WO2020107306A1 - 一种闯红灯车辆信息智能化采集***及其方法 - Google Patents
一种闯红灯车辆信息智能化采集***及其方法 Download PDFInfo
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- WO2020107306A1 WO2020107306A1 PCT/CN2018/118095 CN2018118095W WO2020107306A1 WO 2020107306 A1 WO2020107306 A1 WO 2020107306A1 CN 2018118095 W CN2018118095 W CN 2018118095W WO 2020107306 A1 WO2020107306 A1 WO 2020107306A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
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- the invention relates to the field of traffic supervision, and in particular to a method for intelligently collecting vehicle information through red lights.
- the present invention provides a method for intelligently collecting information on vehicles running through red lights, using pre-stored image templates of emergency passing vehicles and image matching technology to remove the interference of vehicles passing through vehicles passing through red lights in emergency, and detecting the current red light in real time.
- the parallel image processing technology is used to abandon the violation detection of the green light lane, and only information collection is carried out on the illegal vehicles in the red light lane, which makes the information collection of the red light vehicle of the present invention more targeted.
- an intelligent red light vehicle information collection system for collecting red light vehicle information at intersections corresponding to signal lights
- the collection system includes an induction coil set, a signal light state detection device, an image detection device, and DSP processing
- the induction coil set is used to sense whether a vehicle passing through the traffic lane corresponding to the signal light is detected
- the signal light state detection device is used to detect the current state of the signal light
- the DSP processor is based on the induction result and the position of the induction coil set The detection result of the signal light state detection device, and controlling the image acquisition and image processing operations of the image detection device to obtain the information of the vehicle running through the red light
- the invention also provides a method for intelligently collecting information on vehicles running through red lights. More specifically, in the intelligently collecting information system on vehicles running through red lights, it further includes: a set of oscillation circuits, including a plurality of oscillation circuits, the number of oscillation circuits and signal lights The number of lanes at the corresponding intersection is the same. Multiple oscillation circuits correspond to multiple induction coils in the induction coil set. Each oscillation circuit is connected to the corresponding induction coil. When a vehicle passes a predetermined distance in front of the parking line of the lane where the corresponding induction coil is located, The mutual induction between the corresponding induction coil and the vehicle body causes the oscillation frequency of the oscillation circuit to change.
- the frequency detection circuit is connected to a plurality of oscillation circuits of the oscillation circuit set, Detect whether the oscillation frequency of each oscillating circuit has changed, and send out the lane number of the induction coil corresponding to the oscillating circuit whose oscillation frequency has changed, the number sequence of the lane number is from left to right;
- the storage device use
- two emergency passing vehicle image templates are stored in advance, the emergency passing vehicle image template is an image pre-photographed for a reference emergency passing vehicle, the reference emergency passing vehicle is a reference ambulance or a reference fire truck, and the storage device is also in advance
- the upper limit gray threshold of the lane reference line, the lower limit gray threshold of the lane reference line, the upper limit gray threshold of the vehicle, and the lower limit gray threshold of the vehicle are stored.
- the upper limit gray threshold of the lane reference line and the lower limit gray threshold of the lane reference line are used To separate the lane reference line and the background in the image, the upper vehicle grayscale threshold and the lower vehicle grayscale threshold are used to separate the vehicle from the background in the image;
- the wireless communication device is used to receive one or more red lights Vehicle information and send the one or more red light vehicle information to the server of the local traffic management platform through a wireless communication link, so that the server's hard disk stores the one or more red light vehicle information;
- the induction coil set Including multiple induction coils, the number of induction coils is the same as the number of lanes corresponding to the intersection of signal lights, multiple induction coils correspond to multiple lanes one by one, each induction coil is buried under a predetermined distance in front of the parking lane of the corresponding lane;
- the signal light state detection device is respectively connected to a plurality of signal light units of the signal light, the number of the signal light units is the same as the number of lanes of the corresponding intersection of
- the image detection device It includes an image acquisition unit, a vehicle type recognition unit, a wavelet filter unit, a grayscale processing unit, an image segmentation unit, and multiple parallel image processing units.
- the number of parallel image processing units is the same as the number of lanes at the intersection corresponding to the signal light. Multiple parallel images
- the serial number of the processing unit corresponds one-to-one with multiple lanes.
- the image acquisition unit is connected to the DSP processor and is used to capture an image of the intersection at a predetermined distance in front of the corresponding intersection of the signal light when the same lane number is received.
- the wavelet filter unit is The image acquisition unit is connected to perform wavelet filtering processing on the intersection image based on a Haar wavelet filter to obtain a filtered image
- the vehicle type identification unit is connected to the wavelet filter unit and the storage device, Match the vehicle pattern in the filtered image with the two emergency passing vehicle image templates one by one.
- the processing unit is connected to the vehicle type identification unit, and when the non-emergency passing vehicle signal is received, the filtered image is gray-scaled to obtain a gray-scale image.
- the image segmentation unit and the gray-scale processing The unit, the wavelet filtering unit and the storage device are respectively connected to identify pixels in the grayscale image between the upper grayscale threshold of the lane reference line and the lower grayscale threshold of the lane reference line And form multiple lane reference line sub-images, and divide the filtered image into multiple lane filter sub-images based on the positions of the multiple lane reference line sub-images in the grayscale image, the number of the lane filter sub-images The number of lanes corresponding to the intersection of the signal light is the same, multiple lane filter sub-images correspond to multiple lanes, and each parallel image processing unit is connected to the image segmentation unit, the storage device, and the DSP processor, each The parallel image processing unit exits the power saving mode to start parallel image processing when the corresponding lane number exists in the received same lane number, and enters the power saving mode when the corresponding lane number does not exist in the received same lane number Mode, the parallel image processing includes receiving a lane filtering sub-image corresponding to
- the image collection unit includes a CMOS vision sensor.
