KR101826715B1 - System and method for detecting vehicle invasion using room camera - Google Patents

Abstract

The present invention relates to a system and a method for detecting vehicle invasion. More particularly, the present invention relates to a system and a method for detecting vehicle invasion using a room camera. Images of the entire interior of a vehicle are analyzed to generate a mask including a minimum region that necessarily passes at the time of penetration through a vehicle window in a non-vehicle window region, which is a region excluding a vehicle window region. After that, the generated mask is compared with an image including the monitored vehicle window region and a motion object in an invasion determined region by the mask is detected to determine invasion.

Description

TECHNICAL FIELD [0001] The present invention relates to a system and method for detecting a vehicle intrusion using an indoor camera,

The present invention relates to a vehicle intrusion detection system and method. More particularly, the present invention relates to a vehicle intrusion detection system and method, and more particularly to a vehicle intrusion detection system and method, An indoor camera for detecting a motion object in the intrusion determination area by a mask and comparing the generated mask with an image including the monitored window area to generate an image of an indoor camera And more particularly, to a system and method for detecting intruders using a vehicle.

2. Description of the Related Art In general, an intrusion detection device is installed in a vehicle in order to prevent theft of articles in a vehicle and a vehicle. Generally, an intrusion detection device uses an ultrasonic sensor, an infrared sensor, or the like. In recent years, however, vision-based vehicle intrusion detection devices have attracted much attention as image processing technology develops.

The video (video) surveillance technology is important for intrusion detection devices using such images. Video surveillance technology has become a hot topic of study due to the rapid advancement of computer technology, especially image segmentation methods and background and foreground detection methods. Vehicle intrusion detection systems are primarily focused on detecting intrusions under normal conditions such as underground parking areas, open vehicle parking, and both sides of the road.

Video surveillance can be further divided into three parts, including motion detection, motion tracking and motion recognition. Motion detection, which is the basic part of video surveillance, refers to the extraction of moving objects in video. Common motion detection algorithms can be divided into three categories: background dependent algorithms, frame differential algorithms, and optical flow algorithms.

As most common motion detection algorithms, the background dependent algorithm uses the subtraction of the current frame and the background frame configured to detect the motion region.

The frame difference algorithm compares the current frame with the previous frame in order to detect the motion area, so it is robust to dynamic situations.

The optical flow method mainly uses the optical flow characteristics of moving objects and calculates the intensity values of pixels at different time zones to detect the moving speed and direction of the objects.

To be incorporated into a vehicle operating system, an image-based vehicle intrusion detection algorithm must have the advantages of low memory space cost and low computational cost. In addition, the algorithm must be robust against background variations and complex backgrounds.

The methods described above can perform vehicle intrusion detection to some extent. However, for example, it has some limitations and deficiencies as follows.

First, the main interference is the effect of different illuminance. For example, nighttime illumination is completely different. In addition, vehicle intrusion detection algorithms should be able to overcome dynamic, low illumination. Some algorithms, such as background dependency algorithms, are sensitive to its background model. If the established background differs from the current background, more errors will be detected in the intrusion detection.

Second, the situation outside the car changes frequently. For example, there will be moving pedestrians, moving vehicles, and moving leaves. If you simply use a frame difference algorithm, there will be many alarm malfunctions due to changing circumstances. And the computational cost of optical flow schemes is much higher than the frame differential algorithm.

Therefore, it is required to develop a real - time and high - efficiency vehicle intrusion detection system that is less influenced by the change of illumination, adaptable to changes in the situation outside the windshield, and fast in calculation.

In addition, while the vehicle battery is limited, the intrusion detection system continuously operates in the vehicle parking state in which the power of the vehicle battery is to be used, performs real-time monitoring, Of power. Accordingly, there has been a problem that the vehicle battery may be frequently discharged.

Therefore, development of a vehicle intrusion detection system capable of minimizing power consumption while real-time monitoring is performed in a start-off state of a vehicle that depends only on a vehicle battery is required.

