CN105869184A - Forest fire smoke image detection method based on path analysis - Google Patents

Forest fire smoke image detection method based on path analysis Download PDF

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CN105869184A
CN105869184A CN201610206104.7A CN201610206104A CN105869184A CN 105869184 A CN105869184 A CN 105869184A CN 201610206104 A CN201610206104 A CN 201610206104A CN 105869184 A CN105869184 A CN 105869184A
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image
region
smog
forest
computer
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CN105869184B (en
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程朋乐
乔元秀
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Beijing Forestry University
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Beijing Forestry University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G06T2207/20224—Image subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30232—Surveillance

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  • Engineering & Computer Science (AREA)
  • Geometry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Analysis (AREA)
  • Fire-Detection Mechanisms (AREA)

Abstract

The invention discloses a forest fire smoke image detection method based on path analysis. According to different motion paths of different objects under the influence of the atmosphere and inherent features of smoke at a diffusion initial source, through image processing of a background computer, a scope of a motion path angle is obtained, accordingly, whether a fire hazard takes place is determined, such that objectivity of object motion is ensured, image data is converted into mathematic formulas, features of data processing of the computer is fully utilized, and the response speed of the computer is fast. The detection method provided by the invention does not have to additionally process image data of other portions, only processes and analyzes a dynamic area, reduces the computation amount and improves the monitoring efficiency. The method is adapted to interfaces and images of the computer, enables the response of the computer to be more rapid and is applied to long-distance non-contact monitoring of a forest area.

