WO2017028029A1 - Procédé et appareil d'extraction de modèle d'arrière-plan et dispositif de traitement d'image - Google Patents

Procédé et appareil d'extraction de modèle d'arrière-plan et dispositif de traitement d'image Download PDF

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Publication number
WO2017028029A1
WO2017028029A1 PCT/CN2015/087029 CN2015087029W WO2017028029A1 WO 2017028029 A1 WO2017028029 A1 WO 2017028029A1 CN 2015087029 W CN2015087029 W CN 2015087029W WO 2017028029 A1 WO2017028029 A1 WO 2017028029A1
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WIPO (PCT)
Prior art keywords
background model
image
foreground
preset threshold
area
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PCT/CN2015/087029
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English (en)
Chinese (zh)
Inventor
杨兵兵
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富士通株式会社
杨兵兵
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Priority to PCT/CN2015/087029 priority Critical patent/WO2017028029A1/fr
Publication of WO2017028029A1 publication Critical patent/WO2017028029A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Definitions

  • the present invention relates to the field of graphic image technology, and in particular, to a method and apparatus for extracting a background model and an image processing apparatus.
  • background images are widely used in the field of image monitoring and the like.
  • the difference between the current frame and the reference frame can be compared, thereby detecting a moving object.
  • the reference frame may be referred to as a "background image” or represented using a "background model.”
  • Embodiments of the present invention provide a method, an apparatus, and an image processing apparatus for extracting a background model. It can reduce the ghosting phenomenon during image detection, and can detect objects that move at a relatively small speed or are stationary for a certain period of time.
  • a method for extracting a background model includes:
  • the background model is initialized if the ratio is less than the predetermined threshold.
  • an apparatus for extracting a background model comprising:
  • An image acquisition unit that acquires a current image of the monitoring area
  • a foreground extraction unit that extracts a foreground image region from the current image based on a background model
  • a ratio calculating unit that calculates a ratio of the number of pixels of the foreground image region to the number of pixels of the monitoring region
  • Comparing units comparing the ratio to a preset threshold
  • the background initializing unit initializes the background model if the ratio is less than the preset threshold.
  • an image processing apparatus comprising the extraction means of the background model as described above.
  • a computer readable program wherein when the program is executed in an image processing apparatus, the program causes a computer to execute a background model as described above in the image processing apparatus Extraction method.
  • a storage medium storing a computer readable program, wherein the computer readable program causes a computer to perform an extraction method of a background model as described above in an image processing device.
  • the beneficial effects of the embodiment of the present invention are: calculating a ratio of the number of pixels of the foreground image area to the number of pixels of the monitoring area; and updating the background model using the current image if the ratio is less than a preset threshold. Therefore, the background model can be extracted using a more suitable image, the ghost phenomenon in the image detection process can be reduced, and an object with a relatively small moving speed or a certain time can be detected, and the image detection accuracy is higher and the noise is tolerated. The ability is stronger.
  • FIG. 1 is a schematic diagram of a method for extracting a background model according to Embodiment 1 of the present invention
  • FIG. 2 is another schematic diagram of a method for extracting a background model according to Embodiment 1 of the present invention.
  • FIG. 3 is a schematic diagram of expanding a foreground object region according to Embodiment 1 of the present invention.
  • FIG. 4 is a schematic diagram of an apparatus for extracting a background model according to Embodiment 2 of the present invention.
  • Figure 5 is another schematic diagram of an apparatus for extracting a background model according to Embodiment 2 of the present invention.
  • Fig. 6 is a block diagram showing the configuration of an image processing apparatus according to a third embodiment of the present invention.
  • ghosting may occur in a scene where, for example, when a moving object becomes a stationary object for a period of time (for example, a vehicle waiting for a traffic light), the moving object may be considered to be stationary and updated.
  • a moving object becomes a stationary object for a period of time (for example, a vehicle waiting for a traffic light)
  • the moving object may be considered to be stationary and updated.
  • ghosts will be left when the object moves again.
  • an object that has been considered to be the background image area for example, a car that has been parked for a few days in the parking lot
  • ghosting will occur when the object starts moving.
  • an image monitoring scene in the traffic field will be taken as an example for description.
  • the present invention is not limited thereto, and can be applied to other scenarios.
  • Embodiments of the present invention provide a method for extracting a background model.
  • 1 is a schematic diagram of a method for extracting a background model according to an embodiment of the present invention. As shown in FIG. 1, the extraction method includes:
  • Step 101 Acquire a current image of a monitoring area.
  • Step 102 Extract a foreground image region from the current image based on a background model
  • Step 103 Calculate a ratio of the number of pixels of the foreground image area to the number of pixels of the monitoring area;
  • Step 104 comparing the ratio with a preset threshold
  • Step 105 Initialize the background model if the ratio is less than the preset threshold.
  • video information including a plurality of frame images can be obtained by the camera.
  • the camera may be a camera for performing traffic image monitoring, and the monitoring area is continuously captured; however, the present invention is not limited thereto, and may be other image monitoring scenes.
  • the background model in step 102 may be pre-generated using the prior art, and then the background model may be continuously updated.
