CN109059775A - The method of Edge extraction - Google Patents

The method of Edge extraction Download PDF

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Publication number
CN109059775A
CN109059775A CN201810556247.XA CN201810556247A CN109059775A CN 109059775 A CN109059775 A CN 109059775A CN 201810556247 A CN201810556247 A CN 201810556247A CN 109059775 A CN109059775 A CN 109059775A
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image
rail
laser
brightness
detection
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CN109059775B (en
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张秀峰
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Dalian Minzu University
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Dalian Nationalities University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/028—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness by measuring lateral position of a boundary of the object
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61K—AUXILIARY EQUIPMENT SPECIALLY ADAPTED FOR RAILWAYS, NOT OTHERWISE PROVIDED FOR
    • B61K9/00—Railway vehicle profile gauges; Detecting or indicating overheating of components; Apparatus on locomotives or cars to indicate bad track sections; General design of track recording vehicles
    • B61K9/08—Measuring installations for surveying permanent way
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/22—Measuring arrangements characterised by the use of optical techniques for measuring depth
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • 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
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30164—Workpiece; Machine component

Abstract

This divisional application discloses a kind of method of Edge extraction, belong to detection field, for optimizing the detection and calculating process of rail wear, it is characterized in that: appointing and take the median filtering brightness curve for being distributed pixel in the horizontal direction, brightness step is taken out respectively in the curve peak-peak two sides changes maximum continuity point, the midpoint p and q of two groups of continuity points are taken, distance is as detection template diameter between p and q；Effect is to realize Edge extraction.

Description

The method of Edge extraction
The application is application number 201610765942.8, and applying date 2016-08-30, denomination of invention " examine automatically by rail wear The divisional application of survey method ".
Technical field
The invention belongs to detection fields, are related to a kind of rail wear automatic testing method, in particular to are swashed based on a wordline Light image processing and microprocessor can effectively to detect a kind of rail wear of rail head of rail surface abrasion depth and width automatic Detection method.
Background technique
Railway is the main artery of communications and transportation, compares other means of transportation, and heavy haul railway transport is big with freight volume, at low cost Feature is developed rapidly all over the world.In track equipment, rail is most important building block, and directly receiving train carries Lotus simultaneously guides wheel to run.Whether the state of the art of rail is intact, and can directly affect train safe, flat by defined speed Steady and continual operation.Railway locomotive is that driving force and brake force are transmitted by the frictional force between wheel track, and between wheel track Friction then will lead to the generation of rail wear.With the high speed of locomotive, heavy duty, high density operation, the abrasion of rail will be quick The increase of degree, especially sharp radius curve outer rail medial surface abrasion are particularly acute.
The detection technique of rail wear have passed through monocular of conforming to the principle of simplicity measure ruler class tool detection, digitized instrument detection waited Journey.Currently, there are the main methods such as contact fixture measurement, EDDY CURRENT, optical triangulation in China in terms of Rail Abrasion Detection System, The experience that testing result is often depending on the attitude of detection workman and instrument uses, that there is detection efficiencies is low for these methods, inspection The not high problems of precision are surveyed, the development need of current high speed is had been unable to meet.Although occurring now a kind of using sharp The detection device of light detection rail surface abrasion, but can not achieve accurately step-by-step movement detection, other detection methods are also only stopped Stay in theoretical research level.
Summary of the invention
In order to optimize the detection and calculating process of rail wear, the invention proposes a kind of rail wear sides of detection automatically Method is characterized in that: being acquired the laser image of rail, and is carried out image with complete rail laser light belt image and compare, to sentence Whether disconnected detection rail has abrasion, judges that rail has abrasion, selects and extracts laser image spy relevant to rail wear amount Sign amount, rail wear depth and/or width is calculated.
