CN110866944A - Consigned luggage measurement and identification method and system - Google Patents
Consigned luggage measurement and identification method and system Download PDFInfo
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- CN110866944A CN110866944A CN201911239311.2A CN201911239311A CN110866944A CN 110866944 A CN110866944 A CN 110866944A CN 201911239311 A CN201911239311 A CN 201911239311A CN 110866944 A CN110866944 A CN 110866944A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
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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
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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
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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
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
- G06T7/85—Stereo camera calibration
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- 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
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20032—Median filtering
Abstract
The invention discloses a consigned luggage measurement and identification method and a consigned luggage measurement and identification system, which belong to the field of luggage identification and measurement systems and comprise 3D measurement equipment, a main control unit and a background management center; the 3D measuring equipment is used for scanning the luggage after calibration and three-dimensional modeling, and transmitting a 3D cloud point depth map and a picture obtained by scanning to the main control unit; the main control unit carries out plane fitting, filtering and thresholding on the received 3D cloud point depth map in sequence, then carries out identification and judgment to obtain the state information of the luggage, and sends the state information and the photo to a background management center; the background management center receives the luggage state information and the photos of the main control unit and issues luggage scanning instructions to the main control unit; the 3D measuring equipment adopts 3D structured light and image recognition technology to scan the luggage. The invention solves the problems that the conventional luggage measurement and identification system has incomplete luggage measurement data, large error and incapability of identifying special-shaped luggage, thereby causing inconvenience for consigning the luggage.
Description
Technical Field
The invention belongs to the field of baggage identification and measurement systems, and relates to a consigned baggage measurement and identification method and system.
Background
At present, the baggage handling and consignment in airports at home and abroad only have two modes: the method comprises the steps of manual check-in counter baggage consignment (hereinafter referred to as manual counter) and self-service check-in baggage consignment (hereinafter referred to as self-service consignment).
The measurement and identification of the luggage at the manual counter is generally carried out by visual evaluation inspection or manual measurement by the ground clothes staff according to the bag specification. The manual measurement and identification mode has low efficiency, is one of the main reasons for congestion of manual check-in counters, and is easy to cause the problems of bag blocking, baggage blockage or baggage damage and the like caused by the fact that oversized and over-sized baggage is conveyed from a conventional baggage channel due to large errors of the manual measurement and identification mode, so that passenger experience and flight collimation rate are influenced.
The measurement of luggage by self-check is typically by using conventional raster 2D measurements or laser measurements. The problems of incomplete data of the size of the luggage, large error and the like exist in the 2D measurement of the grating, and the problems of bag clamping, luggage blocking and the like caused by the fact that oversized and over-sized luggage is conveyed from a conventional luggage channel can also be caused. And the type of the luggage can not be identified by grating 2D measurement or laser measurement, and the real object photo of the luggage can not be collected, so that the application problems of the number of the luggage, whether the luggage needs to be loaded, whether the luggage is abnormal luggage and the like can not be solved, and the luggage is inconvenient to consign.
Therefore, in order to solve the above problems, the present invention provides a method and a system for identifying a commissioning plum measurement.
Disclosure of Invention
The invention aims to: the consigned luggage measurement and identification method and system are provided, and the problems that the conventional luggage measurement and identification system is incomplete in luggage measurement data, large in error and incapable of identifying special-shaped luggage, and accordingly inconvenience is caused to consigned luggage are solved.
The technical scheme adopted by the invention is as follows:
the consigned baggage measurement and identification method comprises the following steps:
step 1: the method comprises the steps that after the 3D measuring equipment is calibrated and three-dimensionally modeled, luggage is scanned, and a 3D cloud point depth map and a picture of the luggage are obtained;
step 2: sequentially carrying out plane fitting, filtering and thresholding on the 3D cloud point depth map to obtain a boundary line, and calculating luggage data according to the boundary line;
and step 3: carrying out identification and judgment on the luggage data to obtain luggage state information;
and 4, step 4: and sending the state information and the photos of the luggage to a background management center.
Further, the 3D measurement device performs calibration and three-dimensional modeling, and specifically includes the following steps:
establishing a geometric model of camera imaging, solving parameters of the geometric model, namely camera parameters, and completing camera calibration in the 3D measuring equipment;
adjusting the camera according to a camera coordinate system, wherein an original point is positioned at the optical center of a lens of the camera, x and y axes are respectively parallel to two sides of a phase plane, and a z axis is a lens optical axis and is vertical to an image plane;
and drawing a plurality of point clouds of the object into a grid, and then mapping textures, namely the uneven grooves on the surface of the object to form a three-dimensional model, thereby completing three-dimensional modeling.
