CN111027383A - Patrol robot - Google Patents

Patrol robot Download PDF

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Publication number
CN111027383A
CN111027383A CN201911079451.8A CN201911079451A CN111027383A CN 111027383 A CN111027383 A CN 111027383A CN 201911079451 A CN201911079451 A CN 201911079451A CN 111027383 A CN111027383 A CN 111027383A
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image
binarization
block
robot
unit
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唐志玉
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J11/00—Manipulators not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
    • B25J19/02—Sensing devices
    • B25J19/04—Viewing devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J5/00—Manipulators mounted on wheels or on carriages
    • B25J5/007—Manipulators mounted on wheels or on carriages mounted on wheels
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/255—Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
    • 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
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
    • G06V20/63—Scene text, e.g. street names
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
    • G06V20/625—License plates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Image Processing (AREA)

Abstract

The invention provides a patrol robot, comprising: the robot comprises a robot body, a supporting upright rod, a shooting cloud platform arranged on the supporting upright rod and an instant camera arranged on the shooting cloud platform; the supporting upright rod is hinged to the robot body in a turnover mode, and the robot body is provided with an upright rod avoiding groove used for avoiding the supporting upright rod and a cloud platform avoiding groove used for avoiding the photographing cloud deck; the instant camera is used for shooting images in front of the robot body to obtain and output a current front image. The patrol robot is simple in overall structure, the photographing holder and the camera can be folded and stored on the robot body through the supporting upright rod, and the storage robot is small in occupied space and convenient to carry or store.

Description

Patrol robot
Technical Field
The invention relates to a robot, in particular to a patrol robot.
Background
A patrol robot, also called a security robot, is a robot that assists humans to complete safety protection work semi-autonomously, autonomously or under the complete control of humans. The patrol robot is used as a subdivision field of the robot industry, is based on the actual production and living needs, and is used for solving potential safety hazards, patrol monitoring, disaster warning and the like. Thereby reducing the occurrence of safety accidents and reducing the loss of lives and properties. At present, the security robot is still in a starting stage, but under the huge security market demand, the security robot has wide development potential and future prospect. The supporting upright rods of the existing patrol robots for mounting the cameras cannot be folded, and the occupied space is large.
Disclosure of Invention
Technical problem to be solved
The invention aims to provide a patrol robot which is simple in structure and can be folded and stored by a photographing holder and a camera through a supporting upright rod.
(II) technical scheme
In order to solve the above technical problem, the present invention provides a patrol robot, including: the robot comprises a robot body, a supporting upright rod, a shooting cloud platform arranged on the supporting upright rod and an instant camera arranged on the shooting cloud platform; the supporting upright rod is hinged to the robot body in a turnover mode, and the robot body is provided with an upright rod avoiding groove used for avoiding the supporting upright rod and a cloud platform avoiding groove used for avoiding the photographing cloud deck; the instant camera is used for shooting images in front of the robot body to obtain and output a current front image. The patrol robot is simple in overall structure, the photographing holder and the camera can be folded and stored in the robot body through the supporting upright rod, the occupied space after storage is small, and carrying or storage is facilitated.