  • the initial background model M 0 can be obtained from one frame of image, and then the background model is continuously updated to obtain background models M 1 , M 2 , . . . , Mi.
  • the ratio of the number of pixels of the foreground image area to the number of pixels of the monitoring area is calculated; and the background model is re-initialized if the ratio is less than a preset threshold.
  • the background model can be extracted using a more suitable image.
  • the preset threshold is 0.5.
  • the ratio (ie, 0.7) of the number of pixels (for example, 560) of the foreground image region and the number of pixels of the monitoring region (for example, 800) is determined to be larger than the ratio.
  • the image can be considered to be unsuitable for background model extraction.
  • the ratio of the number of pixels (for example, 80) of the foreground image region and the number of pixels of the monitoring region (for example, 800) ie, 0.1
  • the image can be considered suitable for background model extraction.
  • the background model may be gradually updated using a plurality of preset thresholds.
  • the preset threshold is a plurality of values arranged in descending order and used in sequence. For example, four values of 0.5, 0.4, 0.3, and 0.2.
  • a relatively accurate initial background model can be obtained by gradually approximating these thresholds.
  • FIG. 2 is another schematic diagram of a method for extracting a background model according to an embodiment of the present invention. As shown in FIG. 2, the extraction method includes:
  • Step 201 obtaining a background model M 0 ;
  • the background model M 0 can be obtained based on the prior art. Any of the methods of obtaining a background model in the prior art can be employed.
  • Step 202 Acquire a current image of the monitoring area.
  • Step 203 extract a foreground image region from the current image based on the background model M i ;
  • i is 0 or a positive integer.
  • Step 204 Calculate a ratio of the number of pixels of the foreground image area to the number of pixels of the monitoring area;
  • F is the number of pixels of the foreground image area
  • N is the number of pixels of the monitoring area
  • R is the ratio of pixels of the monitoring area
  • Step 205 comparing the ratio with a preset threshold
  • the preset threshold is T[k], including a plurality of values arranged in descending order.
  • k is an integer from 0 to K.
  • Step 206 Determine whether the ratio is less than a preset threshold; perform step 207 if the ratio is less than the preset threshold; and perform step 208 if the ratio is greater than or equal to the preset threshold.
  • Step 207 Re-initialize the background model using the current image, that is, perform all updates to the background model using the current image. You can use any method that is initialized by any existing background model.
  • Step 208 Selectively update the background model using the current image. Then, step 202 can be performed to re-acquire the current image of the monitoring area.
  • the update can be selectively performed using a method described later, for example, updating the background model M i to the background model M i+1 .
  • the re-initialization of the background model may be performed if the ratio is less than the preset threshold, that is, all updates are performed; if the ratio is greater than or equal to the preset threshold, the current image is used to the background.
  • the model is selectively updated.
  • step 209 k is incremented by 1, that is, the current preset threshold is changed to the next value.
  • the preset threshold T[k] is used in sequence, and the initial value of k is 0, that is, T[0] is used first, then T[1] is used, ....
  • Step 210 Determine whether k is greater than K, that is, determine whether the preset threshold is all used. Step 211 is performed if the preset threshold has been used all; and step 202 is performed if the preset threshold is not used all, and the current image of the monitoring area is re-acquired.
  • Step 211 The current background model is used as an initial background model of the monitoring area.
  • the M j can be used as the initial background model of the monitoring area, thereby obtaining a relatively accurate initial background model.
  • the initial background model can be continuously updated.
  • the current background model is M 0 , and the number of pixels N in the monitoring area is 1000.
  • the current threshold has been changed to T[3].
  • the image I6 of the monitoring area is acquired, and after the foreground image area is extracted, the number F of pixels of the foreground image area can be known to be 180.
  • R 0.18; comparing R with T[3] shows that R ⁇ T[3] at this time, so the background model is re-initialized using image I6, that is, all updates.
  • the preset threshold has been used all, so the process can be ended.
  • the current background model can also be used as the initial background model for the monitoring area.
  • the background model is updated in a gradual approximation manner, and the background model can be extracted using a more suitable image.
  • FIGS. 1 and 2 only schematically illustrate the case of the present invention, but the present invention is not limited thereto.
  • the order between the steps may be adjusted according to the actual situation, or one step or several steps may be added or subtracted.
  • the background model in step 208, can be selectively updated according to the foreground image region.
  • the foreground image area and the adjacent area may be used as the foreground extended area; the background model is updated according to the area other than the foreground extended area in the current image, and the foreground extended area is not Updated to the background model.
  • FIG. 3 is a schematic diagram of expanding a foreground object area according to an embodiment of the present invention.
  • the foreground image area 302 of the current image 300 except the background image area 301 may be expanded.
  • the foreground image area for example, a moving object
  • the adjacent area are not updated into the background model, the ghost phenomenon can be reduced, and the moving object with a relatively small moving speed can be detected; the image detection accuracy is higher. And the ability to tolerate noise is stronger.
  • the ratio of the number of pixels in the foreground image area to the number of pixels in the monitoring area is calculated; and the background model is initialized if the ratio is less than a preset threshold. Therefore, the background model can be extracted using a more suitable image, the ghost phenomenon in the image detection process can be reduced, and an object with a relatively small moving speed or a certain time can be detected, and the image detection accuracy is higher and the noise is tolerated. The ability is stronger.