- the image collection unit further includes a lens and a filter, the filter is located in front of the lens, and the lens is located in front of the CMOS vision sensor.
- the CMOS vision sensor is a high-definition vision sensor, and the resolution adopted is 1920 ⁇ 1080.
- the collection system further includes a brightness detection device for detecting the ambient brightness of the surrounding environment of the collection system; an auxiliary lighting source is located on the image detection device. Above the image acquisition unit, it is connected to the brightness detection device, and determines whether to provide auxiliary lighting for shooting of the image acquisition unit based on the ambient brightness.
- FIG. 1 is a structural block diagram of a red light traffic information intelligent collection system according to an embodiment of the present invention.
- FIG. 2 is a block diagram showing the structure of an image detection device for a red light traffic information intelligent collection system according to an embodiment of the present invention.
- Red light running refers to the behavior of a motor vehicle crossing a stop line and continuing to drive in violation of the red light no-traffic regulations at signal-controlled intersections and sections.
- intersection is a meeting point and a conflict point of traffic flow. Running a red light increases the insecurity of the meeting point and the conflict point itself, resulting in a decrease in the safety factor;
- Running a red light affects the safe passing performance of vehicles, and also reduces the ability of other traffic participants to respond to and respond to strains;
- the existing red light vehicle information collection system cannot remove the interference caused by emergency vehicles, the system redundancy is too high, and the work efficiency is average.
- the present invention builds an intelligent information collection system for vehicles running through red lights.
- the collection system is built on the crossbar where the signal lights are located and is used to collect information about vehicles running through red lights corresponding to the intersections of the signal lights.
- Multiple image processing technologies such as filtering, image graying processing and image segmentation complete the collection of vehicle information of running red lights efficiently and reasonably, and the structure of the entire collection system is more compact.
- FIG. 1 is a structural block diagram of an intelligent collection system for red light traffic vehicles according to an embodiment of the present invention.
- the collection system is disposed on a crossbar where a signal light is located, and is used to collect information about a red light traffic vehicle at an intersection corresponding to the signal lights.
- the signal light state detection device 4, the image detection device 5, the storage device 6, and the wireless communication device 7 are respectively connected, and the oscillation circuit set 2 is connected to the frequency detection circuit 1 and the induction coil set 3, respectively.
- the induction coil set 3 is used to sense whether a vehicle passing through the lane corresponding to the signal light is detected
- the signal light state detection device 4 is used to detect the current state of the signal light
- the DSP processor 8 is based on the induction coil set 3
- the sensing result and the detection result of the signal light state detection device 4 control the image acquisition and image processing operations of the image detection device 5 to obtain the red light vehicle information.
- the oscillating circuit set 2 includes a plurality of oscillating circuits, the number of oscillating circuits is the same as the number of lanes corresponding to the intersections of the signal lights, the oscillating circuits correspond one-to-one with the plurality of induction coils in the induction coil set 3, and each oscillating circuit is connected Induction coil, when a vehicle passes a predetermined distance in front of the parking line where the corresponding induction coil is located, the corresponding induction coil and the vehicle body have a mutual inductance, causing the oscillation frequency of the oscillation circuit to change. Conversely, when no vehicle passes, the oscillation frequency of the oscillation circuit remains constant.
- the frequency detection circuit 1 is connected to a plurality of oscillation circuits of the oscillation circuit set 2 respectively, detects whether the oscillation frequency of each oscillation circuit has changed, and sends out the lane number of the induction coil corresponding to the oscillation circuit whose oscillation frequency has changed, The numbering sequence of the lane numbers is from left to right.
- the storage device 6 is used to pre-store two emergency passing vehicle image templates, the emergency passing vehicle image template being an image pre-photographed for a reference emergency passing vehicle, the reference emergency passing vehicle being a reference ambulance or a reference fire truck, the The storage device 6 also pre-stores the lane reference line upper limit gray threshold, the lane reference line lower limit gray threshold, the vehicle upper limit gray threshold and the vehicle lower limit gray threshold, the lane reference line upper limit gray threshold and the lane reference line
- the lower limit grayscale threshold is used to separate the lane reference line and the background in the image
- the upper vehicle grayscale threshold and the lower vehicle grayscale threshold are used to separate the vehicle and the background in the image.
- the wireless communication device 7 is used to receive one or more red light vehicle information and send the one or more red light vehicle information to a server of a local traffic management platform through a wireless communication link, so that the hard disk of the server stores the one Or multiple vehicles running through red lights.
- the induction coil set 3 includes a plurality of induction coils.
- the number of induction coils is the same as the number of lanes corresponding to the intersections of the signal lights.
- the plurality of induction coils correspond to the plurality of lanes one by one.
- Each induction coil is buried in front of the parking lane of the corresponding lane. Below the distance.
- the signal light state detection device 4 is respectively connected to a plurality of signal light units of the signal light.
- the number of the signal light units is the same as the number of lanes of the corresponding intersection of the signal light.
- the plurality of signal light units correspond to the plurality of lanes.
- the signal light state detection device 4 is based on Whether the plurality of signal light units are currently red lights outputs the lane number of the lane corresponding to the signal light unit currently being red lights.
- the DSP processor 8 is connected to the frequency detection circuit 1, the signal light state detection device 4, the image detection device 5, and the wireless communication device 7 respectively, looking for the frequency detection circuit 1 and the signal light state
- the lane numbers with the same value output by the detection devices 4 are sent to the image detection device 5 as the same lane numbers.