The patrol robot is a robot which assists humans to complete safety protection work semi-autonomously, autonomously or under the complete control of humans, and in the existing traffic accidents, the traffic accidents caused by vehicles with temporary license plates are frequent, so that some unlicensed vehicles on the road surface need to be monitored practically and effectively, and precautionary measures are taken. Therefore, the patrol robot according to the present embodiment further includes:
the block processing unit is used for receiving the current front image, determining the blurring degree of the current front image, and performing block processing on the current front image based on the blurring degree of the current front image to obtain a plurality of image blocks with the same size, wherein the smaller the blurring degree of the current front image is, the more the number of the image blocks obtained by performing block processing on the current front image is;
a threshold analyzing unit, connected to the block processing unit, configured to receive the multiple image blocks, and execute the following processing on each image block: acquiring a binarization threshold of the image blocks based on an OTSU algorithm, acquiring each binarization threshold of each image block in the neighborhood of the image blocks based on the OTSU algorithm, adjusting the binarization thresholds of the image blocks based on each binarization threshold of each image block in the neighborhood of the image blocks to obtain adjusted thresholds of the image blocks, and outputting the adjusted thresholds of the image blocks;
a binarization processing unit connected with the threshold value analysis unit and used for receiving the plurality of image blocks and the adjusted threshold value corresponding to each image block, performing binarization processing on the image blocks based on the adjusted threshold value corresponding to each image block to obtain binarization blocks, and outputting each binarization block corresponding to each image block;
the merging processing unit is connected with the binarization processing unit and used for receiving each binarization partition, merging each binarization partition, performing edge fusion on the merged image to obtain a fused image and outputting the fused image as a binarization image;
the self-adaptive high-frequency analysis unit is connected with the merging processing unit and used for receiving the binary image, measuring the contrast of the binary image to obtain the real-time contrast corresponding to the binary image, and determining the corresponding high-frequency distribution frequency band in the binary image based on the real-time contrast to output the high-frequency distribution frequency band as a target frequency band;
an image differentiation unit, connected to the frequency band extraction unit and the contrast measurement unit, respectively, and configured to receive the target frequency band and the binarized image, perform high-pass filtering processing based on the target frequency band on the binarized image, to obtain a corresponding high-pass filtered image, and output the high-pass filtered image;
a difference value obtaining unit, connected to the image differentiation unit, for obtaining the binarized image and the high-pass filtered image, and further for subtracting the high-pass filtered image from the binarized image pixel by pixel to obtain a corresponding difference value processed image, and outputting the difference value processed image;
the targeted processing unit is respectively connected with the difference value acquisition unit and the image differentiation unit, and is used for receiving the high-pass filtering image and the difference value processing image, performing feature enhancement processing on the high-pass filtering image to obtain and output a corresponding feature enhanced image, and adding the feature enhanced image and the difference value processing image pixel by pixel to obtain a corresponding reconstructed image and outputting the reconstructed image;
and the license plate missing identification unit is connected with the targeted processing unit and used for receiving the reconstructed image, carrying out vehicle body identification on the reconstructed image based on a preset vehicle body shape so as to obtain one or more vehicle body areas in the reconstructed image, carrying out license plate detection on each vehicle body area, and sending license plate missing information when the vehicle body areas without the detected license plates exist.
Further, the instant camera includes a shooting support, a brightness measuring instrument, an auxiliary light source, a filter, a lens, an image sensor, a content analyzer and an LED lamp, the shooting support is used to support the brightness measuring instrument, the auxiliary light source, the filter, the lens, the content analyzer and the LED lamp, the brightness measuring instrument is used to measure an ambient brightness mean value within a preset time interval, the auxiliary light source is connected with the brightness measuring instrument and is used to receive the ambient brightness mean value and determine whether to emit auxiliary light based on the ambient brightness mean value, the filter is arranged in front of the lens, the lens is arranged in front of the image sensor, the image sensor is used to obtain and output a current front image, the content analyzer is connected with the image sensor and is used to receive the current front image output by the image sensor, analyzing the current front image according to the following contents: and detecting each edge line in the current front image, and determining whether to send out a blurring alarm signal according to the distribution uniformity of each edge line in the current front image.
Further, in the license plate missing identification unit, the license plate detection for each vehicle body region includes: and in the vehicle area, combining all pixel points of which the blue color component is greater than or equal to a preset component threshold value into a license plate sub-area, and determining that no license plate is detected in the vehicle area when OCR recognition in the license plate sub-area fails.
Further, in the threshold analyzing unit, adjusting the binarization threshold of the image block based on each binarization threshold of each image block in the neighborhood of the image block to obtain an adjusted threshold of the image block includes: the higher the matching degree of the image block neighborhood image block and the image block is, the greater the influence degree of the image block neighborhood image block on the binarization threshold value of the image block is.