Description

Forest fires smog image detecting method based on path analysis
Technical field
The invention belongs to technical field of image detection, relate to one and utilize ccd video camera that forest fires smog is carried out Detection method, is particularly suitable for the monitoring of remote forest or the monitoring of forest district.
Background technology
In forest fire is investigated, the monitoring of fire is a very important content.Traditional fire detection Often relying on forest ranger, Watchtower carries out manual detection, and its detection range is limited, it is impossible to detect at a distance, and And limited personnel, efficiency comparison is low.The method using video monitoring carries out the noncontact monitoring energy of forest fire The detection region enough making up tradition monitoring method is little, and shortage of manpower the most increasingly comes into one's own.
University of Electronic Science and Technology proposes to judge doubtful smog district with according to color characteristic, and extracts doubtful smog district shape Shape is irregular, area increases, grader is trained by K blurred background feature, differentiates smog with grader (Zhou Xue, Zou Jianxiao, Xu Hongbing, Deng Lin, video smoke detection method based on multi-feature fusion, China Patent: 201510170159.2,2015-4-10.), the characteristic vector that this method calculates is many, and data are loaded down with trivial details, And big to the performance quality dependency of grader, forest is the region of an opening, is affected greatly by geographical conditions, And there is the feature of miniclimate, the generation of smog is also randomness, therefore the training radix of grader big and Substantial amounts of data are difficult to obtain, and can cause data redundancy, are not suitable for detecting the feature of labile state.
Wuxi the Big Dipper communication breath Science and Technology Ltd. proposes a kind of forest smoke region detecting system, this detection System is positioned on unmanned plane, and this system carries out forest detection by accepting the instruction on ground, although can be quick Determine smoke region, but capital expenditure is relatively big, and forest can not aloft be examined in the moment by unmanned plane Survey, and easily ignore narrow regions and the region of special geological surrounding.
Fujitsu Ltd. propose a kind of multiframe to image to be detected carry out feature extraction, it is thus achieved that one or Multiple candidate regions, then analyze the area change in multiple frame, the direction of motion and change of shape, sentence Whether disconnected candidate region exists smog, relates to data various in the method, and processing speed is relatively slow, wherein by institute Select the barycenter of candidate region in the highest direction of motion of the frequency of occurrences as direction of primary motion, but forest environment Changing unpredictably, depend on air motion, the discriminant accuracy of direction of primary motion is indefinite, increases rate of false alarm.
Summary of the invention
Instant invention overcomes the deficiency of above-mentioned technology, it is provided that a kind of forest fires smog image based on path analysis is examined Survey method, its object is to efficient, sensitive, remote, noncontact monitoring forest zone.
The forest fires smog image detecting method based on path analysis of the present invention, is arranged on the CCD of forest zone eminence The video camera moment monitors whole forest farm, and when fire occurs to produce smog, the change in this region is taken the photograph by CCD Camera captures, and gathers the smog image in a period of time, according to the affiliated scope of smog movement path angle Determining whether this region has fire to produce, the method is carried out according to the following steps,
(1) ccd video camera being positioned at forest zone eminence captures the dynamic change in certain region,
(2) ccd video camera gathers the view data of this region a period of time, and is sent to background computer, Carry out Image semantic classification, image be converted into binary image,
(3) image in this region is partitioned into dynamic region of variation by background computer, and is recorded as A,
(4) the coordinate position A of each barycenter in the connected domain of region A is calculated1(x1, y1), A2(x2, y2) depend on Secondary record also preserves,
(5) relatively each center-of-mass coordinate size, and remember that the maximum center-of-mass coordinate of coordinate figure is B0(x0, y0), sit The center-of-mass coordinate of scale value minimum is B1(x1, y1), coordinate figure be second largest center-of-mass coordinate be B2(x2, y2), take B0With B1Between barycenter, line is θ, B with the angle of horizontal direction0With B2Line and the angle of horizontal direction between barycenter For α,
(6) value of θ and α is calculated,
t a n θ = y 0 - y 1 x 0 - x 1 tan α = y 0 - y 2 x 0 - x 2
θ = a r c t a n ( y 0 - y 1 x 0 - x 1 ) × π 3.14 α = a r c t a n ( y 0 - y 2 x 0 - x 2 ) × π 3.14
(7) judge the size of θ and α, and determine scope,
(8) if θ and α is between 0 °～90 °, then background computer window display result: be, otherwise, Show no.
Described forest fires smog image detecting method based on path analysis, utilizes ccd video camera to gather dynamically Area image, different according to different objects motion path under atmospheric effect, and smog is initial in diffusion Feature intrinsic at source, through the image procossing of background computer, draws the scope at motion path angle, thus Determine whether there is fire to produce.
Present invention foundation different objects motion path under atmospheric effect is different, and smog is initial in diffusion Feature intrinsic at source, through the image procossing of background computer, draws the scope at motion path angle, thus Determine whether there is fire to produce, it is ensured that the objectivity of thing movement, view data be converted into mathematical formulae, Make full use of the feature of computer digital animation, make computer fast response time.Detection provided by the present invention Method, it is not necessary to the view data of other parts of extra process, just for Treatment Analysis dynamic area, reduces Operand, improves monitoring efficiency.The present invention adapts with interfaceization and the image conversion of computer so that Computer response is rapider, it is adaptable to remote noncontact monitoring forest zone.
Detailed description of the invention
Forest fires smog image detecting method based on path analysis, is arranged on the ccd video camera moment of forest zone eminence Monitor whole forest farm, when fire occurs to produce smog, the change in this region is captured by ccd video camera, And gather the smog image in a period of time, determine that this region is according to the affiliated scope of smog movement path angle No have fire to produce, and the method is carried out according to the following steps,
(1) ccd video camera being positioned at forest zone eminence captures the dynamic change in certain region,
Double frame differences obtain difference diagram: Dn(i, j)=| In(i, j)-In-1(i, j) |, In, In-1Represent phase in image sequence Two adjacent two field pictures, carry out thresholding and obtain sport foreground region difference image:
M n ( i , j ) = 0 D n ( i , j ) < T I n ( i , j ) D n ( i , j ) &GreaterEqual; T
(2) ccd video camera gathers the view data of this region a period of time, and is sent to background computer, Carry out Image semantic classification, image be converted into binary image,
Image is carried out gray processing process, and carries out greyscale transformation, make the contrast of image increase and be prone to two-value Change processes:
Gray processing: f (i, j)=0.03R (i, j)+0.59G (i, j)+0.11B (i, j)
Greyscale transformation: DB=f (DA)=fDA+fB
By iterative method, image being carried out binary conversion treatment, its step is as follows:
First obtain maximum gradation value and the minimum gradation value of image, be designated as R respectivelymaxAnd Rmin, make threshold value T=(Rmax+Rmin)/2, are divided into two groups of R further according to threshold value T by the average gray value of image1And R2, distinguish afterwards Obtain the average gray value μ of two groups1And μ2, finally obtain new threshold value T=(μ1+μ2)/2, i.e. set T as the overall situation The data of image are divided into two parts with T: the pixel group more than T and the pixel group less than T by threshold value, its In the pixel value of pixel group more than T be set as white, the pixel value of the pixel group less than T is set as black, Wherein white portion is dynamic region of variation,
(3) image in this region is partitioned into dynamic region of variation by background computer, and is recorded as A,
(4) the coordinate position A of each barycenter in the connected domain of region A is calculated1(x1, y1), A2(x2, y2) etc. And record preservation successively,
Barycenter mathematic(al) representation:
(5) relatively each center-of-mass coordinate size, and remember that the maximum center-of-mass coordinate of coordinate figure is B0(x0, y0), sit The center-of-mass coordinate of scale value minimum is B1(x1, y1), coordinate figure be second largest center-of-mass coordinate be B2(x2, y2), take B0With B1Between barycenter, line is θ, B with the angle of horizontal direction0With B2Line and the angle of horizontal direction between barycenter For α,
(6) calculating the value of θ and α, unit employing degree represents,
t a n &theta; = y 0 - y 1 x 0 - x 1 tan &alpha; = y 0 - y 2 x 0 - x 2
&theta; = a r c t a n ( y 0 - y 1 x 0 - x 1 ) &times; &pi; 3.14 &alpha; = a r c t a n ( y 0 - y 2 x 0 - x 2 ) &times; &pi; 3.14
(7) judge the size of θ and α, and determine its scope,
(8) if θ and α is between 0 °～90 °, then background computer window display result: be, otherwise, Show no.

