WO2023279966A1 - Procédé et appareil de détection de ligne à plusieurs voies, et dispositif de détection - Google Patents

Procédé et appareil de détection de ligne à plusieurs voies, et dispositif de détection Download PDF

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Publication number
WO2023279966A1
WO2023279966A1 PCT/CN2022/100542 CN2022100542W WO2023279966A1 WO 2023279966 A1 WO2023279966 A1 WO 2023279966A1 CN 2022100542 W CN2022100542 W CN 2022100542W WO 2023279966 A1 WO2023279966 A1 WO 2023279966A1
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Prior art keywords
straight line
line segments
lane
line segment
image
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PCT/CN2022/100542
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English (en)
Chinese (zh)
Inventor
李�杰
李森
张尉
马坤
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中移(上海)信息通信科技有限公司
中移智行网络科技有限公司
中国移动通信集团有限公司
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Publication of WO2023279966A1 publication Critical patent/WO2023279966A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road

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  • the present invention relates to the technical field of image processing, in particular to a multi-lane detection method, device and detection equipment.
  • the present application provides a multi-lane line detection method, device and detection equipment, which are used to solve the problem that in the prior art, all the lane lines cannot be detected at one time, and the vehicles on the road will block the lane lines and thus affect the The detection effect, some identifiers and signs on the road will be falsely detected as lane lines.
  • the present application provides a multi-lane line detection method, including:
  • Determining the lane line according to the straight line segment obtained after the second merging process includes:
  • the straight line segments obtained after the second merging process are determined as lane lines.
  • the filtering out non-lane lines according to the position information corresponding to a plurality of straight line segments in each frame image includes:
  • the non-lane lines in the multiple straight line segments are screened out.
  • the filtering out non-lane lines in the multiple straight line segments according to the slopes of the multiple straight line segments in each frame of image and the first angle includes:
  • ⁇ is the first angle
  • ⁇ is the slope of the straight line segment
  • the first merging process and/or the second merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • the preset condition is:
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • the step of determining the lane line according to the straight line segment obtained after the second merging process it further includes:
  • the present application also provides a multi-lane detection device, including:
  • the extraction module is configured to extract several frame images from the video of the road with multi-lane lines;
  • a processing module configured to perform binarization processing and edge detection on each frame of image to obtain a plurality of straight line segments in each frame of image
  • the filtering module is configured to filter out non-lane lines according to the position information corresponding to a plurality of straight line segments in each frame of image;
  • the first merging module is configured to perform the first merging process on the straight line segments located on the same straight line among the multiple straight line segments obtained after screening in each frame of image;
  • the second merging module is configured to perform the second merging process on the straight line segments obtained after the first merging process in all frame images;
  • the determination module is configured to determine the lane line according to the straight line segment obtained after the second merging process
  • the determination module includes:
  • the determination unit is configured to determine, among the straight line segments obtained after the second merging process, the number of the combined straight line segments obtained after the first merging process is greater than a preset threshold value as the lane line.
  • the screening module includes:
  • an angle unit configured to determine a first angle formed between the shooting direction of the video and the direction of the road;
  • the filtering unit is configured to filter out non-lane lines in the multiple straight line segments in each frame of image according to the slopes of the multiple straight line segments and the first angle.
  • the screening unit includes:
  • the first subunit is configured such that if the slope of a line segment meets the first angle: then retain the straight line segment;
  • the second subunit is configured such that if the slope of a line segment meets the first angle: Then filter out the straight line segment;
  • ⁇ is the first angle
  • ⁇ is the slope of the straight line segment
  • the first merging process and/or the second merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • the preset condition is:
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • it also includes:
  • the third merging module is configured to merge two straight line segments whose distance is smaller than a preset distance into one straight line segment as a final lane line.
  • the present application also provides a detection device, including a memory, a processor, and a computer program stored on the memory and operable on the processor; when the processor executes the computer program, the above-mentioned Any multi-lane line detection method.
  • the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in any one of the above multi-lane detection methods are implemented.
  • multi-frame images in the road video are extracted to detect multi-lane lines, and the mutual complementation and mutual verification between multi-frame images is used to avoid the missed detection caused by vehicles blocking the lane lines. It prevents non-lane lines such as pavement symbol signs and text signs from being misdetected as lane lines, and improves the accuracy of lane line detection.
  • FIG. 1 is a schematic flowchart of a multi-lane detection method provided in Embodiment 1 of the present application;
  • Fig. 2 is the result figure after the image in embodiment one of the present application is binarized
  • Fig. 3 is the result figure after edge detection is performed on the image in Embodiment 1 of the present application;
  • FIG. 4 is a schematic structural diagram of a multi-lane detection device in Embodiment 2 of the present application.
