WO2016147899A1 - Dispositif pour détection de crochets de suspension par traitement d'image - Google Patents

Dispositif pour détection de crochets de suspension par traitement d'image Download PDF

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Publication number
WO2016147899A1
WO2016147899A1 PCT/JP2016/056715 JP2016056715W WO2016147899A1 WO 2016147899 A1 WO2016147899 A1 WO 2016147899A1 JP 2016056715 W JP2016056715 W JP 2016056715W WO 2016147899 A1 WO2016147899 A1 WO 2016147899A1
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WIPO (PCT)
Prior art keywords
image
gsth
hanger
line sensor
line
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PCT/JP2016/056715
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English (en)
Japanese (ja)
Inventor
庭川　誠
勇介 渡部
匠朗 川畑
Original Assignee
株式会社 明電舎
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Application filed by 株式会社 明電舎 filed Critical 株式会社 明電舎
Priority to CN201680015092.8A priority Critical patent/CN107428261B/zh
Priority to SG11201707279TA priority patent/SG11201707279TA/en
Priority to MYPI2017703343A priority patent/MY186370A/en
Publication of WO2016147899A1 publication Critical patent/WO2016147899A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60M—POWER SUPPLY LINES, AND DEVICES ALONG RAILS, FOR ELECTRICALLY- PROPELLED VEHICLES
    • B60M1/00—Power supply lines for contact with collector on vehicle
    • B60M1/12—Trolley lines; Accessories therefor
    • B60M1/28—Manufacturing or repairing trolley lines
    • 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