Patent No. 1510948

Accordingly, an object of the present invention is to provide an image processing apparatus, an image processing method, an image processing method, an image processing method, an image processing method, The present invention also provides a system and method for detecting a vehicle intrusion using an indoor camera for detecting an intruder by detecting a moving object in an intrusion determination area by a mask by comparing images including a monitored window region.

According to an aspect of the present invention, there is provided a vehicle intrusion detection system using an indoor camera, comprising: an image acquisition unit including a camera for capturing and outputting an image; An alarm unit for alarming intrusion detection; And a control unit for controlling the operation of the control unit so as to control the operation of the control unit so that the control unit controls the operation of the control unit, And a mask including a masking region as a determination region. The image processing apparatus includes a mask generating unit that generates a still image by capturing an image input from the camera, detects the intrusion determination region by applying the mask to the still image, A control unit for generating an intrusion item still image including information on a moving object in the intruding still image, determining an intrusion by information on a moving object of the intrusion item still image, and generating an alarm through the alarm unit upon intrusion detection .

Wherein the control unit comprises: an image generating unit having the mask and capturing an image input from the camera to generate a still image; An intrusion determination area detector for detecting an intrusion determination area by applying the mask to the still image and outputting an intrusion determination area still image; An intrusion item detector for outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image; And an intrusion judging unit for judging an intrusion by information on a moving object of the intrusion item still image and generating an alarm through the alarm unit when intrusion is detected.

The system may further include: a brightness detector for measuring brightness; and the image acquiring unit may further include an infrared light capable of adjusting an intensity of infrared light, wherein the control unit controls the brightness of the night And a day / night determiner for determining whether the infrared light is on when the infrared light is on, turning off the infrared light when the day is off, and turning on the infrared light when the night is off.

The image generating unit may further include an infrared intensity adjusting unit for detecting a gray value of the generated still image and adjusting an infrared light intensity of the infrared light according to an infrared light intensity value corresponding to the gray value previously stored do.

The control unit receives a still image and generates and stores a mask that is a binary image by converting a window region to 0 from the still image and a masking region that is an intrusion determination region to 1 and outputs the still image to the intrusion determination region detection unit An image mask acquisition unit for outputting the mask to the intrusion determination region detection unit every time; And a still image generated from the image generating unit, determines whether or not it is an initial drive by determining whether a predetermined mask setting flag is set, and outputs the still image to the intrusion determination area detecting unit And an initial drive determination unit for outputting the image data to the image mask acquisition unit if the initial drive is performed.

The system may further include: a door closing detector for detecting at least one of closing and locking of the car door, wherein the controller further comprises a door closing determiner for determining whether the door is closed through the door closing detector, And the acquiring unit generates the mask when the door is closed and locked by the door closing detecting unit.

The intrusion item detection unit detects an object moving in the intrusion determination area still image by applying the following Equation 3 to the intrusion determination area still image output from the intrusion determination area detection unit, and has a threshold value T of 20 .

&Quot; (3) "

I (t) is the non-binning area of the image captured at time t. T is the threshold.

According to another aspect of the present invention, there is provided a method for detecting a vehicle intrusion using an indoor camera, comprising: generating an image by capturing an image input from a camera and generating a still image; The control unit separates and extracts a window region and a non-window region inside the vehicle. The control unit forms the window region through which the intruding object passes when the vehicle enters the vehicle room through the window region of the non- An intrusion judgment area detecting step of detecting an intrusion judgment area by applying a mask including a masking area as an intrusion judgment area to generate an intrusion judgment area still image; An intrusion item detection step of outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image; An intrusion judging step of judging an intrusion by information on a moving object of the intrusion item still image; And an alarm process for generating an alarm through the alarm unit upon detection of an intrusion.

The method further comprises: an infrared light driving step of driving the infrared light by turning on the infrared light when the control unit is low when the camera is low and turning on the infrared light when the camera is low during the camera driving.

The image generating step may include: an infrared light intensity adjusting step of detecting a gray value of a still image generated at the time of generating the still image and adjusting an infrared light intensity of the infrared light according to the detected gray value; And a still image output step of generating and outputting a still image from the image to which the infrared light intensity is applied after the infrared light intensity of the infrared light is adjusted.