  • FIG. 5 is a schematic structural diagram of a detection device in Embodiment 3 of the present application.
  • FIG. 1 is a schematic flowchart of a multi-lane detection method provided in Embodiment 1 of the present application. The method includes the following steps:
  • Step 11 Extract several frames of images from the video of the road with multiple lanes.
  • a video of a certain road is captured first, and the road captured in the video has multiple lane lines, and then the continuous frames of the acquired video are analyzed, and several frames of images are extracted from the video; optionally, When extracting, several frames of images can be extracted at intervals from consecutive frames, and the size of the interval and the specific number of frames to be extracted can be adjusted according to the specific conditions of the road and traffic.
  • the vehicles driving on the road usually form certain occlusions to the lane lines, which makes the detection of the occluded lane lines more difficult. At the same time, if there are symbols, text signs, etc.
  • the discrimination can be realized according to the number of straight line segments appearing in several frames of images.
  • Using the method of mutual verification and complementarity between multiple frames of images can make the lane line detection results more complete and accurate, so that the lane lines existing on the road can be completely detected, and at the same time, the interference objects that do not belong to the lane line can be effectively eliminated.
  • Step 12 Perform binarization processing and edge detection on each frame of image to obtain multiple straight line segments in each frame of image.
  • each frame of images may be preprocessed first.
  • the preprocessing may include: performing distortion correction on each frame of image according to the camera parameters of the camera that shoots the road video, so as to prevent the straight lines on the road from appearing non-linear in the image due to distortion; the preprocessing may also Including: According to the spatial position relationship of the camera's installation position, height, angle, etc. relative to the captured road, the approximate image range of the road in each frame of image is obtained through geometric calculation, and the image region of interest (region) is set according to this range.
  • the follow-up process can only process the region of interest in the image, which can save computing time;
  • the preprocessing can also include: converting each frame of image into grayscale through the color image to grayscale image formula Image, because the color image and grayscale image have little influence on the detection effect, and the multi-channel image becomes a single channel, which is beneficial to speed up image processing.
  • each frame of image can be binarized, that is, binary Value-based segmentation, for example: given a threshold, the pixels in the image whose grayscale is higher than this threshold are assigned a value of 255, and the pixels lower than or equal to this threshold are assigned a value of 0.
  • the key of binarization segmentation lies in the determination of the threshold value.
  • the threshold value such as image gray level average method, etc.
  • the result after binarization processing is shown in Figure 2.
  • the image may also be filtered to improve the effect of image edge detection in the next step.
  • FIG. 3 is a result diagram of edge detection performed on the image in Embodiment 1 of the present application.
  • edge detection is further performed on the image, and the result after the edge detection is shown in FIG. 3 .
  • the straight line segment of the vector can be obtained by means of straight line fitting, so as to obtain multiple straight line segments in each frame of the image, and the obtained after fitting
  • Step 13 Filter out non-lane lines according to the position information corresponding to multiple straight line segments in each frame of image.
  • the straight line segment fitted after edge detection are obviously not lane lines, for example, the lane line is consistent with the direction of the road, if the angle between the direction of the straight line segment and the direction of the road exceeds a certain value, the straight line segment is considered It is obviously not a lane line.
  • some straight line segments that are obviously not a lane line may be screened out according to the position information corresponding to multiple straight line segments in each frame of image.
  • the filtering out the non-lane lines according to the position information corresponding to the multiple straight line segments in each frame image includes:
  • the non-lane lines in the multiple straight line segments are screened out.
  • the position information corresponding to the straight line segment can include the position/coordinate of the straight line segment in the image, and the slope of the straight line segment.
  • the determination of the slope threshold is related to The orientation relationship between the camera that shoots the video and the road is related. Therefore, the first angle formed between the shooting direction of the video and the direction of the road to be shot is determined, and part of the straight line segments can be screened out according to the slope of each straight line segment and the relationship between the first angle.
  • the filtering out non-lane lines in the multiple straight line segments according to the slopes of the multiple straight line segments in each frame of image and the first angle includes:
  • ⁇ is the first angle
  • ⁇ is the slope of the straight line segment
  • ⁇ be the first angle formed between the shooting direction of the video and the direction of the road being shot
  • ⁇ be the slope of multiple straight line segments fitted in each frame of image
  • the angle of the straight line segment is calculated by the arc tangent arctan, and then the angular relationship between the first angle ⁇ and the straight line segment is limited by the tangent value, so that some straight line segments that are obviously not lane lines can be screened out.
  • Step 14 Perform the first merging process on the straight line segments located on the same straight line among the multiple straight line segments obtained after filtering in each frame of image.