  • the embodiment of the present invention provides a device for extracting a background model, and the same content as that of Embodiment 1 will not be described again.
  • the background model extraction apparatus 400 includes:
  • the image obtaining unit 401 acquires a current image of the monitoring area
  • the foreground extracting unit 402 extracts a foreground image region from the current image based on the background model
  • the ratio calculating unit 403 calculates a ratio of the number of pixels of the foreground image region to the number of pixels of the monitoring region;
  • Comparing unit 404 comparing the ratio to a preset threshold
  • the background initializing unit 405 initializes the background model if the ratio is smaller than the preset threshold.
  • the image acquisition unit 401 can obtain the current image according to the video information obtained by the camera.
  • FIG. 5 is another schematic diagram of a background model extraction apparatus according to an embodiment of the present invention.
  • the background model extraction apparatus 500 includes: an image acquisition unit 401, a foreground extraction unit 402, a ratio calculation unit 403, and comparison.
  • Unit 404 and background initialization unit 405 are as described above.
  • the preset threshold is a plurality of values arranged in descending order and used in sequence.
  • the extraction device 500 of the background model may further include:
  • the threshold determining unit 501 determines whether the preset threshold is all used
  • the background determining unit 502 may also use the current background model as an initial background model of the monitoring area if the preset threshold has been used all.
  • the image obtaining unit 401 is further configured to: re-acquire the current image of the monitoring area if the preset threshold is not used.
  • the extraction device 500 of the background model may further include: a background update unit 406; the background update unit 406 may be specifically configured to: if the ratio is greater than or equal to the preset threshold, The background model is selectively updated based on the foreground image region in the current image.
  • the background update unit 406 can include:
  • a foreground extension unit 503 the foreground image area and the adjacent area as a foreground extended area;
  • the background generation unit 504 updates the background model according to an area other than the foreground extended area in the current image, and does not update the foreground extended area into the background model.
  • the ratio of the number of pixels in the foreground image area to the number of pixels in the monitoring area is calculated; and the background model is initialized if the ratio is less than a preset threshold. Therefore, the background model can be extracted using a more suitable image, the ghost phenomenon in the image detection process can be reduced, and the object with a relatively slow moving speed or a certain time can be detected, and the image detection accuracy is higher and the noise is tolerated. The ability is stronger.
  • An embodiment of the present invention provides an image processing apparatus, where the image processing apparatus includes: a background model extraction apparatus according to Embodiment 2.
  • Fig. 6 is a block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention.
  • the image processing apparatus 600 may include a central processing unit (CPU) 100 and a memory 110; the memory 110 is coupled to the central processing unit 100.
  • the memory 110 can store various data; in addition, a program for information processing is stored, and the program is executed under the control of the central processing unit 100.
  • the functionality of the background model's extraction device 400 or 500 can be integrated into the central processor 100.
  • the central processing unit 100 can be configured to implement the background model as described in Embodiment 1. Extraction Method.
  • the extraction device 400 or 500 of the background model may be configured separately from the central processing unit.
  • the extraction device 400 or 500 of the background model may be configured as a chip connected to the central processing unit 100 through the central processing unit. The functions of the extraction device 400 or 500 that implement the background model are controlled.
  • the image processing apparatus 600 may further include: an input and output unit 120, a display unit 130, and the like; wherein the functions of the above components are similar to those of the prior art, and are not described herein again. It is to be noted that the image processing apparatus 600 does not necessarily have to include all of the components shown in FIG. 6; in addition, the image processing apparatus 600 may further include components not shown in FIG. 6, and reference may be made to the related art.
  • Embodiments of the present invention also provide a computer readable program, wherein when the program is executed in an image processing apparatus, the program causes a computer to perform extraction of a background model as described in Embodiment 1 in the image processing apparatus method.
  • the embodiment of the present invention further provides a storage medium storing a computer readable program, wherein the computer readable program causes the computer to execute the extraction method of the background model as described in Embodiment 1 in the image processing device.
  • the above apparatus and method of the present invention may be implemented by hardware or by hardware in combination with software.
  • the present invention relates to a computer readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to cause the logic component to implement the various methods described above Or steps.
  • the present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, or the like.
  • One or more of the functional blocks described in the figures and/or one or more combinations of functional blocks may be implemented as a general purpose processor, digital signal processor (DSP) for performing the functions described herein.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA field programmable gate array
  • One or more of the functional blocks described with respect to the figures and/or one or more combinations of functional blocks may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, multiple microprocessors One or more microprocessors in conjunction with DSP communication or any other such configuration.