The method may further include: an initial drive determining step of determining whether an initial drive is performed by determining whether a predetermined mask setting flag is set upon driving the image acquiring unit; And if it is determined in the initial driving state that the initial driving is performed, a window region and an intrusion determination region are detected from the still image, a detected window region is changed to 0, an intrusion determination region is changed to 1 to generate and store a mask, And an image mask acquiring step of outputting the mask every time the still image is output to the intrusion determining region detecting unit. The intrusion determining region detecting process is performed when the initial driving is not the result of the initial driving determination.

The method may further include: a door closing determination process for determining whether the door is closed by detecting at least one of closing and locking of the door through the door closing detection unit, And when it is determined that the door is closed.

The present invention has the effect of minimizing the influence of a sudden change in illuminance by turning the infrared light on or off according to illuminance, that is, brightness.

Further, the present invention adjusts the light intensity of the infrared ray according to the gray value of the obtained image, so that it has the effect of receiving less influence of the illumination change.

Further, the present invention has the effect of being unaffected by the change of the situation in the window region, that is, outside the window by applying the mask to the non-window region.

In addition, the present invention has an effect of being able to perform intrusion detection with high efficiency in real time because it is less influenced by a change in illuminance and is not affected by a change in a situation outside the windshield.

In addition, the present invention minimizes the area of the mask by minimizing the area of the mask, thereby minimizing the power consumption, thereby minimizing the discharge of the vehicle battery.

1 is a block diagram of an intrusion detection system using an indoor camera according to the present invention.
2 is a view showing an installation position of a camera in a vehicle according to an embodiment of the present invention.
3 is a flowchart illustrating an intrusion detection method using an indoor camera according to the present invention.
4 is a diagram illustrating a daytime software interface unit in which an infrared light is turned off according to an embodiment of the present invention.
FIG. 5 is a diagram showing an intrusion detection result during intrusion through a windshield in a daytime according to an embodiment of the present invention, in a general image and black and white (gray scale).
6 is a flowchart illustrating a mask generation method of an intrusion detection method using an indoor camera according to the present invention.
FIG. 7 is a view showing an example of generating a mask according to the setting of the in-vehicle region and the non-in-vehicle region of the grab-cut algorithm according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a vehicle intrusion detection system using an indoor camera according to the present invention will be described with reference to the accompanying drawings, and a vehicle intrusion detection method in the system will be described.

FIG. 1 is a view illustrating a configuration of an intrusion detection system using an indoor camera according to the present invention, and FIG. 2 is a view illustrating an installation position of a camera in a vehicle according to an embodiment of the present invention. Hereinafter, description will be made with reference to Figs. 1 and 2. Fig.

An intrusion detection system using an indoor camera according to the present invention includes an image acquisition unit 20 including a control unit 10, a camera 21 and an infrared light 22, a brightness detection unit 30, a door close detection unit 40, And may include an alarm unit 50, and may optionally include a display unit 60 and an input unit 70.

The control unit 10 controls the overall operation of the intrusion detection system according to the present invention. The detailed configuration and operation of the control unit 10 will be described later.

The image acquisition unit 20 includes a camera 21, an infrared light 22, and an image processing unit 23.

The camera 21 outputs a video signal of a scene captured on the lens. The camera 21 is preferably installed inside the vehicle so that all window areas within the vehicle are photographed. The resolution of the image captured by the camera 21 is preferably 640 * 480 and the frame rate is preferably 30 fps.

The infrared light 22 is integrally formed around the lens of the camera 21 and is turned on / off under the control of the control unit 10 and is illuminated in the morning / afternoon with sunlight (I.e., "day", "week", or "week"), and is turned on when there is no sunlight (or "night" or "night"). The infrared light 22 is controlled by the controller 10 to adjust the intensity of the infrared light. The lens in which the infrared light 22 is normally constituted is called an infrared lens.