Claims (2)

1. forest fires smog image detecting method based on path analysis, is arranged on the ccd video camera of forest zone eminence Moment monitors whole forest farm, and when fire occurs to produce smog, the change in this region is caught by ccd video camera Grasp, and gather the smog image in a period of time, determine this according to the affiliated scope of smog movement path angle Whether region has fire to produce, and the method is carried out according to the following steps,
(1) ccd video camera being positioned at forest zone eminence captures the dynamic change in certain region,
(2) ccd video camera gathers the view data of this region a period of time, and is sent to background computer, Carry out Image semantic classification, image be converted into binary image,
(3) image in this region is partitioned into dynamic region of variation by background computer, and is recorded as A,
(4) the coordinate position A of each barycenter in the connected domain of region A is calculated1(x1, y1), A2(x2, y2) depend on Secondary record also preserves,
(5) relatively each center-of-mass coordinate size, and remember that the maximum center-of-mass coordinate of coordinate figure is B0(x0, y0), sit The center-of-mass coordinate of scale value minimum is B1(x1, y1), coordinate figure be second largest center-of-mass coordinate be B2(x2, y2), take B0With B1Between barycenter, line is θ, B with the angle of horizontal direction0With B2Line and the angle of horizontal direction between barycenter For α,
(6) value of θ and α is calculated,
tan &theta; = y 0 - y 1 x 0 - x 1 t a n &alpha; = y 0 - y 2 x 0 - x 2
&theta; = arctan ( y 0 - y 1 x 0 - x 1 ) &times; &pi; 3.14 &alpha; = a r c t a n ( y 0 - y 2 x 0 - x 2 ) &times; &pi; 3.14
(7) judge the size of θ and α, and determine scope,
(8) if θ and α is between 0 °～90 °, then background computer window display result: be, otherwise, Show no.
2. forest fires smog image detecting method based on path analysis as claimed in claim 1, its feature exists In, different according to different objects motion path under atmospheric effect, and smog is solid at diffusion starting resource Some features, through the image procossing of background computer, draw the scope at motion path angle, thus judgement are No have fire to produce.
CN201610206104.7A 2016-04-06 2016-04-06 Forest fires smog image detecting method based on path analysis Expired - Fee Related CN105869184B (en)

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Publication number Priority date Publication date Assignee Title
CN108279287A (en) * 2018-02-01 2018-07-13 李绍辉 Smog Quick diffusing system based on the communication technology
CN109410512A (en) * 2018-11-07 2019-03-01 北京林业大学 A kind of smog root node detection method based on least square method
CN109903490A (en) * 2019-03-25 2019-06-18 哈尔滨工程大学 A kind of calculation method of fire evacuation path and instruction system
CN114549442A (en) * 2022-02-14 2022-05-27 常州市新创智能科技有限公司 Real-time monitoring method, device and equipment for moving object and storage medium

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108279287A (en) * 2018-02-01 2018-07-13 李绍辉 Smog Quick diffusing system based on the communication technology
CN108279287B (en) * 2018-02-01 2020-12-18 嘉兴市丰成五金材料股份有限公司 Smoke rapid emission system based on communication technology
CN109410512A (en) * 2018-11-07 2019-03-01 北京林业大学 A kind of smog root node detection method based on least square method
CN109903490A (en) * 2019-03-25 2019-06-18 哈尔滨工程大学 A kind of calculation method of fire evacuation path and instruction system
CN109903490B (en) * 2019-03-25 2020-12-01 哈尔滨工程大学 Fire evacuation path calculation method and indication system
CN114549442A (en) * 2022-02-14 2022-05-27 常州市新创智能科技有限公司 Real-time monitoring method, device and equipment for moving object and storage medium

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