Definitions

  • the present invention relates to a hanger detection device by image processing that detects a hanger by image processing and detects a travel position of a train car and an angle abnormality of the hanger.
  • a railway operator records a train track while traveling and specifies the traveling position of the train from the recorded image.
  • GPS and ATC technologies for identifying the location of trains.
  • these technologies are accurate enough not to interfere with train operation, but when train locations are identified from images. Therefore, it is required to grasp the traveling position more accurately.
  • Patent Documents 1 and 2 are known as techniques for detecting hangers.
  • Patent Document 1 is a patent that detects hangers from captured images by template matching processing or vertical edge detection processing.
  • Patent Document 2 is a patent for detecting a hanger by detecting an intersection of two straight lines from a captured image by detecting a Hough transform process, a luminance histogram process, or two straight lines.
  • Patent Documents 1 and 2 are capable of detecting hangers as long as they have a simple line configuration. However, as shown in FIG. It is difficult to detect the hanger 6 at a location where 5 intersects.
  • Patent document 1 detects a hanger by vertical edge detection. In general edge detection, a portion having a large differential value between 2 pixels is detected as an edge. The local detection of 2 pixels has a problem with many false detections.
  • Patent document 2 is a patent which detects a hanger by Hough transformation. The Hough transform finds a hanger using a relative vote amount between the feature of the entire image and the hanger feature, so it is difficult to detect the hanger 6 that appears small relative to the entire image as shown in FIG.
  • Patent Document 3 As a related patent. This is an invention for measuring wear of a trolley wire, and is a patent for robustly detecting a worn portion of a trolley wire by removing the background by GSTH processing (see FIGS. 4 and 5).
  • the GSTH process of Patent Document 3 is characterized in that the illumination light on the lower surface of the trolley wire is reflected in white. Since there is no part which reflects white in the hanger which is the object of this case, it is difficult to detect the hanger using Patent Document 3.
  • an object of the present invention is to provide a hanger detection device using image processing that can detect a hanger with higher accuracy.
  • a hanger detection device by image processing according to the first invention for solving the above-mentioned problems is A line sensor camera for photographing a hanger that is installed at equal intervals and supports a trolley line from the roof of the vehicle, and an image processing unit that is installed inside the vehicle and analyzes an image obtained by the line sensor camera, A hanger detection device by image processing for detecting a hanger in an image, The image processing unit A GSTH processing unit that sequentially performs GSTH processing on a line sensor image input from the line sensor camera in a shooting line direction and a time direction of the line sensor camera to obtain a GSTH image in which the hanger in the image is emphasized; , And a hanger detector for detecting a hanger from the GSTH image.
  • the GSTH processing unit obtains a first GSTH image by performing an expansion process on the line sensor image after performing a contraction process on the imaging line direction of the line sensor camera as the GSTH process, and acquiring the first GSTH image.
  • a difference image is obtained by taking a difference between the image and the first GSTH image, and after the shrinkage process is performed on the difference image in the time direction, the expansion process is performed to emphasize the hanger in the line sensor image Get a second GSTH image, The hanger detection unit detects the hanger from the second GSTH image.
  • the GSTH processing unit obtains a gsth image by performing only a contraction process on the line sensor image in the photographing line direction of the line sensor camera, and acquires a gsth image in the time direction on the gsth image.
  • the GSTH image in which the hanger in the line sensor image is emphasized by performing an expansion process after performing The hanger detection unit detects the hanger from the GSTH image.
  • the hanger detection apparatus by the image processing which concerns on 4th invention is the invention in any one of 1st to 3rd.
  • the GSTH processing unit inverts the luminance value for the line sensor image, one line at a time for the shooting line direction of the line sensor camera, and the luminance value of the main component in the shooting line direction when the luminance value of the main component is light color. When the value is a dark color, the GSTH process is performed after the luminance inversion process that does not invert the luminance value.
  • FIG. 10 is a schematic diagram illustrating an example in which the image shown in FIG. 9 is subjected to GSTH processing in a region long in the x direction. It is a schematic diagram which shows the image which took the difference of the image shown in FIG. 9, and the image shown in FIG.
  • FIG. 12 is a schematic diagram illustrating an example in which the image shown in FIG. 11 is subjected to GSTH processing in a region long in the y direction. It is a flowchart which shows the flow of the hanger detection in Example 2 of this invention.