For example, the camera 21 having the infrared lens may be installed at the center of the in-vehicle ceiling as shown in FIG. 2, and the angle of view of the lens is preferably 180 degrees so as to photograph all the in-vehicle window region.

The image processor 23 converts a video signal to be captured into a predetermined video format and outputs the video signal to the controller 10.

The brightness detector 30 may be an illuminometer or the like and detects the intensity of the light and outputs the detected intensity to the controller 10.

The door closing detection unit 40 detects at least one of closing and locking of the door, and outputs a door closing signal to the control unit 10 when the door is closed or locked.

The alarm unit 50 generates an alarm under the control of the control unit 10. The alarm may be an alarm sound, blinking of a light of a vehicle headlight or the like, transmission of a message to a mobile terminal of a vehicle manager, a smart phone, or the like through communication means.

The display unit 60 may be a liquid crystal display (LCD), a touch screen including an LCD and a touch pad, or may be integrally formed with a vehicle intrusion detection system, And may be configured as a cable connection. Under the control of the control unit 10, the display unit 60 displays various operation state information, moving images, still images, and the like of the vehicle intrusion detection system.

The input unit 70 may be a touch pad constituting a touch screen, a keypad having a plurality of function selection and information input means, and a keyboard, which are integrally formed on the screen of the display unit 60.

The control unit 10 includes a day / night determining unit 11, a door closing determining unit 12, an image generating unit 13, an initial driving determining unit 14, An acquisition unit 15, an intrusion determination region detection unit 16, an intrusion item detection unit 17 and an intrusion determination unit 19, and may further include a noise removing unit 18 according to an embodiment.

The day / night determining unit 11 determines whether the daylight is night (nighttime) or not (nighttime) based on the intensity of light input from the brightness detector 30, turns off the infrared light 22 when the daylight is low, The infrared light 22 is turned on. Here, daytime means the case where the intensity of light is more than a certain century, and it may be judged as a day if it is in a bright place at night or night if it is in a dark building at daytime.

The door close determination unit 12 determines whether a door close signal is input from the door close detection unit 40 and determines whether the door is closed or open. Closing may be a closed state of the door or a locked state of the door. The door closing determination unit 12 drives the image generation unit 13 when the door is closed.

The control unit 10 is connected to a key box of a vehicle, a body control module (BCM), and the like, and controls the start-up (On) / off Off determination unit (not shown) so as to drive the image generating unit 13 when the start is turned off and the vehicle door is closed.

The image generating unit 13 loads an image through the image processing unit 23 at the time of driving and acquires a still image (or a "still image" or an "image") from the loaded image to periodically output the image.

The image generating unit 13 includes an infrared intensity adjusting unit 13 for detecting a gray value of an image generated at every occurrence of an infrared light intensity adjusting event and adjusting an infrared light intensity of the infrared light 22 in accordance with the detected gray value -1). ≪ / RTI > The infrared light intensity control event may be generated every day or night by the day / night determiner 11, or may be generated every time a certain period or a certain number of still images are generated or may be generated by the vehicle manager. The infrared light intensity for each gray value may be obtained by an experiment.

The initial drive determination unit 14 receives the still image output from the image generation unit 13 and checks whether the mask setting flag is set to 1 or 0 or not (0 or 1) And outputs the still image to the image mask acquiring unit 15. If the mask is acquired, that is, if it is not the initial drive, the still image is judged as an intrusion judgment And outputs it to the area detection unit 16. [

The image mask obtaining unit 15 applies a GrabCut algorithm to the image output from the image generating unit 13 to apply the following Equation 1 to separate the in-vehicle and non-in-vehicle regions from the image in the vehicle And generates and stores a mask having a masking area, which is an intrusion determination area that minimizes an area that must pass through the extracted non-windowing area, and stores the generated mask in an image And outputs it to the area detection unit 16. [ The mask may be a binary image in which the window region is denoted by 0 and the non-window region is denoted by 1. As the method of selecting the masking area, there are an automatic mode and a manual mode.