Further, in the content analyzer, determining whether to send out a blurring alarm signal according to the distribution uniformity of each edge line in the current front image includes: and when the distribution uniformity of each edge line in the current front image exceeds the limit, sending a blurring alarm signal.
Further, the LED lamp is connected with the content analyzer and used for emitting red light at a preset flashing frequency when receiving the blurring alarm signal; after the auxiliary light source further determines to emit auxiliary light, determining the intensity of the emitted auxiliary light according to the size of the ambient brightness mean value, wherein the intensity of the emitted auxiliary light is smaller when the ambient brightness mean value is larger; the LED lamp is also used for not carrying out any flashing operation when the blurring alarm signal is not received.
(III) advantageous effects
The patrol robot is simple in overall structure, the photographing holder and the camera can be folded and stored on the robot body through the supporting upright rod, and the storage robot is small in occupied space and convenient to carry or store.
Drawings
FIG. 1 is a schematic structural diagram of a patrol robot of the present invention;
wherein: the robot comprises a robot body 1, a supporting upright rod 2, a photographing tripod head 3, an instant camera 4, an upright rod avoiding groove 5 and a tripod head avoiding groove 6.
Detailed Description
Referring to fig. 1, the present invention provides a patrol robot including: the robot comprises a robot body 1, a supporting upright rod 2, a shooting cloud platform 3 arranged on the supporting upright rod 2 and an instant camera 4 arranged on the shooting cloud platform 3; the supporting upright stanchion 2 is hinged on the robot car body 1 in a turnover way, and the robot car body 1 is provided with an upright stanchion avoiding groove 5 for avoiding the supporting upright stanchion 2 and a pan-tilt avoiding groove 6 for avoiding the photographing pan-tilt 3; the instant camera 4 is used for shooting images in front of the robot body 1 to obtain and output a current front image. The overall structure of this embodiment patrol robot is simple, and photographic cloud platform and camera accessible support pole setting are folding to be accomodate on the robot, and the occupation space after accomodating is little, is convenient for transport or store.
The patrol robot is a robot which assists humans to complete safety protection work semi-autonomously, autonomously or under the complete control of humans, and in the existing traffic accidents, the traffic accidents caused by vehicles with temporary license plates are frequent, so that some unlicensed vehicles on the road surface need to be monitored practically and effectively, and precautionary measures are taken. Therefore, the patrol robot of the present embodiment further includes:
the block processing unit is used for receiving the current front image, determining the blurring degree of the current front image, and performing block processing on the current front image based on the blurring degree of the current front image to obtain a plurality of image blocks with the same size, wherein the smaller the blurring degree of the current front image is, the more the number of the image blocks obtained by performing block processing on the current front image is;
a threshold analyzing unit, connected to the block processing unit, configured to receive the multiple image blocks, and execute the following processing on each image block: acquiring a binarization threshold of the image blocks based on an OTSU algorithm, acquiring each binarization threshold of each image block in the neighborhood of the image blocks based on the OTSU algorithm, adjusting the binarization thresholds of the image blocks based on each binarization threshold of each image block in the neighborhood of the image blocks to obtain adjusted thresholds of the image blocks, and outputting the adjusted thresholds of the image blocks;
a binarization processing unit connected with the threshold value analysis unit and used for receiving the plurality of image blocks and the adjusted threshold value corresponding to each image block, performing binarization processing on the image blocks based on the adjusted threshold value corresponding to each image block to obtain binarization blocks, and outputting each binarization block corresponding to each image block;
the merging processing unit is connected with the binarization processing unit and used for receiving each binarization partition, merging each binarization partition, performing edge fusion on the merged image to obtain a fused image and outputting the fused image as a binarization image;
the self-adaptive high-frequency analysis unit is connected with the merging processing unit and used for receiving the binary image, measuring the contrast of the binary image to obtain the real-time contrast corresponding to the binary image, and determining the corresponding high-frequency distribution frequency band in the binary image based on the real-time contrast to output the high-frequency distribution frequency band as a target frequency band;