The utility model has the advantages that the rail laser image that the present invention just acquires is compared with complete image, to judge whether to acquire There is abrasion in the rail in image, and when being judged as abrasion, further characteristic quantity is selected to wear to be calculated, first qualitative to sentence Disconnected abrasion, then the quantitative thinking for calculating abrasion depth and width, and in calculating process, characteristic quantity is selected, with excellent Change the calculating process of abrasion depth and width.
Detailed description of the invention
Fig. 1 is the structural block diagram of rail wear automatic detection device described in embodiment 2；
Fig. 2 is without abrasion laser image schematic diagram；
Fig. 3 is to have abrasion laser image schematic diagram；
Fig. 4 is brightness curve and disk diameter schematic diagram；
Fig. 5 is the label schematic diagram of data point and characteristic quantity.
Specific embodiment
Embodiment 1: a kind of rail wear automatic testing method acquires the laser image of rail, and with complete rail laser Light belt image carries out image comparison, to judge to detect whether rail has abrasion, judges that rail has abrasion, to the laser figure of acquisition As carrying out laser image processing, the laser image processing includes image preprocessing and Edge extraction, laser image processing Afterwards, laser image characteristic quantity relevant to rail wear amount is selected and extracts, rail wear depth and width are calculated.Its In: described to extract laser image characteristic quantity relevant to rail wear amount as one or more of following characteristics amount:
1) the length l of two sections of straight line portions of laser imageAAnd lB；
2) the width difference e of two sections of linear laser images；
3) the lengthwise position difference z of two sections of linear laser images；
4) between two sections of linear laser images changeover portion length lC；
5) between two sections of linear laser images changeover portion inclination angle theta；
Abrasion width and abrasion depth are referred to as the characteristic quantity of rail wear, select one or more laser images among the above Characteristic quantity, for calculating the depth and width of rail wear；
And when calculating the depth and width of rail wear, and non-selection whole above-mentioned laser image characteristic quantity is counted It calculates, in order to optimize calculating process, selects base of the combination of laser image characteristic quantity as the depth and width for calculating rail wear Plinth calculates data, and the method when combination is selected to be: laser image characteristic quantity relevant to the wear characteristics determining first, and from Preferred features amount is selected in laser image characteristic quantity, calculates the degree of correlation system of remaining each laser image characteristic quantity and preferred features amount Number, and be averaged, which is the threshold value beta of characteristic quantity selection, if wherein between certain two laser image feature The absolute value of related coefficient | rTij | >=β, two laser images are characterized in relevant redundancy feature, only select it is one of as The laser image characteristic quantity of rail wear judgement.When combination i.e. in selection for the laser image characteristic quantity of judgement, it is assumed that M is Collected feature samples set is pinpointed on the rail with abrasion, which includes swashing for the reaction abrasion of N number of fixed point Light image characteristic quantity selects correlation coefficient as metric parameter, the parameter be characterized by between similitude, two laser figures As being characterized in relevant redundancy feature, one of laser image characteristic quantity as rail wear judgement is only selected, for finding It can effectively judge the combination of the minimum laser image characteristic quantity of rail wear width and depth.
As one embodiment, correlation coefficient is as metric parameter among the above, to be characterized by the specific of a correlation Method is: being respectively as follows: T using two groups of different laser image features are seti={ tik, k=1,2 ..., n } and Tj={ tjk, k=1, 2 ..., n }, wherein k indicates k-th of test point, shares n test point, then the related coefficient of two groups of laser image features defines such as Under:
In formula,WithRespectively two groups of feature TiAnd TjAverage value:With
Correlation coefficient r TijReflect two groups of feature TiAnd TjDegree of correlation, rTijValue when being negative, indicate two features It is negatively correlated；rTijValue be timing, indicate two features be positively correlated；Work as rTijBe when=0, between two wear characteristics it is incoherent, Work as rTijAbsolute value closer to 1 when, the degree of correlation of two laser image features is higher, and the redundancy of generation is bigger, is reacting In the laser image characteristic set of rail wear, using the related coefficient between each laser image characteristic quantity, threshold value beta is set, if The wherein absolute value of the related coefficient between certain two laser image feature | rTij| >=β, two laser images are characterized in correlation Redundancy feature only selects one of laser image characteristic quantity as rail wear judgement.