The manual mode is a mode in which the intruder detection system installer or the user directly selects the masking area through the input unit 70 and the display unit 60. [

The automatic mode is a mode in which the image mask obtaining unit 15 automatically selects an area having a width corresponding to the pixel depth from the boundary of the window region in the non-window area according to a preset pixel depth as a masking area.

Where E is an energy function. The grab-cut algorithm minimizes the energy function to detect the background and foreground in the image. The background indicates a window in the intrusion detection algorithm, that is, a window region, and the foreground indicates a non-window region that is the remainder of the image.

Therefore, the doors of the vehicle must be closed when the image is taken. The purpose of the image is to partition the position of the non-window region in the vehicle to perform motion detection. So the doors must be closed and the inside view of the vehicle is not relevant unless the vehicle window is covered. Also, the background outside the vehicle will not affect the partition. This step may be performed only once after the camera is fixed by the initial drive determination unit 14 or at system initialization.

The intrusion determination area detecting unit 16 detects the intrusion determination area by multiplying the image generated by the image generating unit 13 by the mask output from the image mask obtaining unit 15 and detects an intrusion determination area including the detected intrusion determination area Area Output a still image.

The intrusion item detection unit 17 detects an intrusion item, i.e., a moving object, by applying a frame difference algorithm according to the previous intrusion determination area still image to the intrusion determination area still image output from the intrusion determination area detection unit 16, And outputs an intrusion item still image including information on the intrusion item.

The intrusion item detector 17 detects a moving object in a non-window area using a threshold value at the time of subtraction of a current frame having a background model. The background model in the frame difference is the same as the previous frame. The theory is shown in Equation 2 below.

I (t) is the non-binning area of the image captured at time t. T is the threshold.

As described above, the mask is a binary image in which the window region has a value of 0 and the intrusion determination region has a value of 1. The intrusion detection area in the new captured image is obtained by multiplying it by the image mask. The frame difference algorithm is then used to detect moving objects in the intrusion detection area. The influence of moving objects outside the car is removed by detecting the intrusion detection area of the vehicle. Moving objects are detected by applying a threshold value of 20 to the resulting image.

The noise removing unit 18 removes the noise of the intrusion item still image caused by the frame difference algorithm performed by the intrusion item detecting unit 17 and outputs the noise.

More specifically, the noise eliminator 18 applies a 3x3 or 5x5 convolution kernel to be convolved with the captured intent still image to remove noise, and applies a threshold filter to the still invaded still image with convolution And outputs the filtered image to the intrusion determining unit 18. The threshold value of the threshold filter may be 200. In other words, the filter threshold is set to 4 when the 3x3 convolution kernel is applied, the filter threshold is set to 12 when the 5x5 convolution kernel is applied, and the sum of the pixels The filter threshold for the value may be set to 200.

The intrusion determining unit 19 determines the intrusion by calculating the sum of the remaining pixels in the filtered image. Specifically, if the sum of the filtered image pixels is greater than the threshold value, the intrusion determining unit 19 determines that an intrusion has occurred, and generates an alarm through the alarm unit 50.

More specifically, even if the vehicle window region is removed, there will still be noise pixels after the frame difference algorithm. Thus, the culling removal 18 removes such noise pixels by two convolution kernels. The two convolution kernels are 3x3 and 5x5, respectively. The values of the pixels in the kernels are 1. For the 3x3 kernel, threshold 4 is used to filter the convolution result image. For the 5x5 kernel, the threshold 12 is used to filter the convolution result image. Finally, the intrusion judging unit 19 calculates remaining pixels after the convolution result image to judge the intrusion.

FIG. 3 is a flowchart illustrating an intrusion detection method using an indoor camera according to the present invention, FIG. 4 is a diagram illustrating a daytime software interface means in which an infrared light is turned off according to an embodiment of the present invention, (Gray scale) of the intrusion detection result during the daytime through the window according to one embodiment of the present invention. This will be described below with reference to Figs. 3 to 5. Fig.

First, when the intrusion detection system is activated, the control unit 10 detects the brightness or lightness of light through the brightness detection unit 30 (S111) and determines whether it is day or night (S113).

The control unit 10 turns off the infrared light 22 of the image obtaining unit 20 in step S115 and turns on the infrared light 22 in step S117.