- the DSP processor 8 also receives one or more red light vehicle information output by the image detection device 5 and sends The one or more red light vehicle information is forwarded to the wireless communication device 7.
- the image detection device 5 includes an image acquisition unit 51, a vehicle type recognition unit 53, a wavelet filter unit 52, a gradation processing unit 54, an image segmentation unit 56, and a plurality of parallel image processing units 55.
- Multiple parallel image processing units 55 have serial numbers corresponding to multiple lanes.
- the image acquisition unit 51 is connected to the DSP processor, and is used to take an image of a junction at a predetermined distance in front of the intersection corresponding to the signal light when the same lane number is received, and the wavelet filter unit 52 is The image acquisition unit 51 is connected to perform wavelet filtering processing on the intersection image based on a Haar wavelet filter to obtain a filtered image, the vehicle type recognition unit 53 and the wavelet filter unit 52 and the storage device Connect respectively, and match the vehicle pattern in the filtered image with the two emergency passing vehicle image templates one by one. When there is a matching emergency passing vehicle image template, the emergency passing vehicle signal is output; otherwise, the non-emergency passing vehicle signal is output.
- the grayscale processing unit 54 is connected to the vehicle type identification unit 53, and when the non-emergency passing vehicle signal is received, the filtered image is grayscaled to obtain a grayscale image, and the image segmentation unit 56 is The gradation processing unit 54, the wavelet filtering unit 52 and the storage device are respectively connected to connect the gradation value in the gradation image to the upper limit gradation threshold of the lane reference line and the lower limit of the lane reference line.
- the pixels between the gray thresholds identify and compose multiple lane reference line sub-images, and divide the filtered image into multiple lane filter sub-images based on the positions of the multiple lane reference line sub-images in the gray-scale image,
- the number of the lane filtering sub-images is the same as the number of lanes corresponding to the intersections of the signal lights, and the multiple lane filtering sub-images correspond to the multiple lanes one-to-one.
- Each parallel image processing unit 55 is connected to the image segmentation unit 56, the storage device, and the DSP processor.
- each parallel image processing unit 55 receives the corresponding lane number in the same lane number, Exit the power saving mode to start parallel image processing, and enter the power saving mode when the corresponding lane number does not exist in the same lane number received.
- the parallel image processing includes receiving the lane filtering sub-image of the corresponding lane, which will be received.
- the pixels in the lane filter sub-image whose gray value is between the upper gray threshold of the vehicle and the lower gray threshold of the vehicle identify and form a vehicle sub-image, identify the license plate information in the vehicle sub-image, and will correspond
- the lane number of the lane and the recognized license plate information are combined and output as the red light vehicle information.
- the wireless communication link is one of GPRS mobile communication link, 3G mobile communication link or 4G mobile communication link.
- the image acquisition unit 51 may include a CMOS vision sensor, and the image acquisition unit 51 may further include a lens and a filter.
- the filter is located in front of the lens, and the lens is located in front of the CMOS vision sensor.
- the CMOS vision sensor is a high-definition vision sensor with a resolution of 1920 ⁇ 1080;
- the collection system may further include a brightness detection device for detecting the ambient brightness of the surrounding environment of the collection system, including an auxiliary lighting source, located at the Above the image acquisition unit 51 of the image detection device 5, it is connected to the brightness detection device, and determines whether to provide auxiliary lighting for shooting of the image acquisition unit 51 based on the ambient brightness.
- CMOS Complementary Metal-Oxide-Semiconductor
- Chinese name is complementary metal oxide semiconductor
- CMOS Complementary Metal-Oxide-Semiconductor
- N charge-charged
- P charged + charge
- CMOS image sensors are designed for 5V and 3.3V supply voltages.
- the CCD chip requires a power supply voltage of about 12V, so a voltage converter has to be used, resulting in increased power consumption.
- the integration of control and system functions into the CMOS sensor will bring another benefit: he removes all external connections to other semiconductor components. Its high-power drivers are now deprecated, because the energy consumed for communication inside the chip is much lower than the external implementation through the PCB or substrate.
- CMOS sensors can also be subdivided into passive pixel sensors (Passive Pixel Sensor CMOS) and active pixel sensors (Active Pixel Sensor CMOS).
- Passive Pixel Sensor CMOS Passive Pixel Sensor CMOS
- Active Pixel Sensor CMOS Active Pixel Sensor CMOS
- Passive pixel sensor also called passive pixel sensor, is composed of a reverse-biased photodiode and a switch tube.
- the photodiode is essentially a PN junction composed of a P-type semiconductor and an N-type semiconductor. It can be equivalent to a reverse biased diode and a MOS capacitor in parallel.
- the switch tube When the switch tube is turned on, the photodiode is connected to the vertical column line (Column bus).
- the charge integration amplifier at the end of the column line maintains the column line voltage at a constant value.
- the signal charge stored in the photodiode is read out, its voltage is reset to the column line voltage level, and at the same time The charge proportional to the optical signal is converted into a charge output by the charge integration amplifier.
- Active pixel sensor Active Pixel Sensor, APS for short
- CMOS PPS pixel structure Almost at the same time that the CMOS PPS pixel structure was invented, people quickly realized that introducing a buffer or amplifier into the pixel can improve the performance of the pixel.
- each pixel has its own amplifier.
- the amplifying transistor integrated on the surface reduces the effective surface area of the pixel element and reduces the "packing density", so that 40% to 50% of incident light is reflected.