In another embodiment, it is for the determination method of threshold value beta described above: special to the laser image that Mr. Yu is single Sign amount chooses it as preferred features, judges that the method for a possibility that remaining laser image characteristic quantity is redundancy feature is: determining After preferred features, by calculate obtain in rail wear width and depth associated laser characteristics of image set with preferred features amount it Between correlation coefficient, set threshold value beta for the mean value of this group of correlation coefficient data, the determination method of threshold value beta is:
Wherein: the quantity of the c amount of being characterized in formula, l are the serial number of preferred characteristic quantity, and j is the serial number of alternative features amount.
Above-described embodiment as a result, a possibility that acquiring the related coefficient between feature to obtain redundancy between feature size, by this Group correlation coefficient data mean value be set as threshold value beta, using this threshold value as judging characteristic whether the foundation of redundancy, thus sentencing When disconnected two feature redundancy, a laser image feature as the depth and width for calculating abrasion between redundancy feature is only selected, To optimize calculating process, minimal features combination is obtained with this.
As one embodiment, the calculation method of specific open abrasion depth and width: two sections of straight line portions of laser image The length l dividedAAs the preferred features of abrasion width detection, the lengthwise position difference z of two sections of linear laser images is deep as abrasion Spend the preferred features of detection；Two straight line portions of laser image are calculated by the related coefficient of two groups of laser image features Length lAAnd lBAs the characteristic quantity of abrasion width detection, the lengthwise position difference z of two sections of linear laser images is as abrasion depth inspection The characteristic quantity of survey wears away width calculation formula are as follows:
Wherein, l is the width without wearing away rail；
Wear away depth calculation formula are as follows:
60 ° of V=ztan
As one embodiment, described image pretreatment includes the following steps:
First by image gray processing, the histogram of gray level image is drawn, gray scale is found out and concentrates range；
Then following formula are used, grey level enhancement is carried out to gray level image, is more clear image；
Wherein: a, b are respectively the left and right boundary point of gray value integrated distribution in gray level image histogram, and x, y are respectively represented Gray value before and after grey level enhancement.
As one embodiment, the method for described image edge extracting, includes the following steps:
Appoint and take the median filtering brightness curve for being distributed pixel in the horizontal direction, in the curve peak-peak two sides point Not Qu Chu brightness step change maximum continuity point, take the midpoint p and q of two groups of continuity points, distance is as detection between p and q Template diameter；
If the brightness of image is f (i, j), take a round s (c, r) as detection template in picture field, wherein c is circle The heart, coordinate are (ic,jc), r is radius；
Define the set of s (c, r) interior pixel, and remember in round s the brightness of pixel and are as follows:
Keep detection template center of circle a small range in the horizontal direction mobile, it is bright to calculate each pixel in the detection template of each position Degree and brightness and maximum template center location, the as bright wisp Pixel-level roof edge point within the scope of this, using most Small square law fitting a straight line, the straight line are a wordline laser picture centre line, and the small range is that a left side is put centered on the center of circle The image interval of right each 2 times of radiuses, to obtain the length l of two sections of straight line portions of laser imageAAnd lB, two sections of linear laser figures The length l of changeover portion as betweenC。
Embodiment 2: as the supplement of 1 technical solution of embodiment, or as a kind of individual embodiment: abrasion are main out The head of present rail, abrasion include top surface abrasion and side wear, and when detection must detect the two numerical value simultaneously, are come comprehensive Close the wear intensity for judging rail.The present embodiment utilizes one word laser beam of high-intensitive narrow beam, laser and a wordline light beam institute It is in 60 ° of angles in plane and tested Rail Surface, high-resolution Array CCD sensor is located at the surface shooting of laser image Laser image.There is bending in the Rail Surface light beam image for there are abrasion, the position occurred by bending point and bending degree Determine the width and depth of rail wear.