an image differentiation unit, connected to the frequency band extraction unit and the contrast measurement unit, respectively, and configured to receive the target frequency band and the binarized image, perform high-pass filtering processing based on the target frequency band on the binarized image, to obtain a corresponding high-pass filtered image, and output the high-pass filtered image;
a difference value obtaining unit, connected to the image differentiation unit, for obtaining the binarized image and the high-pass filtered image, and further for subtracting the high-pass filtered image from the binarized image pixel by pixel to obtain a corresponding difference value processed image, and outputting the difference value processed image;
the targeted processing unit is respectively connected with the difference value acquisition unit and the image differentiation unit, and is used for receiving the high-pass filtering image and the difference value processing image, performing feature enhancement processing on the high-pass filtering image to obtain and output a corresponding feature enhanced image, and adding the feature enhanced image and the difference value processing image pixel by pixel to obtain a corresponding reconstructed image and outputting the reconstructed image;
and the license plate missing identification unit is connected with the targeted processing unit and used for receiving the reconstructed image, carrying out vehicle body identification on the reconstructed image based on a preset vehicle body shape so as to obtain one or more vehicle body areas in the reconstructed image, carrying out license plate detection on each vehicle body area, and sending license plate missing information when the vehicle body areas without the detected license plates exist.
The instant camera 4 comprises a shooting support, a brightness measuring instrument, an auxiliary light source, a light filter, a lens, an image sensor, a content analyzer and an LED lamp, wherein the shooting support is used for supporting the brightness measuring instrument, the auxiliary light source, the light filter, the lens, the content analyzer and the LED lamp, the brightness measuring instrument is used for measuring an ambient brightness mean value in a preset time interval, the auxiliary light source is connected with the brightness measuring instrument and is used for receiving the ambient brightness mean value and determining whether to emit auxiliary light or not based on the ambient brightness mean value, the light filter is arranged in front of the lens, the lens is arranged in front of the image sensor, the image sensor is used for obtaining and outputting a current front image, the content analyzer is connected with the image sensor and is used for receiving the current front image output by the image sensor, analyzing the current front image according to the following contents: and detecting each edge line in the current front image, and determining whether to send out a blurring alarm signal according to the distribution uniformity of each edge line in the current front image.
In the license plate missing identification unit, the license plate detection of each vehicle body region comprises: and in the vehicle area, combining all pixel points of which the blue color component is greater than or equal to a preset component threshold value into a license plate sub-area, and determining that no license plate is detected in the vehicle area when OCR recognition in the license plate sub-area fails.
In the threshold analysis unit, adjusting the binarization threshold of the image block based on each binarization threshold of each image block in the image block neighborhood to obtain an adjusted threshold of the image block includes: the higher the matching degree of the image block neighborhood image block and the image block is, the greater the influence degree of the image block neighborhood image block on the binarization threshold value of the image block is.
In the content analyzer, determining whether to send out a blurring alarm signal according to the distribution uniformity of each edge line in the current front image includes: and when the distribution uniformity of each edge line in the current front image exceeds the limit, sending a blurring alarm signal.
The LED lamp is connected with the content analyzer and is used for emitting red light at a preset flashing frequency when receiving the blurring alarm signal; after the auxiliary light source further determines to emit auxiliary light, determining the intensity of the emitted auxiliary light according to the size of the ambient brightness mean value, wherein the intensity of the emitted auxiliary light is smaller when the ambient brightness mean value is larger; the LED lamp is also used for not carrying out any flashing operation when the blurring alarm signal is not received.