  • the edge fitting of the solid line lane lines is a complete straight line segment, that is, a solid line
  • the edge of a lane line corresponds to a straight line segment; while each small segment of a dashed lane line will be fitted with a straight line segment, that is, the edge of a dashed lane line will correspond to multiple straight line segments, in fact, these straight line segments are all on the same line Therefore, in the detection process, these straight line segments that are actually on the same straight line need to be merged.
  • the first merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • the basis for merging is that for every two straight line segments, if the rotation angles and distances of the two straight line segments are very close, it can be determined that the two straight line segments are on the same straight line, and the two straight line segments can be combined segments are merged.
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • the endpoints of the merged straight line segment can be the two endpoints farthest from the endpoints (four endpoints in total) of the two straight line segments before the merge, and the above-mentioned merge process is repeated until the dotted lane line corresponds to All the straight line segments lying on the same straight line are connected.
  • a vector-type storage container may be created to store the straight line segment processed from each frame of image.
  • Step 15 Perform the second merging process on the straight line segments obtained after the first merging process in all frame images.
  • the second merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • Step 16 Determining the lane line according to the straight line segment obtained after the second merging process, said determining the lane line according to the straight line segment obtained after the second merging process includes:
  • the straight line segments obtained after the second merging process are determined as lane lines.
  • the number of repetitions of the straight line segments corresponding to these symbols and characters in all frame images is usually higher than that of the straight line corresponding to the lane line. Therefore, by counting the number of straight line segments obtained after the first merge process combined by each straight line segment obtained after the second merge process, it can be determined which straight line segments are lane line. For example, the set of straight line segments before the second merging process (that is, the straight line segments obtained after the first merging process) can be set as A, and the set of straight line segments after the second merging process is B. While performing the second merging process, it is also counted how many straight line segments in set A each straight line segment in set B is merged from.
  • the straight line segment is determined as the lane line. Therefore, by setting the preset threshold value, the straight line segment corresponding to the symbol mark and text mark on the road can be screened out, thereby improving the accuracy of detection.
  • the value of the preset threshold can be adjusted according to specific road conditions.
  • the step of determining the lane line according to the straight line segment obtained after the second merging process it further includes:
  • a lane line on the road will detect two straight line segments in the image, that is, the straight line segments corresponding to the edges on both sides of the length direction of the lane line, and the detected lane line
  • the goal of the line is to provide accurate lane separation information for driving, traffic monitoring, traffic scheduling, etc. Therefore, it is more convenient for each actual lane line to be marked with a straight line segment in the detection results of the lane line. Therefore, Among the straight line segments determined as lane lines, if two straight line segments correspond to both side edges of the same lane line, the two straight line segments may be merged into one line.
  • straight line segments may be merged according to the actual width of the lanes on the road and/or the actual width of the lane lines. For example, two straight line segments whose distance is smaller than the preset distance are merged into one straight line segment as the final lane line.
  • the final lane line takes an intermediate value, that is, an equidistant line between the two straight line segments.
  • the straight line segments determined as lane lines can be sorted from left to right according to the intersection of their extension lines and the x-axis, and then cluster analysis is performed on the sorted straight line segments, that is, according to the relationship between the two straight line segments and The distance between the intersection points of the x-axis is used for cluster analysis.
  • the two straight line segments belong to the two side edges of the same lane line. At this time, the two straight line segments can be merged into one, and if If the spacing is greater than the preset spacing, it is judged that the two straight line segments do not belong to the edges on both sides of the same lane line.
  • multi-frame images in the road video are extracted to detect multi-lane lines, and the mutual complementation and mutual verification between multi-frame images is used to avoid missed detection caused by vehicles blocking lane lines. It also prevents non-lane lines such as road surface symbols and text signs from being misdetected as lane lines, and improves the accuracy of lane line detection.
  • FIG. 4 is a schematic structural diagram of a multi-lane detection device provided in Embodiment 2 of the present application.
  • the detection device 40 includes:
  • the extraction module 41 is configured to extract several frames of images from the video of the road with multi-lane lines;
  • the processing module 42 is configured to perform binarization processing and edge detection on each frame of image to obtain a plurality of straight line segments in each frame of image;
  • the filtering module 43 is configured to filter out non-lane lines according to the position information corresponding to a plurality of straight line segments in each frame of image;
  • the first merging module 44 is configured to perform the first merging process on the straight line segments located on the same straight line among the multiple straight line segments obtained after screening in each frame of image;
  • the second merging module 45 is configured to perform a second merging process on the straight line segments obtained after the first merging process in all frame images;
  • the determination module 46 is configured to determine the lane line according to the straight line segment obtained after the second merging process
  • the determination module includes:
  • the determination unit is configured to determine, among the straight line segments obtained after the second merging process, the number of the combined straight line segments obtained after the first merging process is greater than a preset threshold value as the lane line.