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Analysis (AREA)

Abstract

La présente invention concerne un procédé et un appareil d'extraction de modèle d'arrière-plan ainsi qu'un dispositif de traitement d'image. Le procédé d'extraction consiste : à acquérir une image courante d'une zone surveillée ; à extraire une zone d'image d'avant-plan de l'image courante sur la base d'un modèle d'arrière-plan ; à calculer le rapport entre le nombre de pixels dans la zone d'image d'avant-plan et le nombre de pixels dans la zone surveillée ; à comparer le rapport avec un seuil prédéfini ; et à initialiser le modèle d'arrière-plan lorsque le rapport est inférieur au seuil prédéfini. En conséquence, le modèle d'arrière-plan peut être extrait au moyen d'une image relativement appropriée, un phénomène de fantôme se produisant pendant le processus de détection d'image peut être réduit, et des objets ayant une vitesse de déplacement relativement lente ou restant immobiles pendant une certaine période peuvent être détectés, tandis qu'une plus grande précision de détection d'image et une meilleure capacité de tolérance au bruit sont obtenues.
PCT/CN2015/087029 2015-08-14 2015-08-14 Procédé et appareil d'extraction de modèle d'arrière-plan et dispositif de traitement d'image WO2017028029A1 (fr)

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CN108805897A (zh) * 2018-05-22 2018-11-13 安徽大学 一种改进的运动目标检测vibe算法
CN109727274A (zh) * 2018-11-28 2019-05-07 吉林大学 视频处理方法
CN110033425A (zh) * 2018-01-10 2019-07-19 富士通株式会社 干扰区域检测装置及方法、电子设备

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CN103871082A (zh) * 2014-03-31 2014-06-18 百年金海科技有限公司 一种基于安防视频图像的人流量统计方法
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CN101673400A (zh) * 2008-09-08 2010-03-17 索尼株式会社 图像处理设备、方法和程序
CN102821272A (zh) * 2012-08-16 2012-12-12 安徽中科智能高技术有限责任公司 一种清除电梯无效请求信号的视频监控系统
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CN110033425A (zh) * 2018-01-10 2019-07-19 富士通株式会社 干扰区域检测装置及方法、电子设备
CN110033425B (zh) * 2018-01-10 2023-03-28 富士通株式会社 干扰区域检测装置及方法、电子设备
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CN109727274A (zh) * 2018-11-28 2019-05-07 吉林大学 视频处理方法

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