Rail wear automatic detection device includes: a wordline laser device, ccd image sensor, microprocessor, executes list Member, display and acousto-optic warning unit and interface unit.Ccd image sensor acquires laser image, image information obtained It is transferred to microprocessor to be analyzed and processed, extracts image border and center and fitting a straight line, form complete rail laser Light belt image outline converts image information into rail profile parameter, stores the characteristic quantity of rail profile, and join with complete rail Number is compared, and judges rail with the presence or absence of abrasion.It does not wear away and continues next point detection；There are abrasion, further determines that Abrasion loss, the depth and width including abrasion.Execution unit receives the control signal of microprocessor, controls the traveling of detection device Direction and speed, adjust the orientation of ccd image sensor, the output end of microprocessor respectively with LCD display and sound-light alarm System connection, LCD display are used to show current location and the wear intensity of rail, and acoustooptic alarm system is for prompting rail to work as There are abrasion in front position, need to repair.Interface unit can be further to abrasion position for exchanging information, host computer with host computer The further fine processing of the image set determines accurately abrasion loss.
Image preprocessing is the pre-processing stage of laser image edge extracting, first by image gray processing, draws gray scale The histogram of image finds out gray scale and concentrates range, and using formula (1), (wherein a, b are respectively gray value in gray level image histogram The left and right boundary point of integrated distribution, x, y respectively represent the gray value before and after grey level enhancement) grey level enhancement is carried out to gray level image, It is more clear image.
The edge detection of a wordline laser image uses " ridge-shaped " edge detection method.Based on single pixel brightness Edge detection method noise resisting ability is poor, in order to reduce the interference of picture noise, pixel brightness each in a certain region and As " ridge-shaped " edge distinguishing rule.Due to circle have it is each to same tropism, do not influenced by ridge-shaped edge direction, therefore, The present invention uses plate way " ridge-shaped " edge detection method.By size disk detection template appropriate in a wordline laser image It is moved in a certain range of two sides, when the change of gradient of the brightness sum of pixel each in template meets certain requirements, template Central point is ridge-shaped marginal point.
Appoint and take the median filtering brightness curve for being distributed pixel in the horizontal direction, in the curve peak-peak two sides point Not Qu Chu brightness step change maximum continuity point, take the midpoint p and q of two groups of continuity points, distance is as detection between p and q Template diameter, as shown in Figure 3.
If the brightness of image is f (i, j), take a round s (c, r) as detection template in picture field, wherein c is circle The heart, coordinate are (ic,jc), r is radius.Define the set of s (c, r) interior pixel:
And remember in round s the brightness of pixel and are as follows:
Keep detection template center of circle a small range in the horizontal direction mobile, it is bright to calculate each pixel in the detection template of each position Degree and brightness and maximum template center location, the as bright wisp Pixel-level roof edge point within the scope of this.Using most Small square law fitting a straight line, the straight line are a wordline laser picture centre line.The straight line of the marginal point and fitting that detect is such as Shown in Fig. 4.
Further extraction and rail wear amount associated laser image feature amount, selection method and threshold value including characteristic quantity It determines.
The invention mainly relates to rail wear width and depth, steel can be determined by the bending degree of laser image The width and depth of rail abrasion, have following characteristic quantity to can be used for selecting:
1) the length l of two sections of straight line portions of laser imageAAnd lB；
2) the width difference e of two sections of linear laser images；
3) the lengthwise position difference z of two sections of linear laser images；
4) between two sections of linear laser images changeover portion length lC；
5) between two sections of linear laser images changeover portion inclination angle theta.