  • the screening module includes:
  • an angle unit configured to determine a first angle formed between the shooting direction of the video and the direction of the road;
  • the filtering unit is configured to filter out non-lane lines in the multiple straight line segments in each frame of image according to the slopes of the multiple straight line segments and the first angle.
  • the screening unit includes:
  • the first subunit is configured such that if the slope of a line segment meets the first angle: then retain the straight line segment;
  • the second subunit is configured such that if the slope of a line segment meets the first angle: Then filter out the straight line segment;
  • ⁇ is the first angle
  • ⁇ is the slope of the straight line segment
  • the first merging process and/or the second merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • the preset condition is:
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • it also includes:
  • the third merging module is configured to merge the two straight line segments whose distance is smaller than the preset distance into one straight line segment as the final lane line.
  • the embodiment of the present application is a product embodiment corresponding to the above-mentioned method embodiment one, so details are not repeated here, please refer to the above-mentioned embodiment one for details.
  • FIG. 5 is a schematic structural diagram of a detection device provided in Embodiment 3 of the present application.
  • the detection device 50 includes a processor 51, a memory 52 and a The computer program that runs on; When described processor 51 executes described computer program, realize following steps:
  • Determining the lane line according to the straight line segment obtained after the second merging process includes:
  • the straight line segments obtained after the second merging process are determined as lane lines.
  • Said filtering non-lane lines according to the position information corresponding to a plurality of straight line segments in each frame image includes:
  • the non-lane lines in the multiple straight line segments are screened out.
  • the filtering out non-lane lines in the multiple straight line segments according to the slopes of the multiple straight line segments in each frame of image and the first angle includes:
  • ⁇ is the first angle
  • ⁇ is the slope of the straight line segment
  • the first merging process and/or the second merging process includes:
  • the straight line segments satisfying the preset condition are merged into one straight line segment.
  • the preset condition is:
  • ⁇ is the preset angle
  • D is the preset distance
  • P 1 and P 2 are respectively the abscissas of the intersection points of the two straight line segments and the x-axis
  • the step of determining the lane line according to the straight line segment obtained after the second merging process it further includes:
  • Embodiment 4 of the present application provides a computer-readable storage medium, on which a computer program is stored.
  • the computer program is executed by a processor, the steps in the method for detecting multi-lane markings in Embodiment 1 above are implemented.
  • the steps in the method for detecting multi-lane markings in Embodiment 1 above are implemented.
  • the above-mentioned computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage may be realized by any method or technology.
  • Information may be computer readable instructions, data structures, modules of a program, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Flash memory or other memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cartridge, tape magnetic disk storage or other magnetic storage device or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
  • PRAM phase change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • ROM read only memory
  • EEPROM Electrically Era

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Abstract

La présente demande se rapporte au domaine technique du traitement d'image. L'invention concerne un procédé et un appareil de détection de ligne à plusieurs voies, et un dispositif de détection. Le procédé de détection de ligne à plusieurs voies consiste : à extraire une pluralité de trames d'images à partir d'une vidéo d'une route ayant une pluralité de lignes de voie ; à effectuer un traitement de binarisation et une détection de bord sur chaque trame d'image, de façon à obtenir une pluralité de segments de ligne droite ; selon des informations de position correspondant à la pluralité de segments de ligne droite, à éliminer par criblage de lignes hors voie ; à effectuer un premier traitement de fusion sur une pluralité de segments de ligne droite obtenus après avoir été soumis à un criblage ; à effectuer un second traitement de fusion sur des segments de ligne droite, qui sont obtenus après avoir été soumis à un premier traitement de fusion, dans toutes les trames d'images ; et à déterminer des lignes de voie selon des segments de ligne droite obtenus après avoir été soumis à un second traitement de fusion. Dans la présente demande, une pluralité de trames d'images sont extraites d'une vidéo d'une route pour effectuer une détection, et la compensation mutuelle et la vérification entre la pluralité de trames d'images sont utilisées, de telle sorte que la situation de détection manquante due à un véhicule bloquant une ligne de voie est évitée, et une ligne hors voie, telle qu'un symbole ou un signe sur une route, est également empêchée d'être détectée de manière erronée en tant que ligne de voie, ce qui permet d'augmenter le taux de précision de détection de ligne de voie.
PCT/CN2022/100542 2021-07-08 2022-06-22 Procédé et appareil de détection de ligne à plusieurs voies, et dispositif de détection WO2023279966A1 (fr)

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