The patrol robot is characterized in that aiming at the technical problems that a temporary vehicle monitoring and license plate loss detection mechanism is lacked in the prior art, pixel points with blue color components larger than or equal to a preset component threshold value are combined into a license plate sub-region, and when OCR recognition fails in the license plate sub-region, the fact that a front vehicle has a license plate loss condition is determined; performing uniform blocking processing on the image according to the corresponding size based on the fuzzy degree of the image, and adjusting the threshold value of each image block based on the threshold value of the image block in the neighborhood thereof, thereby improving the precision of image binaryzation; a self-adaptive image sharpening processing mode is adopted, so that the image sharpening effect is ensured; and detecting the blurring degree of the image output by the shooting unit in real time so as to perform corresponding alarm operation when blurring is excessive.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the technical principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (7)

1. A patrol robot, comprising: the robot comprises a robot body (1), a supporting upright rod (2), a shooting cloud platform (3) arranged on the supporting upright rod (2) and an instant camera (4) arranged on the shooting cloud platform (3); the supporting upright stanchion (2) is hinged on the robot car body (1) in a turnover manner, and the robot car body (1) is provided with an upright stanchion avoiding groove (5) for avoiding the supporting upright stanchion (2) and a tripod head avoiding groove (6) for avoiding the photographing tripod head (3); the real-time camera (4) is used for shooting images in front of the robot car body (1) to obtain and output a current front image.
2. A patrol robot as claimed in claim 1, further comprising:
the block processing unit is used for receiving the current front image, determining the blurring degree of the current front image, and performing block processing on the current front image based on the blurring degree of the current front image to obtain a plurality of image blocks with the same size, wherein the smaller the blurring degree of the current front image is, the more the number of the image blocks obtained by performing block processing on the current front image is;
a threshold analyzing unit, connected to the block processing unit, configured to receive the multiple image blocks, and execute the following processing on each image block: acquiring a binarization threshold of the image blocks based on an OTSU algorithm, acquiring each binarization threshold of each image block in the neighborhood of the image blocks based on the OTSU algorithm, adjusting the binarization thresholds of the image blocks based on each binarization threshold of each image block in the neighborhood of the image blocks to obtain adjusted thresholds of the image blocks, and outputting the adjusted thresholds of the image blocks;
a binarization processing unit connected with the threshold value analysis unit and used for receiving the plurality of image blocks and the adjusted threshold value corresponding to each image block, performing binarization processing on the image blocks based on the adjusted threshold value corresponding to each image block to obtain binarization blocks, and outputting each binarization block corresponding to each image block;
the merging processing unit is connected with the binarization processing unit and used for receiving each binarization partition, merging each binarization partition, performing edge fusion on the merged image to obtain a fused image and outputting the fused image as a binarization image;
the self-adaptive high-frequency analysis unit is connected with the merging processing unit and used for receiving the binary image, measuring the contrast of the binary image to obtain the real-time contrast corresponding to the binary image, and determining the corresponding high-frequency distribution frequency band in the binary image based on the real-time contrast to output the high-frequency distribution frequency band as a target frequency band;
an image differentiation unit, connected to the frequency band extraction unit and the contrast measurement unit, respectively, and configured to receive the target frequency band and the binarized image, perform high-pass filtering processing based on the target frequency band on the binarized image, to obtain a corresponding high-pass filtered image, and output the high-pass filtered image;
a difference value obtaining unit, connected to the image differentiation unit, for obtaining the binarized image and the high-pass filtered image, and further for subtracting the high-pass filtered image from the binarized image pixel by pixel to obtain a corresponding difference value processed image, and outputting the difference value processed image;
the targeted processing unit is respectively connected with the difference value acquisition unit and the image differentiation unit, and is used for receiving the high-pass filtering image and the difference value processing image, performing feature enhancement processing on the high-pass filtering image to obtain and output a corresponding feature enhanced image, and adding the feature enhanced image and the difference value processing image pixel by pixel to obtain a corresponding reconstructed image and outputting the reconstructed image;
and the license plate missing identification unit is connected with the targeted processing unit and used for receiving the reconstructed image, carrying out vehicle body identification on the reconstructed image based on a preset vehicle body shape so as to obtain one or more vehicle body areas in the reconstructed image, carrying out license plate detection on each vehicle body area, and sending license plate missing information when the vehicle body areas without the detected license plates exist.