  • the process denoted as GSTH process indicates that the expansion process illustrated in FIG. 5 is performed after the contraction process illustrated in FIG. 4, and the process denoted as gsth process is a process obtained by simplifying the GSTH process. It is assumed that only the contraction process shown in FIG. 4 is performed without performing the expansion process shown.
  • the hanger detection apparatus using image processing in this embodiment includes a line sensor camera 2 installed on the roof of a train vehicle 1 and an image processing unit 3 installed inside the vehicle 1. ing.
  • the trolley wire 4 is supported by a plurality of hangers 6 that are installed on the platform wire 5 at approximately equal intervals.
  • the line sensor camera 2 is installed on the side of the roof of the vehicle 1, the installation angle and the elevation angle so that the optical axis thereof is orthogonal to the traveling direction of the vehicle 1 and one hanger 6 is contained in the field of view. Is set.
  • an alternate long and short dash line in FIG. 1 indicates a photographing line.
  • An image I (hereinafter referred to as a line sensor image) I as shown in FIG. 8 acquired by the line sensor camera 2 is input to the image processing unit 3.
  • the trolley line 4, the overhead line 5, and the four hangers 6 are displayed in the line sensor image I.
  • the image processing unit 3 analyzes the line sensor image I and detects the hanger 6, and includes an arithmetic device 31 and a recording device 32.
  • the arithmetic unit 31 includes a GSTH processing unit 31a, a hanger detection unit 31b, and a memory 31c.
  • the GSTH processing unit 31a performs image luminance inversion processing on the line sensor image I based on the parameters input from the recording device 32 via the memory 31c and the line sensor image I input from the line sensor camera 2 via the memory 31c. And GSTH treatment.
  • the image luminance inversion processing is processing for inverting the luminance value for each line in the x direction with respect to the line sensor image I. However, if the luminance value of the main component in the x direction is dark, it is determined that the night or a tunnel, and luminance inversion processing is not performed.
  • the GSTH process is a gray scale-top hat process (Gray Scale-Top Hat process). As the name implies, the top hat process is applied to a gray scale image.
  • the Top Hat process is a process of subtracting an opening image (an image subjected to a contraction process and an expansion process for the same number of times) from the original image.
  • GSTH processing by the GSTH processing unit 31a will be briefly described with reference to FIGS.
  • GSTH processing is performed according to the following flow.
  • a range of N pixels three pixels in FIG. 3
  • Shrinkage processing is performed by writing the luminance value of the darkest pixel to another buffer (shrinkage processing buffer) 12-m while shifting to create a shrinkage processed image 12 (12-M).
  • GSTH image (transformed image) I D as shown in FIG. 12 GSTH processing has been performed is input through the memory 31c to the hanger detection unit 31b.
  • the hanger detection unit 31b detects the hanger 6 by binarization processing or the like based on the parameters input from the recording device 32 via the memory 31c and the converted image input from the GSTH processing unit 31a via the memory 31c.
  • the installed hangers 6 are installed at predetermined equal intervals (distances)
  • the position in the image can be grasped by counting the number of detected hangers 6.
  • only the hanger 6 installed vertically is detected in this embodiment, and the inclined hanger 6 is not detected.
  • the number of hangers 6 between the utility poles is managed in advance as equipment data. Therefore, by separately interlocking with the utility pole detection signal, when the number of hangers 6 for each utility pole is small, it can be detected as the hangers 6 having an abnormal angle.
  • Information on the hanger 6 detected by the hanger detection unit 31b is output to the memory 31c as a hanger detection result.
  • the memory 31c temporarily stores various data. Various data are stored in the recording device 32. Note that the parameters described above are the number of pixels N for setting the search range, the number of pixels w and h required when performing GSTH processing, the binarization threshold value, and the like.
  • a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S1).
  • the x direction shown in FIG. 8 corresponds to the photographing line of the line sensor camera 2 in FIG.
  • the y direction shown in FIG. 8 is the time taken by the line sensor camera 2 line by line.
  • An image taken from the vehicle 1 traveling at a constant speed is as shown in FIG.
  • the GSTH processing unit 31a performs a process of inverting the luminance value for the line sensor image I (step S2).
  • the luminance inversion is processed for each line in the x direction of the line sensor image I, and when the luminance value of the main component in the x direction is dark, it is determined as nighttime or tunnel and the luminance is not inverted.
  • the tunnel portion shown in the upper part of FIG. 8 whose background is a dark color can be assimilated with a section whose background such as the sky is a light color.
  • Step S3 the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w ⁇ 1 [pixel] long in the x direction is performed, and the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed.
  • a first GSTH image I B of white points as shown in FIG. 10 are extracted for the following width w x direction.
  • w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally.
  • the first GSTH image I B is hangers 6 and telephone poles and structures such as buildings against inverted luminance image I A (hereinafter, a disturbance hereinafter) has a picture 7 is removed .