One or more features amount be can choose for judging the depth and width of rail wear, in selection for judgement When the combination of characteristic quantity, it is desirable that different category features have marked difference, avoid redundancy feature interference judgement.Assuming that M is that have Collected feature samples set is pinpointed on the rail of abrasion, which includes the wear characteristics of n fixed point.Select the degree of correlation Coefficient as metric parameter, the parameter can be characterized by between similitude, for find can effectively judge that rail wear is wide The combination of the minimal features amount of degree and depth.If two groups of different wear characteristics are respectively as follows: Ti={ tik, k=1,2 ..., n } and Tj={ tjk, k=1,2 ..., n }, wherein k indicates k-th of test point, shares n test point, then the related coefficient of two groups of features It is defined as follows:
(3)
In formula,WithRespectively two groups of feature TiAnd TjAverage value:With
Correlation coefficient r TijReflect two groups of feature TiAnd TjDegree of correlation, rTijValue when being negative, indicate two features It is negatively correlated；Value is timing, indicates that two features are positively correlated.Work as rTijIt is incoherent between two features when=0.Then work as rTij Absolute value closer to 1 when, indicate that the degree of correlation of two features is higher, issuable redundancy is bigger at this time.
In the characteristic set of rail wear, using the related coefficient between each characteristic quantity, threshold value beta is set, if wherein certain The absolute value of related coefficient between two features | rTij| >=β illustrates that the two are characterized in relevant redundancy feature, can only select One of characteristic quantity as rail wear judgement.
To Mr. Yu's single features, and the direct relation of rail wear depth and width is bigger, judgment method is simpler, uses It is higher in the feasibility for judging abrasion loss, be selected a possibility that it is bigger, selected feature is as preferred features.Judge a certain A possibility that feature is redundancy feature, according to the correlation of itself and preferred features, correlation is higher, then becomes relevant redundancy feature A possibility that it is bigger.After determining preferred features, by calculate obtain in rail wear width and depth correlated characteristic set with The mean value of this group of data is set threshold value beta by correlation coefficient between preferred features amount, as shown in formula (4):
After determining characteristic quantity, the rail wear amount of detection position is calculated, is stored and shown have starting when wearing away of transfiniting Acoustic-optic alarm.
Interface unit can be further to abrasion position for exchanging information, host computer with host computer in off-line case The further fine processing of image determines accurately abrasion loss.Due to the adoption of the above technical scheme, a kind of steel provided in this embodiment Rail, which wears away automatic detection device, has such beneficial effect, due to the method using image procossing, in the control of microprocessor Under, be detached from the control of PC machine, device can under the setting of operator automatic running.Equipment has certain integrity and actual effect Property, it is not only easy to operate, testing result is accurate convenient for the use of testing staff, and also manufacturing cost is low.
The preferable specific embodiment of the above, only the invention, but the protection scope of the invention is not It is confined to this, anyone skilled in the art is in the technical scope that the invention discloses, according to the present invention The technical solution of creation and its inventive concept are subject to equivalent substitution or change, should all cover the invention protection scope it It is interior.

Claims (1)

1. a kind of method of Edge extraction, which comprises the steps of:
Appoint and take the median filtering brightness curve for being distributed pixel in the horizontal direction, is taken respectively in the curve peak-peak two sides Brightness step changes maximum continuity point out, takes the midpoint p and q of two groups of continuity points, distance is as detection template between p and q Diameter；
If the brightness of image is f (i, j), take a round s (c, r) as detection template in picture field, wherein c is the center of circle, Coordinate is (ic,jc), r is radius；
Define the set of s (c, r) interior pixel, and remember in round s the brightness of pixel and are as follows:
Keep detection template center of circle a small range in the horizontal direction mobile, calculates each pixel intensity in the detection template of each position With brightness and maximum template center location, the as bright wisp Pixel-level roof edge point, utilize minimum within the scope of this Square law fitting a straight line, the straight line are a wordline laser picture centre line, and the small range is point or so centered on the center of circle The image interval of each 2 times of radiuses, to obtain the length l of two sections of straight line portions of laser imageAAnd lB, two sections of linear laser images Between changeover portion length lC。
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