3. The patrol robot according to claim 2, wherein the point-in-time camera (4) includes a photographing bracket for supporting the lightness measurement instrument, the auxiliary light source, the filter, the lens, the content analyzer and the LED lamp, a lightness measurement instrument for measuring an ambient lightness mean value within a preset time interval, an auxiliary light source connected to the lightness measurement instrument for receiving the ambient lightness mean value and deciding whether to emit auxiliary light based on the ambient lightness mean value, a filter provided in front of the lens provided in front of the image sensor, an image sensor for obtaining and outputting a current front image, and a content analyzer connected to the image sensor, the image sensor is used for receiving a current front image output by the image sensor and analyzing the current front image as follows: and detecting each edge line in the current front image, and determining whether to send out a blurring alarm signal according to the distribution uniformity of each edge line in the current front image.
4. A patrol robot as claimed in claim 3, wherein the license plate absence identifying unit, wherein the license plate detection for each body region comprises: and in the vehicle area, combining all pixel points of which the blue color component is greater than or equal to a preset component threshold value into a license plate sub-area, and determining that no license plate is detected in the vehicle area when OCR recognition in the license plate sub-area fails.
5. The patrol robot of claim 4, wherein in the threshold resolving unit, adjusting the binarization threshold values of the image patches based on respective binarization thresholds of respective image patches of the image patch neighborhood to obtain adjusted threshold values of the image patches comprises: the higher the matching degree of the image block neighborhood image block and the image block is, the greater the influence degree of the image block neighborhood image block on the binarization threshold value of the image block is.
6. The patrol robot of claim 5, wherein the determining, in the content parser, whether to issue a blurring alarm signal according to a degree of uniformity of distribution of the respective edge lines in the current front image comprises: and when the distribution uniformity of each edge line in the current front image exceeds the limit, sending a blurring alarm signal.
7. A patrol robot as claimed in claim 6, wherein the LED light is connected to the content parser for emitting red light at a preset blinking frequency upon receipt of the virtualisation alarm signal; after the auxiliary light source further determines to emit auxiliary light, determining the intensity of the emitted auxiliary light according to the size of the ambient brightness mean value, wherein the intensity of the emitted auxiliary light is smaller when the ambient brightness mean value is larger; the LED lamp is also used for not carrying out any flashing operation when the blurring alarm signal is not received.
CN201911079451.8A 2019-11-07 2019-11-07 Patrol robot Withdrawn CN111027383A (en)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111645467A (en) * 2020-05-15 2020-09-11 特斯联科技集团有限公司 Security patrol robot
CN112528056A (en) * 2020-11-29 2021-03-19 泰州芯源半导体科技有限公司 Double-index field data retrieval system and method
CN112931287A (en) * 2021-01-28 2021-06-11 河北农业大学 Inspection robot for livestock and poultry breeding
CN113664848A (en) * 2021-08-27 2021-11-19 沈阳吕尚科技有限公司 Inspection robot and working method thereof
CN113942595A (en) * 2020-07-15 2022-01-18 Oppo广东移动通信有限公司 Vehicle body, functional device and charging device
CN114652220A (en) * 2022-03-29 2022-06-24 常州机电职业技术学院 Home security robot with floor sweeping function

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111645467A (en) * 2020-05-15 2020-09-11 特斯联科技集团有限公司 Security patrol robot
CN113942595A (en) * 2020-07-15 2022-01-18 Oppo广东移动通信有限公司 Vehicle body, functional device and charging device
CN112528056A (en) * 2020-11-29 2021-03-19 泰州芯源半导体科技有限公司 Double-index field data retrieval system and method
CN112931287A (en) * 2021-01-28 2021-06-11 河北农业大学 Inspection robot for livestock and poultry breeding
CN113664848A (en) * 2021-08-27 2021-11-19 沈阳吕尚科技有限公司 Inspection robot and working method thereof
CN114652220A (en) * 2022-03-29 2022-06-24 常州机电职业技术学院 Home security robot with floor sweeping function

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