  • the GSTH processing unit 31a similarly subtracts the first GSTH image I B from the luminance inverted image I A to obtain a difference image I C as shown in FIG. 11 (step S4).
  • the difference image I C is an image in which the hanger 6 and the disturbance 7 such as a utility pole or a building are extracted.
  • region which becomes negative by a difference process is made, 0 or less shall be rounded up to 0.
  • the difference image I C is GSTH processed in the y direction in the GSTH processing unit 31a (step S5). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 ⁇ h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed.
  • an image (hereinafter referred to as a second GSTH image) ID in which the white portion is extracted in the y direction and with a length of h or less is obtained.
  • h corresponds to the diameter of the hanger 6 and is calculated experimentally.
  • the second GSTH image I D is an image in which only the hangers 6 are extracted to the difference image I C.
  • the second GSTH image ID is input as a converted image to the hanger detector 31b via the memory 31c.
  • step S6 the hanger detection unit 31b, the second GSTH image I D shown in FIG. 12, for detecting the hanger 6 using binarization process or the like. Since the installed hangers 6 are installed at predetermined equal intervals (distances), the number of detected hangers 6 is counted to grasp the position in the image.
  • Step P1 to Step P6 The above processing from Step P1 to Step P6 is performed until the input of all the line sensor images I is completed.
  • the GSTH processing is a combination of the shrinkage processing shown in FIG. 4 and the expansion processing shown in FIG.
  • the hanger detection apparatus using image processing according to the present embodiment has the following advantages that make use of the features of GSTH. -Only the hanger 6 reflected in a predetermined direction and a predetermined thickness can be detected.
  • the hanger 6 can be detected by eliminating the disturbance 7 having characteristics different from those of the hanger 6 such as the tunnel wellhead and the utility pole 7.
  • the abnormal hanger 6 can also be detected by comparing the number of hangers 6 detected in the present embodiment with the number of normal hangers 6 for each utility pole that is managed in advance as facility data.
  • the hanger detection apparatus using image processing according to the present embodiment is different from the first embodiment in that the processing in the GSTH processing unit 31a is simplified.
  • the apparatus configuration is the same as that of the hanger detection apparatus based on image processing according to the first embodiment, and the description thereof will be omitted below, focusing on the processing in the image processing unit 3.
  • a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S11), and then In the GSTH processing unit 31a, the line sensor image I is subjected to a process of inverting the luminance value for a photographing line whose main component luminance value is light in the x direction (step S12). This gives inverted luminance image I A, as shown in FIG.
  • step S13 gsth processing the luminance reversed image I A shown in FIG. 8 the x-direction. That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w ⁇ 1 [pixel] long in the x direction is performed, while the expansion process shown in FIG. 5 for acquiring the brightest pixel is not performed. As a result, a gsth image I C in which white portions as shown in FIG. 11 are extracted with a width w or less in the x direction is obtained. Note that w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally.
  • the GSTH processing unit 31a similarly performs GSTH processing on the gsth image I C in the y direction (step S14). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 ⁇ h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed. As a result, as shown in FIG. 12, a GSTH image ID in which white portions are extracted in the y direction and with a length equal to or shorter than h is obtained. Note that h corresponds to the diameter of the hanger 6 and is calculated experimentally.
  • the GSTH image ID is input as a converted image to the hanger detector 31b via the memory 31c.
  • the hanger detection unit 31b detects the hanger 6 from the GSTH image ID shown in FIG. 12 using binarization processing or the like (step S15). Since the hangers 6 are installed at a predetermined interval (distance), the current position of the vehicle 1 is grasped by counting the detected hangers 6, and the installation angle of the hangers 6 has a management value. Inspect whether the installation angle is.
  • Step P11 to Step P15 The above processing of Step P11 to Step P15 is performed until the input of all the line sensor images I is completed.
  • the luminance inversion image I A is subjected to gsth processing in the x direction (only the contraction processing shown in FIG. 4 is performed), thereby simplifying the processing. Therefore, there is an advantage that the hanger detection processing can be speeded up as compared with the first embodiment.
  • the hanger 6 detected on the image is shortened by performing the gsth process, the present embodiment is intended to determine whether or not the hanger 6 is present. Absent.
  • the present invention is suitable for application to a hanger detection apparatus using image processing.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Manufacturing & Machinery (AREA)
  • Mechanical Engineering (AREA)
  • Image Processing (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Analysis (AREA)