- Another problem with this type of sensor is how to better match the multi-channel amplifiers of the sensor, which can be better achieved by reducing the residual pattern of fixed pattern noise. Since each amplifier in the CMOS APS pixel is only activated during this readout, the power consumption of the CMOS APS is smaller than that of the CCD image sensor.
- red light vehicle information collection system of the present invention By adopting the intelligent red light vehicle information collection system of the present invention, in view of the technical problems that the existing red light vehicle information collection system may erroneously collect and the system is not compact, through a series of image processing, emergency traffic vehicles such as ambulances that allow temporary red light traffic to pass are avoided Vehicles and fire engines were collected by mistake. At the same time, vehicle information was collected only for the red light channel, which improved the reliability and intelligence of the system.
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Abstract
一种闯红灯车辆信息智能化采集***及其方法,用于采集信号灯对应路口的闯红灯车辆信息,采集***包括感应线圈集合(3)、信号灯状态检测设备(4)、图像检测设备(5)和DSP处理器(8),感应线圈集合(3)用于感应信号灯对应路口的车道是否有车辆通过,信号灯状态检测设备(4)用于检测信号灯的当前状态,DSP处理器(8)根据感应线圈集合(3)的感应结果和信号灯状态检测设备(4)的检测结果,控制图像检测设备(5)的图像采集和图像处理操作以获得闯红灯车辆信息;采集***及其方法还包括使用***来进行采集。
Description
本发明涉及交通监管领域,尤其涉及一种闯红灯车辆信息智能化采集方法。
为了实现对车辆违章行为的有效发现、处罚、维护交通安全,大量的违章车辆信息采集***被安装在各个重要交通路口,以应用到道路交通管理中。然而,现有技术中的闯红灯车辆信息采集***存在以下局限:一是无法实时鉴别如救护车、消防车等紧急通行车辆,仍然会对这些紧急通行车辆进行闯红灯拍照,浪费了有限的***资源,为闯红灯违章查处带来了干扰;二是一般通过一幅路口图像的分析同时判断多个车道的闯红灯违章检测,实际上,对当前允许通行的车道的车辆信息检测是无意义,也是同样浪费***资源的。
因此,需要一种闯红灯车辆信息智能化采集方法,能够提高闯红灯车辆信息采集***的电子资源的利用率,并实时在拍摄现场即完成对紧急通行车辆的去干扰,在保证信息采集的准确性的同时,提高了采集***的智能化程度和工作效率。
发明内容
为了解决上述问题,本发明提供了一种闯红灯车辆信息智能化采集方法,利用预先存储的紧急通过车辆图像模板和图像匹配技术去除紧急通过车辆对闯红灯车辆信息采集的干扰,在实时检测到当前红灯车道的基础上,利用并行图像处理技术放弃绿灯车道的违章检测,只对红灯车道的违章车辆进行信息采集,使得本发明的闯红灯车辆信息采集更有针对性。
根据本发明的一方面,提供了一种闯红灯车辆信息智能化采集***,用于采集信号灯对应路口的闯红灯车辆信息,所述采集***包括感应线圈集合、信号灯状态检测设备、图像检测设备和DSP处理器,所述感应线圈集合用于感应信号灯对应路口的车道是否有车辆通过,所述信号灯状态检测设备用于检测信号灯的当前状态,所述DSP处理器根据所述感应线圈集合的感应结果和所 述信号灯状态检测设备的检测结果,控制所述图像检测设备的图像采集和图像处理操作以获得闯红灯车辆信息;