When the operation of the infrared light 22 is completed, the control unit 10 reads the image photographed through the camera 21 (S119).

When the image is read, the control unit 10 determines whether the mask setting flag is set (1 or 0) or reset (0 or 1) and determines whether it is the first drive (S121). The mask setting flag is a flag indicating whether or not a mask is generated and stored by a mask generation process, and may be set when a mask is generated and stored.

If it is determined that the vehicle is the first drive, the control unit 10 separates and extracts a window region and a non-window region according to the grab-cut algorithm from the image to be read, and generates a mask having an intrusion determination region in the non-window region (S123). The still image for generating the mask would preferably be acquired in the daytime. The mask generation process will be described in detail with reference to FIG. 4, which will be described later.

On the other hand, if it is not the first drive, the control unit 10 may acquire a still image including all the window regions as indicated by the program interface means of FIG. 4 (S125). After adjusting the light intensity by gray value detection, (S127 to S135).

S127 to S135 will be described in more detail. The control unit 10 detects a gray value in a still image S121 obtained from an input image (S127), and loads an infrared light intensity value corresponding to the detected gray value ( S129). It is preferable that the infrared light intensity value is previously defined for each gray value, and it can be obtained by experiment.

When the infrared light intensity value is loaded, the controller 10 determines whether the light intensity value is an allowable intensity (S131).

As a result of the determination, if the infrared light intensity value is not an allowable intensity, the process after step S111 is performed again. If the infrared light intensity value is less than the allowable intensity, the infrared light intensity value is increased. If the infrared light intensity value is larger than the allowable intensity, the light intensity value may be adjusted to be lowered.

If the loaded infrared light intensity value is an allowable intensity, the controller 10 controls the infrared light 22 to adjust the infrared light intensity to the loaded infrared light intensity value (S133).

After the infrared light intensity is adjusted, the control unit 10 obtains a still image to which the infrared ray of the adjusted intensity is applied (S135).

As described above, if a still image is obtained immediately after the initial driving determination or after the light intensity is adjusted, the control unit 10 multiplies the obtained still image by the mask to determine an intrusion determination area including an intrusion determination area And generates an image (S137).

When the intrusion determination region still image is generated, the control unit 10 applies the frame difference algorithm to the non-window region still image to determine whether there is a moving object (intrusion item) in the intrusion determination region, An intrusion item still image including an intrusion item as shown on the right side of FIG. 2 (b) is generated (S139).

When an intrusion item still image including an intrusion item is generated as described above, the controller 10 convolutes a 3x3 or 5x5 convolution kernel to the image to generate a filtered image (S141).

When the filtered image is generated, the controller 10 calculates the sum of the pixels in the filtered image as described above, and determines whether the sum of the calculated pixels exceeds the filter threshold (S143).

If it is determined that an intrusion has occurred, the control unit 10 generates an alarm through the alarm unit 50 (S145).

FIG. 6 is a flowchart illustrating a mask generation method of an intrusion detection method using an indoor camera according to the present invention. FIG. 7 is a flowchart illustrating a method of generating a mask according to the setting of a vehicle window region and a non- Fig. Hereinafter, a mask generation method will be described with reference to FIGS. 6 and 7. FIG.

First, the control unit 10 acquires a still image from a video signal input from the image acquisition unit 20 (S211). The control unit 10 may acquire the still image after acquiring the still image by applying the processes of S127 to S133 of FIG.

 The control unit 10 separates and extracts the non-windower regions, which are regions excluding the windshield region 701 and the windshield region 701, by applying the grab-cut algorithm (S213, S215).

If the window region 701 and the non-window region are separated and extracted, the control unit 10 determines whether the intrusion determination region selection mode is the automatic mode or the manual mode (S217).

In the automatic mode, the control unit 10 searches through the window region 701 for the minimum area that must pass through the window region 701 (S219). A search area through which the intruding object must pass when entering the inside of the vehicle through the window region 701 may be 711 in FIG. 7 (B).