Abstract

Dispositif de détection de crochets de suspension par traitement d'image détectant des crochets de suspension (6) dans une image, et équipé : d'une caméra à capteur linéaire(2) qui capture une image de crochets de suspension (6) à partir du toit d'un véhicule (1), les crochets de suspension (6) étant installés selon un espacement égal et supportant une ligne de chariot (4) ; et d'une unité de traitement d'image (3) qui est installée dans le véhicule (1) et analyse l'image obtenue par la caméra à capteur linéaire (2). Le dispositif de détection de crochets de suspension est conçu de telle sorte que l'unité de traitement d'image (3) est doté : d'une unité de traitement par top-hat à échelle de gris (31a) qui soumet séquentiellement chaque image de capteur linéaire entrée depuis la caméra à capteur linéaire (2) au traitement par top-hat à échelle de gris dans la direction linéaire d'imagerie et dans la direction temporelle de la caméra à capteur linéaire (2) et acquiert une image top-hat à échelle de gris où les crochets de suspension (6) de l'image sont mis en évidence ; et d'une unité de détection (31b) de crochets de suspension qui détecte les crochets de suspension (6) à partir de l'image top-hat à échelle de gris.
PCT/JP2016/056715 2015-03-13 2016-03-04 Dispositif pour détection de crochets de suspension par traitement d'image WO2016147899A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN201680015092.8A CN107428261B (zh) 2015-03-13 2016-03-04 基于图像处理的吊钩检测装置
SG11201707279TA SG11201707279TA (en) 2015-03-13 2016-03-04 Device for hanger detection by image processing
MYPI2017703343A MY186370A (en) 2015-03-13 2016-03-04 Device for hanger detection by image processing

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JP2015-050139 2015-03-13
JP2015050139A JP6427797B2 (ja) 2015-03-13 2015-03-13 画像処理によるハンガー検出装置

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CN (1) CN107428261B (fr)
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SG (1) SG11201707279TA (fr)
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JP6644720B2 (ja) * 2017-01-20 2020-02-12 公益財団法人鉄道総合技術研究所 電車線金具検出システム及びその検出方法
JP7043761B2 (ja) * 2017-09-06 2022-03-30 株式会社明電舎 電柱距離測定装置
JP6920979B2 (ja) * 2017-12-25 2021-08-18 株式会社明電舎 架線金具検出装置及び方法
CN109019335B (zh) * 2018-09-04 2019-10-11 大连理工大学 一种基于深度学习的吊装安全距离检测方法
JP7299041B2 (ja) * 2019-03-13 2023-06-27 株式会社明電舎 架線金具検出装置および架線金具検出方法
JP2020149286A (ja) * 2019-03-13 2020-09-17 株式会社明電舎 架線金具検出装置および架線金具検出方法
CN112150544B (zh) * 2020-09-24 2024-03-19 西门子（中国）有限公司 吊钩到位检测方法、装置和计算机可读介质

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JP2010285054A (ja) * 2009-06-11 2010-12-24 Meidensha Corp 電気鉄道保守用車両位置測定装置
WO2013002047A1 (fr) * 2011-06-30 2013-01-03 株式会社 明電舎 Appareil pour mesurer l'abrasion de fils métalliques de chariot utilisant un procédé d'imagerie

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JP4635657B2 (ja) * 2005-03-11 2011-02-23 株式会社明電舎 画像処理によるトロリ線摩耗測定装置
JP2007271446A (ja) * 2006-03-31 2007-10-18 Meidensha Corp 画像処理によるトロリ線摩耗測定装置
CN101562691B (zh) * 2008-04-17 2010-12-08 鸿富锦精密工业（深圳）有限公司 图像处理装置及方法
CN201534503U (zh) * 2009-06-15 2010-07-28 湖南科创信息技术股份有限公司 接触网关键部位动态偏移量检测装置
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JP2010285054A (ja) * 2009-06-11 2010-12-24 Meidensha Corp 電気鉄道保守用車両位置測定装置
WO2013002047A1 (fr) * 2011-06-30 2013-01-03 株式会社 明電舎 Appareil pour mesurer l'abrasion de fils métalliques de chariot utilisant un procédé d'imagerie

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TW201636572A (zh) 2016-10-16
MY186370A (en) 2021-07-18
SG11201707279TA (en) 2017-10-30
TWI597471B (zh) 2017-09-01
JP2016168937A (ja) 2016-09-23
CN107428261B (zh) 2019-12-24
CN107428261A (zh) 2017-12-01
JP6427797B2 (ja) 2018-11-28

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