本发明还提供了一种闯红灯车辆信息智能化采集方法,更具体地,在所述闯红灯车辆信息智能化采集***中,还包括:振荡电路集合,包括多个振荡电路,振荡电路的数量与信号灯对应路口的车道数量相同,多个振荡电路与感应线圈集合中多个感应线圈一一对应,每一个振荡电路连接对应的感应线圈,当有车辆通过对应感应线圈所在车道停车线前方预定距离时,对应感应线圈与车辆车体产生互感,导致振荡电路振荡频率发生变化,相反,当无车辆通过时,振荡电路振荡频率保持不变;频率检测电路,与振荡电路集合的多个振荡电路分别连接,检测每一个振荡电路的振荡频率是否发生变化,并将振荡频率发生变化的振荡电路所对应的感应线圈所在的车道序号发送出去,所述车道序号的编号顺序为从左到右;存储设备,用于预先存储两个紧急通过车辆图像模板,所述紧急通过车辆图像模板为对基准紧急通过车辆预先拍摄的图像,所述基准紧急通过车辆为基准救护车或基准消防车,所述存储设备还预先存储了车道参考线上限灰度阈值、车道参考线下限灰度阈值、车辆上限灰度阈值和车辆下限灰度阈值,所述车道参考线上限灰度阈值和所述车道参考线下限灰度阈值用于将图像中的车道参考线和背景分离,所述车辆上限灰度阈值和所述车辆下限灰度阈值用于将图像中的车辆和背景分离;无线通信设备,用于接收一个或多个闯红灯车辆信息并将所述一个或多个闯红灯车辆信息通过无线通信链路发送到当地交通管理平台的服务器,以便于所述服务器的硬盘存储所述一个或多个闯红灯车辆信息;所述感应线圈集合包括多个感应线圈,感应线圈的数量与信号灯对应路口的车道数量相同,多个感应线圈与多个车道一一对应,每一个感应线圈被埋设在对应车道停车线前方预定距离的下方;所述信号灯状态检测设备与信号灯的多个信号灯单元分别连接,信号灯单元的数量与信号灯对应路口的车道数量相同,多个信号灯单元与多个车道一一对应,所述信号灯状态检测设备根据多个信号灯单元当前是否为红灯输出当前为红灯的信号灯单元所对应车道的车道序号;所述DSP处理器与所述频率检测电路、所述信号灯状态检测设备、所述图像检测设备和所述无线通信设备分别连接,寻找所述频率检 测电路和所述信号灯状态检测设备都输出的数值相同的车道序号作为相同车道序号发送给所述图像检测设备,所述DSP处理器还接收所述图像检测设备输出的一个或多个闯红灯车辆信息,并将所述一个或多个闯红灯车辆信息转发给所述无线通信设备;所述图像检测设备包括图像采集单元、车辆类型识别单元、小波滤波单元、灰度化处理单元、图像分割单元和多个并行图像处理单元,并行图像处理单元的数量与信号灯对应路口的车道数量相同,多个并行图像处理单元序号与多个车道一一对应,所述图像采集单元与所述DSP处理器连接,用于在接收到相同车道序号时拍摄信号灯对应路口前方预定距离的路口图像,所述小波滤波单元与所述图像采集单元连接,用于基于哈尔小波滤波器将所述路口图像进行小波滤波处理,以获得滤波图像,所述车辆类型识别单元与所述小波滤波单元和所述存储设备分别连接,将所述滤波图像中的车辆图案与所述两个紧急通过车辆图像模板逐一匹配,存在匹配成功的紧急通过车辆图像模板时输出紧急通过车辆信号,否则输出非紧急通过车辆信号,所述灰度化处理单元与所述车辆类型识别单元连接,在接收到非紧急通过车辆信号时将所述滤波图像进行灰度化处理,以获得灰度图像,所述图像分割单元与所述灰度化处理单元、所述小波滤波单元和所述存储设备分别连接,将所述灰度图像中灰度值在所述车道参考线上限灰度阈值和所述车道参考线下限灰度阈值之间的像素识别并组成多个车道参考线子图像,并基于多个车道参考线子图像在所述灰度图像中的位置将所述滤波图像划分为多个车道滤波子图像,所述车道滤波子图像的数量与信号灯对应路口的车道数量相同,多个车道滤波子图像与多个车道一一对应,每一个并行图像处理单元与所述图像分割单元、所述存储设备和所述DSP处理器连接,每一个并行图像处理单元在接收到的相同车道序号中存在对应的车道的序号时,退出省电模式以启动并行图像处理,在接收到的相同车道序号中不存在对应的车道的序号时,进入省电模式,所述并行图像处理包括接收对应车道的车道滤波子图像,将接收到的车道滤波子图像中灰度值在所述车辆上限灰度阈值和所述车辆下限灰度阈值之间的像素识别并组成车辆子图像,识别所述车辆子图像中的车牌信息,并将对应车道的车道序号和识别到的车牌信息组合以作为闯红灯车辆信息输出;其中,所述无线通信链路为GPRS 移动通信链路、3G移动通信链路或4G移动通信链路中的一种。
更具体地,在所述闯红灯车辆信息智能化采集***中:所述图像采集单元包括CMOS视觉传感器。
更具体地,在所述闯红灯车辆信息智能化采集***中:所述图像采集单元还包括镜头和滤光片,所述滤光片位于镜头前方,所述镜头位于所述CMOS视觉传感器前方。
更具体地,在所述闯红灯车辆信息智能化采集***中:所述CMOS视觉传感器为高清视觉传感器,采用的分辨率为1920×1080。
更具体地,在所述闯红灯车辆信息智能化采集***中,所述采集***还包括亮度检测设备,用于检测所述采集***周围环境的环境亮度;辅助照明光源,位于所述图像检测设备的图像采集单元上方,与所述亮度检测设备连接,基于所述环境亮度确定是否为所述图像采集单元的拍摄提供辅助照明。
为了更清楚地说明本发明实施例的技术方案,下面将对实施例描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
以下将结合附图对本发明的实施方案进行描述,其中:
图1为根据本发明实施方案示出的闯红灯车辆信息智能化采集***的结构方框图。
图2为根据本发明实施方案示出的闯红灯车辆信息智能化采集***的图像检测设备的结构方框图。
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用于限定本发明。
下面将参照附图对本发明的闯红灯车辆信息智能化采集***及其方法的实施方案进行详细说明。