When the search area 711 is searched, the controller 10 sets the search area having the preset pixel depth as the intrusion determination area in the search area (S221), and the mask including the intrusion determination area set as shown in (S223). It is preferable that the mask is generated for each window as shown in (c) of Fig. 7 in order to minimize the intrusion judgment area. That is, the masks 721-1 and 721-2 for the search area 711-1, the search area 711-2, the search area 711-3, and the search area 711-4 in FIG. 7B, A mask 721-2 (not shown), a mask 721-3 (not shown), and a mask 721-4 (not shown). In addition, the mask 721-1, the mask 721-2 (not shown), the mask 721-3 (not shown), and the mask 721-4 (not shown) may be combined.

A pixel depth for determining an area may be set even when searching the search area 711. The pixel depth at this time and the pixel length of the intrusion determination area may be the same. In this case, the search area 711 may be an intrusion determination area.

On the other hand, in the manual mode, the controller 10 requests the masking area to be selected through the display unit 60 (S225), and then the masking area is selected through the input unit 70 (S227).

If the masking area is selected, the control unit 10 checks whether a mask generation command is generated (S229). The mask generation command may be generated from the input unit 70 or may be generated automatically after a predetermined time after the selection of the masking area.

When a mask generation command is generated, the controller 10 generates a mask including the masking area (S231).

The pixel depth of the masking area may be preset in manual mode and when the user selects the masking area within the pixel depth, the control unit 10 may request to select the masking area again through the display unit 60. [

 While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. It will be easily understood. It is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, it is intended to cover various modifications within the scope of the appended claims.

10: control unit 11: day /
12: door closing determination unit 13:
13-1 Infrared intensity controller 14: Initial drive determiner
15: Image mask acquisition unit 16: Intrusion determination area detection unit
17: Intrusion item detecting unit 18: Noise removing unit
19: Intrusion judging unit 20: Image acquiring unit
21: Camera 22: Infrared light
23: image processor 30: brightness detector
40: door closing detection part 50: alarm part
60: display section 70: input section

Claims (12)

An image acquisition unit including a camera for capturing and outputting an image;
An alarm unit for alarming intrusion detection; And
A method of detecting an intrusion of an intruder, comprising the steps of: extracting a windshield area and a non-windshield area inside a vehicle; And a mask including a masking area, wherein the camera includes a camera for capturing an image input from the camera to generate a still image, detecting the intrusion determination area by applying the mask to the still image, And a control unit for generating an alarm through the alarm unit upon detecting an intrusion by detecting information on a moving object of the intrusion item still image, wherein the intrusion item still image includes information on a moving object of the intrusion item,
Wherein,
An image generating unit having the mask and capturing an image input from the camera to generate a still image;
An intrusion determination area detector for detecting an intrusion determination area by applying the mask to the still image and outputting an intrusion determination area still image;
An intrusion item detector for outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image; And
And an intrusion determination unit for determining an intrusion based on information on a moving object of the intrusion item still image and generating an alarm through the alarm unit when an intrusion is detected.
delete The method according to claim 1,
Further comprising a brightness detector for measuring brightness,
The image acquiring unit may further include an infrared light capable of adjusting the intensity of infrared light,
Wherein,
Further comprising a day / night judging section for judging whether the time is night or night by the brightness measured by the brightness detecting section, turning off the infrared light when it is low, and turning on the infrared light when it is nighttime Intrusion detection system.
The method of claim 3,
The image generation unit may include:
Further comprising an infrared intensity adjusting unit for detecting a gray value of the generated still image and adjusting an infrared light intensity of the infrared light according to an infrared light intensity value corresponding to the gray value that is held in advance Vehicle intrusion detection system.
The method according to claim 1,
Wherein,
A still image is received, and a mask, which is a binary image, is generated by converting a window region to 0 and an intrusion determination region to 1 from the still image, and stores the generated mask as an intrusion determination region detection portion. An image mask obtaining unit outputting the image mask image to the intrusion determination region detecting unit; And
Wherein the control unit receives the still image generated from the image generating unit, determines whether the predefined mask setting flag is set to determine whether it is an initial drive, outputs the still image to the intrusion determination area detecting unit, Further comprising an initial drive determination unit for outputting the initial image data to the image mask acquisition unit if the initial camera is an initial drive.
6. The method of claim 5,
Further comprising a door closing detecting portion for detecting at least one of closing and locking of the car door,
Wherein,
Further comprising a door closing determination unit for determining whether the door is closed through the door closing detection unit,
Wherein the image mask obtaining unit generates the mask when the door is closed or locked by the door close detecting unit.
The method according to claim 1,
Wherein the intrusion item detecting unit comprises:
Wherein a moving object is detected in the intrusion determination area still image by applying the following Equation (3) to the intrusion determination area still image output from the intrusion determination area detection unit, and the threshold value T is 20. [ Detection system.

