南京邮电大学 | Method for detecting fatigue driving based on convolutional neural networks and system |
| CN108509923A (en) * | 2018-03-30 | 2018-09-07 | 百度在线网络技术（北京）有限公司 | Classroom attention detection method, device, equipment and computer-readable medium |
| WO2020082242A1 (en) * | 2018-10-23 | 2020-04-30 | 黄正民 | Fpga+arm control-based driver fatigue monitoring system |
| CN109493565A (en) * | 2018-11-02 | 2019-03-19 | 南京泰晟科技实业有限公司 | A kind of timely fatigue alarm set |
| CN110381288A (en) * | 2019-04-14 | 2019-10-25 | 泰州悦诚科技信息咨询中心 | Signal receives reply system |
| CN110910610A (en) * | 2019-11-22 | 2020-03-24 | 辽宁工程技术大学 | Fatigue driving early warning system based on DSP |
| CN111709396A (en) * | 2020-07-08 | 2020-09-25 | 六盘水达安驾驶培训有限公司 | Driving skill subject two and three examination auxiliary evaluation method based on human body posture |
| CN112581509A (en) * | 2020-12-25 | 2021-03-30 | 北京环境特性研究所 | SOPC-based unmanned aerial vehicle-mounted ground target real-time tracking system and method |
| CN112581509B (en) * | 2020-12-25 | 2023-08-15 | 北京环境特性研究所 | Unmanned aerial vehicle ground target real-time tracking system and tracking method based on SOPC |
| CN113558621A (en) * | 2021-07-23 | 2021-10-29 | 福州数据技术研究院有限公司 | Method and system for detecting and reminding fatigue of driver |
| CN113558621B (en) * | 2021-07-23 | 2023-08-01 | 福州数据技术研究院有限公司 | Method and system for detecting and reminding fatigue of driver |
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