闯红灯指的是,机动车在信号控制的交叉路口和路段上违反红灯禁止通行规定,越过停止线并继续行驶的行为。
闯红灯会使得驾驶员出现以下不良反应:
1、闯红灯时驾驶员的注意力都在交通信号灯上,不能全面和正确感知车内外的变化,给驾驶员的反应和措施带来困难;
2、闯红灯时,通常通过路口的车速都比较快,减弱了驾驶员对空间的认知能力;
3、闯红灯时,驾驶员对各类交通环境的判断能力下降,有时会使驾驶员的思维判断或操作出现失误;
4、路口是交通流的汇合点和冲突点,闯红灯加大了汇合点和冲突点本身的不安全性,导致安全系数下降;
5、闯红灯影响驾驶员及时、准确、有效地操控车辆;
6、闯红灯影响车辆的安全通过性能,同时也减弱了其他交通参与者的应变反映能力和应变处置能力;
7、实践证明百分之九十的重特大交通事故都发生在交叉路口,因此由闯红灯所造成的事故后果通常都比较严重;
8、红绿灯下,如出现驾驶员的无意识化,则具有极端危害性。
为了抑制闯红灯这一违章现象,避免严重交通事故发生,需要对实时获取闯红灯车辆的信息以对闯红灯车辆的持有人进行严惩。现有的闯红灯车辆信息采集***无法去除紧急通行车辆带来的干扰,***冗余度过高,工作效率一般。
本发明搭建了一种闯红灯车辆信息智能化采集***,所述采集***搭建在信号灯所在的横杆上,用于采集信号灯对应路口的闯红灯车辆信息,通过包括图像识别、图像匹配、图像采集、图像滤波、图像灰度化处理以及图像分割等多项图像处理技术,高效合理地完成了闯红灯车辆信息的采集,整个采集***的结构更加紧凑。
图1为根据本发明实施方案示出的闯红灯车辆信息智能化采集***的结构方框图,所述采集***设置在信号灯所在的横杆上,用于采集信号灯对应路口的闯红灯车辆信息,所述采集***包括频率检测电路1、振荡电路集合2、感 应线圈集合3、信号灯状态检测设备4、图像检测设备5、存储设备6、无线通信设备7和DSP处理器8,DSP处理器8与频率检测电路1、信号灯状态检测设备4、图像检测设备5、存储设备6和无线通信设备7分别连接,振荡电路集合2与频率检测电路1和感应线圈集合3分别连接。
其中,所述感应线圈集合3用于感应信号灯对应路口的车道是否有车辆通过,所述信号灯状态检测设备4用于检测信号灯的当前状态,所述DSP处理器8根据所述感应线圈集合3的感应结果和所述信号灯状态检测设备4的检测结果,控制所述图像检测设备5的图像采集和图像处理操作以获得闯红灯车辆信息。
接着,继续对本发明的闯红灯车辆信息智能化采集***的具体结构进行进一步的说明。
所述振荡电路集合2包括多个振荡电路,振荡电路的数量与信号灯对应路口的车道数量相同,多个振荡电路与感应线圈集合3中多个感应线圈一一对应,每一个振荡电路连接对应的感应线圈,当有车辆通过对应感应线圈所在车道停车线前方预定距离时,对应感应线圈与车辆车体产生互感,导致振荡电路振荡频率发生变化,相反,当无车辆通过时,振荡电路振荡频率保持不变。
频率检测电路1与振荡电路集合2的多个振荡电路分别连接,检测每一个振荡电路的振荡频率是否发生变化,并将振荡频率发生变化的振荡电路所对应的感应线圈所在的车道序号发送出去,所述车道序号的编号顺序为从左到右。
存储设备6用于预先存储两个紧急通过车辆图像模板,所述紧急通过车辆图像模板为对基准紧急通过车辆预先拍摄的图像,所述基准紧急通过车辆为基准救护车或基准消防车,所述存储设备6还预先存储了车道参考线上限灰度阈值、车道参考线下限灰度阈值、车辆上限灰度阈值和车辆下限灰度阈值,所述车道参考线上限灰度阈值和所述车道参考线下限灰度阈值用于将图像中的车道参考线和背景分离,所述车辆上限灰度阈值和所述车辆下限灰度阈值用于将图像中的车辆和背景分离。
无线通信设备7用于接收一个或多个闯红灯车辆信息并将所述一个或多个闯红灯车辆信息通过无线通信链路发送到当地交通管理平台的服务器,以便于 所述服务器的硬盘存储所述一个或多个闯红灯车辆信息。
所述感应线圈集合3包括多个感应线圈,感应线圈的数量与信号灯对应路口的车道数量相同,多个感应线圈与多个车道一一对应,每一个感应线圈被埋设在对应车道停车线前方预定距离的下方。
所述信号灯状态检测设备4与信号灯的多个信号灯单元分别连接,信号灯单元的数量与信号灯对应路口的车道数量相同,多个信号灯单元与多个车道一一对应,所述信号灯状态检测设备4根据多个信号灯单元当前是否为红灯输出当前为红灯的信号灯单元所对应车道的车道序号。
所述DSP处理器8与所述频率检测电路1、所述信号灯状态检测设备4、所述图像检测设备5和所述无线通信设备7分别连接,寻找所述频率检测电路1和所述信号灯状态检测设备4都输出的数值相同的车道序号作为相同车道序号发送给所述图像检测设备5,所述DSP处理器8还接收所述图像检测设备5输出的一个或多个闯红灯车辆信息,并将所述一个或多个闯红灯车辆信息转发给所述无线通信设备7。
如图2所示,所述图像检测设备5包括图像采集单元51、车辆类型识别单元53、小波滤波单元52、灰度化处理单元54、图像分割单元56和多个并行图像处理单元55,多个并行图像处理单元为n个,n与信号灯对应路口的车道数量相同,多个并行图像处理单元55序号与多个车道一一对应。