&Quot; (3) "

I (t) is the non-binning area of the image captured at time t. T is the threshold.
An image generating process of capturing an image input from a camera and generating a still image;
The control unit separates and extracts a window region and a non-window region inside the vehicle. The control unit forms the window region through which the intruding object passes when the vehicle enters the vehicle room through the window region of the non- An intrusion judgment area detecting step of detecting an intrusion judgment area by applying a mask including a masking area as an intrusion judgment area to generate an intrusion judgment area still image;
An intrusion item detection step of outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image;
An intrusion judging step of judging an intrusion by information on a moving object of the intrusion item still image; And
And an alarm process for generating an alarm through the alarm unit upon detection of an intrusion,
The image generation process includes:
An infrared light intensity adjusting step of detecting a gray value of the still image generated at the time of generating the still image and adjusting an infrared light intensity of the infrared light according to the detected gray value; And
And a still image outputting step of generating and outputting a still image from the image to which the infrared light intensity is applied after the infrared light intensity of the infrared light is adjusted and outputting the still image.
9. The method of claim 8,
Further comprising an infrared light driving step of driving the infrared light by turning on the infrared light when the controller is low when the camera is low and turning on the infrared light when the camera is low when the camera is driving.
delete An image generating process of capturing an image input from a camera and generating a still image;
The control unit separates and extracts a window region and a non-window region inside the vehicle. The control unit forms the window region through which the intruding object passes when the vehicle enters the vehicle room through the window region of the non- An intrusion judgment area detecting step of detecting an intrusion judgment area by applying a mask including a masking area as an intrusion judgment area to generate an intrusion judgment area still image;
An intrusion item detection step of outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image;
An intrusion judging step of judging an intrusion by information on a moving object of the intrusion item still image; And
And an alarm process for generating an alarm through the alarm unit upon detection of an intrusion,
An initial drive determining step of determining whether an initial drive is performed by determining whether a mask setting flag is predefined when the image acquiring unit is driven; And
If the initial drive is determined to be the initial drive, it detects an in-car region and an intrusion determination region from the still image, converts the detected in-car region to 0, converts the intrusion determination region to 1 to generate and store a mask that is a binary image, And an image mask acquiring step of outputting the mask at each output of the still image to the determination area detecting unit,
The intrusion determination region detecting process may include:
The method of detecting a vehicle intrusion using an indoor camera according to claim 1,
An image generating process of capturing an image input from a camera and generating a still image;
The control unit separates and extracts a window region and a non-window region inside the vehicle. The control unit forms the window region through which the intruding object passes when the vehicle enters the vehicle room through the window region of the non- An intrusion judgment area detecting step of detecting an intrusion judgment area by applying a mask including a masking area as an intrusion judgment area to generate an intrusion judgment area still image;
An intrusion item detection step of outputting an intrusion item still image including information on a moving object in the detected intrusion determination area still image;
An intrusion judging step of judging an intrusion by information on a moving object of the intrusion item still image; And
And an alarm process for generating an alarm through the alarm unit upon detection of an intrusion,
Further comprising a door closing determining step of determining whether the door is closed by detecting at least one of closing and locking of the door through the door closing detecting unit,
Wherein the image generating process is performed when it is determined that the door is closed in the door closing determination process.

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