在所述图像检测设备5中,所述图像采集单元51与所述DSP处理器连接,用于在接收到相同车道序号时拍摄信号灯对应路口前方预定距离的路口图像,所述小波滤波单元52与所述图像采集单元51连接,用于基于哈尔小波滤波器将所述路口图像进行小波滤波处理,以获得滤波图像,所述车辆类型识别单元53与所述小波滤波单元52和所述存储设备分别连接,将所述滤波图像中的车辆图案与所述两个紧急通过车辆图像模板逐一匹配,存在匹配成功的紧急通过车辆图像模板时输出紧急通过车辆信号,否则输出非紧急通过车辆信号,所述灰度化处理单元54与所述车辆类型识别单元53连接,在接收到非紧急通过车辆信号时将所述滤波图像进行灰度化处理,以获得灰度图像,所述图像分割单元56与所述灰度化处理单元54、所述小波滤波单元52和所述存储设备分别连 接,将所述灰度图像中灰度值在所述车道参考线上限灰度阈值和所述车道参考线下限灰度阈值之间的像素识别并组成多个车道参考线子图像,并基于多个车道参考线子图像在所述灰度图像中的位置将所述滤波图像划分为多个车道滤波子图像,所述车道滤波子图像的数量与信号灯对应路口的车道数量相同,多个车道滤波子图像与多个车道一一对应。
每一个并行图像处理单元55与所述图像分割单元56、所述存储设备和所述DSP处理器连接,每一个并行图像处理单元55在接收到的相同车道序号中存在对应的车道的序号时,退出省电模式以启动并行图像处理,在接收到的相同车道序号中不存在对应的车道的序号时,进入省电模式,所述并行图像处理包括接收对应车道的车道滤波子图像,将接收到的车道滤波子图像中灰度值在所述车辆上限灰度阈值和所述车辆下限灰度阈值之间的像素识别并组成车辆子图像,识别所述车辆子图像中的车牌信息,并将对应车道的车道序号和识别到的车牌信息组合以作为闯红灯车辆信息输出。
其中,所述无线通信链路为GPRS移动通信链路、3G移动通信链路或4G移动通信链路中的一种。
其中,所述图像采集单元51可以包括CMOS视觉传感器,所述图像采集单元51还可以包括镜头和滤光片,所述滤光片位于镜头前方,所述镜头位于所述CMOS视觉传感器前方,所述CMOS视觉传感器为高清视觉传感器,采用的分辨率为1920×1080;所述采集***还可以包括亮度检测设备,用于检测所述采集***周围环境的环境亮度,包括辅助照明光源,位于所述图像检测设备5的图像采集单元51上方,与所述亮度检测设备连接,基于所述环境亮度确定是否为所述图像采集单元51的拍摄提供辅助照明。
另外,CMOS(Complementary Metal-Oxide-Semiconductor),中文学名为互补金属氧化物半导体,他本是计算机***内一种重要的芯片,保存了***引导最基本的资料。CMOS的制造技术和一般计算机芯片没什么差别,主要是利用硅和锗这两种元素所做成的半导体,使其在CMOS上共存着带N(带-电)和P(带+电)级的半导体,这两个互补效应所产生的电流即可被处理芯片纪录和解读成影像。后来发现CMOS经过加工也可以作为数码摄影中的图像传感器。
对于独立于电网的便携式应用而言,以低功耗特性而著称的CMOS技术具有一个明显的优势:CMOS图像传感器是针对5V和3.3V电源电压而设计的。而CCD芯片则需要大约12V的电源电压,因此不得不采用一个电压转换器,从而导致功耗增加。在总功耗方面,把控制和***功能集成到CMOS传感器中将带来另一个好处:他去除了与其他半导体元件的所有外部连接线。其高功耗的驱动器如今已遭弃用,这是因为在芯片内部进行通信所消耗的能量要比通过PCB或衬底的外部实现方式低得多。
CMOS传感器也可细分为被动式像素传感器(Passive Pixel Sensor CMOS)与主动式像素传感器(Active Pixel Sensor CMOS)。
被动式像素传感器(Passive Pixel Sensor,简称PPS),又叫无源式像素传感器,他由一个反向偏置的光敏二极管和一个开关管构成。光敏二极管本质上是一个由P型半导体和N型半导体组成的PN结,他可等效为一个反向偏置的二极管和一个MOS电容并联。当开关管开启时,光敏二极管与垂直的列线(Column bus)连通。位于列线末端的电荷积分放大器读出电路(Charge integrating amplifier)保持列线电压为一常数,当光敏二极管存贮的信号电荷被读出时,其电压被复位到列线电压水平,与此同时,与光信号成正比的电荷由电荷积分放大器转换为电荷输出。
主动式像素传感器(Active Pixel Sensor,简称APS),又叫有源式像素传感器。几乎在CMOS PPS像素结构发明的同时,人们很快认识到在像素内引入缓冲器或放大器可以改善像素的性能,在CMOS APS中每一像素内都有自己的放大器。集成在表面的放大晶体管减少了像素元件的有效表面积,降低了“封装密度”,使40%~50%的入射光被反射。这种传感器的另一个问题是,如何使传感器的多通道放大器之间有较好的匹配,这可以通过降低残余水平的固定图形噪声较好地实现。由于CMOS APS像素内的每个放大器仅在此读出期间被激发,所以CMOS APS的功耗比CCD图像传感器的还小。
采用本发明的闯红灯车辆信息智能化采集***,针对现有闯红灯车辆信息采集***可能出现误采集以及***不够紧凑的技术问题,通过一系列的图像处理,避免允许临时闯红灯通行的紧急通行车辆如救护车、消防车被误采集,同 时,只对红灯通道进行车辆信息采集,提高了***的可靠性和智能化水平。
可以理解的是,虽然本发明已以较佳实施例披露如上,然而上述实施例并非用以限定本发明。对于任何熟悉本领域的技术人员而言,在不脱离本发明技术方案范围情况下,都可利用上述揭示的技术内容对本发明技术方案做出许多可能的变动和修饰,或修改为等同变化的等效实施例。因此,凡是未脱离本发明技术方案的内容,依据本发明的技术实质对以上实施例所做的任何简单修改、等同变化及修饰,均仍属于本发明技术方案保护的范围内。
Claims (4)
- 一种闯红灯车辆信息智能化采集***,用于采集信号灯对应路口的闯红灯车辆信息,其特征在于,包括感应线圈集合、信号灯状态检测设备、图像检测设备和DSP处理器,所述感应线圈集合用于感应信号灯对应路口的车道是否有车辆通过,所述信号灯状态检测设备用于检测信号灯的当前状态,所述DSP处理器根据所述感应线圈集合的感应结果和所述信号灯状态检测设备的检测结果,控制所述图像检测设备的图像采集和图像处理操作以获得闯红灯车辆信息。
- 根据权利要求1所述的一种闯红灯车辆信息智能化采集***,其特征在于,所述采集***还包括:振荡电路集合,包括多个振荡电路,振荡电路的数量与信号灯对应路口的车道数量相同,多个振荡电路与感应线圈集合中多个感应线圈一一对应,每一个振荡电路连接对应的感应线圈;频率检测电路,与振荡电路集合的多个振荡电路分别连接,检测每一个振荡电路的振荡频率是否发生变化,并将振荡频率发生变化的振荡电路所对应的感应线圈所在的车道序号发送出去,所述车道序号的编号顺序为从左到右;存储设备,用于预先存储两个紧急通过车辆图像模板,所述紧急通过车辆图像模板为对基准紧急通过车辆预先拍摄的图像,所述基准紧急通过车辆为基准救护车或基准消防车,所述存储设备还预先存储了车道参考线上限灰度阈值、车道参考线下限灰度阈值、车辆上限灰度阈值和车辆下限灰度阈值,所述车道参考线上限灰度阈值和所述车道参考线下限灰度阈值用于将图像中的车道参考线和背景分离,所述车辆上限灰度阈值和所述车辆下限灰度阈值用于将图像中的车辆和背景分离;无线通信设备,用于接收一个或多个闯红灯车辆信息并将所述一个或多个闯红灯车辆信息通过无线通信链路发送到当地交通管理平台的服务器,以便于所述服务器的硬盘存储所述一个或多个闯红灯车辆信息。
- 根据权利要求1所述的一种闯红灯车辆信息智能化采集***及方法,其特征在于,所述感应线圈集合包括多个感应线圈,感应线圈的数量与信号灯对应路口的车道数量相同,多个感应线圈与多个车道一一对应,每一个感应线圈 被埋设在对应车道停车线前方预定距离的下方,当有车辆通过对应感应线圈所在车道停车线前方预定距离时,对应感应线圈与车辆车体产生互感,导致振荡电路振荡频率发生变化,相反,当无车辆通过时,振荡电路振荡频率保持不变。
- 一种闯红灯车辆信息智能化采集方法,其特征在于,信号灯状态检测设备与信号灯的多个信号灯单元分别连接,信号灯单元的数量与信号灯对应路口的车道数量相同,多个信号灯单元与多个车道一一对应,所述信号灯状态检测设备根据多个信号灯单元当前是否为红灯输出当前为红灯的信号灯单元所对应车道的车道序号;DSP处理器与所述频率检测电路、所述信号灯状态检测设备、所述图像检测设备和所述无线通信设备分别连接,寻找所述频率检测电路和所述信号灯状态检测设备都输出的数值相同的车道序号作为相同车道序号发送给所述图像检测设备,所述DSP处理器还接收所述图像检测设备输出的一个或多个闯红灯车辆信息,并将所述一个或多个闯红灯车辆信息转发给所述无线通信设备;所述图像检测设备包括图像采集单元、车辆类型识别单元、小波滤波单元、灰度化处理单元、图像分割单元和多个并行图像处理单元,并行图像处理单元的数量与信号灯对应路口的车道数量相同,多个并行图像处理单元序号与多个车道一一对应;所述图像采集单元与所述DSP处理器连接,用于在接收到相同车道序号时拍摄信号灯对应路口前方预定距离的路口图像;所述小波滤波单元与所述图像采集单元连接,用于基于哈尔小波滤波器将所述路口图像进行小波滤波处理,以获得滤波图像;所述车辆类型识别单元与所述小波滤波单元和所述存储设备分别连接,将所述滤波图像中的车辆图案与所述两个紧急通过车辆图像模板逐一匹配,存在匹配成功的紧急通过车辆图像模板时输出紧急通过车辆信号,否则输出非紧急通过车辆信号,所述灰度化处理单元与所述车辆类型识别单元连接,在接收到非紧急通过车辆信号时将所述滤波图像进行灰度化处理,以获得灰度图像;所述图像分割单元与所述灰度化处理单元、所述小波滤波单元和所述存储设备分别连接,将所述灰度图像中灰度值在所述车道参考线上限灰度阈值和所 述车道参考线下限灰度阈值之间的像素识别并组成多个车道参考线子图像,并基于多个车道参考线子图像在所述灰度图像中的位置将所述滤波图像划分为多个车道滤波子图像,所述车道滤波子图像的数量与信号灯对应路口的车道数量相同,多个车道滤波子图像与多个车道一一对应,每一个并行图像处理单元与所述图像分割单元、所述存储设备和所述DSP处理器连接,每一个并行图像处理单元在接收到的相同车道序号中存在对应的车道的序号时,退出省电模式以启动并行图像处理,在接收到的相同车道序号中不存在对应的车道的序号时,进入省电模式,所述并行图像处理包括接收对应车道的车道滤波子图像,将接收到的车道滤波子图像中灰度值在所述车辆上限灰度阈值和所述车辆下限灰度阈值之间的像素识别并组成车辆子图像,识别所述车辆子图像中的车牌信息,并将对应车道的车道序号和识别到的车牌信息组合以作为闯红灯车辆信息输出;其中,所述无线通信链路为GPRS移动通信链路、3G移动通信链路或4G移动通信链路中的一种。
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