Further, the step 2 specifically includes the following steps:
step 2.1: performing plane fitting on the 3D cloud point depth map by adopting an OpenCV method;
step 2.2: filtering and denoising the image obtained in the step 2.1 by adopting a median filtering algorithm;
step 2.3: setting a threshold value by utilizing an image pixel point distribution rule, and carrying out pixel point segmentation on the denoised image by adopting a self-adaptive thresholding method so as to obtain a binary image of the image;
step 2.4: and adopting a Canny algorithm to obtain a boundary line of the binary image, and calculating luggage data according to the boundary line.
Still further, the baggage data may include a size and a position of the baggage, the size including a length, a width, a height and a volume of the baggage, and the position including a rotation angle, a horizontal offset length and a vertical offset length data of the baggage.
Further, the identifying and judging the baggage data includes: and carrying out sample training on a plurality of baggage data by using a deep learning algorithm, carrying out iteration to obtain a sample model, and then identifying the baggage data to realize baggage classification identification and special-shaped baggage detection.
Further, the baggage status information includes a type of baggage, a number of baggage, whether the baggage is within a measurement range, and whether the baggage is regular.
The consigned luggage measurement and identification system comprises 3D measuring equipment, a main control unit and a background management center, wherein the main control unit is respectively connected with the 3D measuring equipment and the background management center;
the 3D measuring equipment scans the luggage and transmits a 3D cloud point depth map and a picture obtained by scanning to the main control unit;
the main control unit carries out plane fitting, filtering and thresholding on the received 3D cloud point depth map in sequence, then carries out identification and judgment to obtain the state information of the luggage, sends the state information and the picture to a background management center, and drives the 3D measuring equipment to scan after carrying out calibration and three-dimensional modeling on the 3D measuring equipment;
the background management center receives the luggage state information and the photos of the main control unit and issues luggage scanning instructions to the main control unit;
the 3D measuring equipment adopts 3D structured light and image recognition technology to scan the luggage.
Furthermore, the system also comprises an RFID identification unit connected with the main control unit, wherein the RFID identification unit is used for reading and verifying the data of the RFID label in the picture obtained by the 3D measuring equipment and sending the result to the background management center through the main control unit.
Further, the baggage status information includes a type of baggage, a number of baggage, whether the baggage is within a measurement range, and whether the baggage is regular.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the consigned luggage measurement and identification method and system integrates the luggage volume measurement, the luggage photographing and the luggage identification into a whole by adopting an internet of things technology, an industrial measurement technology and an intelligent embedded system, provides the luggage measurement and identification of a luggage full-flow tracking intermediate machine counter luggage consignment link for self-service consignment equipment, and realizes the integrated luggage measurement and identification functions of luggage volume measurement, luggage type detection, luggage quantity detection, luggage position detection, luggage framing prompt, luggage framing judgment, luggage abnormal shape judgment, luggage photo grabbing and the like; manual operation is not needed, millisecond-level measurement and identification time is provided, and efficiency is greatly improved; the measuring error reaches the millimeter level, can avoid super large superstandard luggage to flow into conventional luggage transfer chain completely, very big promotion consignment luggage's processing time and the degree of accuracy, promotion passenger satisfaction and flight punctuality rate.
2. The 3D measuring equipment disclosed by the invention scans the luggage by adopting a 3D structured light and image recognition technology, realizes automatic measurement and recognition of consigned luggage, particularly realizes measurement of the volume, type and position of different types and sizes of luggage, and has excellent stability.
3. The invention identifies and judges the luggage data to obtain the result of whether the luggage is regular or not, and the luggage state information comprises the type of the luggage, the number of the luggage, whether the luggage is in the measuring range or not and whether the luggage is regular or not, thereby being convenient for framing irregular luggage subsequently.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that for those skilled in the art, other relevant drawings can be obtained according to the drawings without inventive effort, wherein:
fig. 1 is a system block diagram of a consignment baggage measurement identification system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described herein and illustrated in the figures may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The consigned luggage measurement and identification method and system solve the problems that the conventional luggage measurement and identification system has incomplete luggage measurement data, large error and incapability of identifying special-shaped luggage, thereby causing inconvenience to consigned luggage.
The consigned baggage measurement and identification method comprises the following steps:
step 1: the method comprises the steps that after the 3D measuring equipment is calibrated and three-dimensionally modeled, luggage is scanned, and a 3D cloud point depth map and a picture of the luggage are obtained;
step 2: sequentially carrying out plane fitting, filtering and thresholding on the 3D cloud point depth map to obtain a boundary line, and calculating luggage data according to the boundary line;
and step 3: carrying out identification and judgment on the luggage data to obtain luggage state information;
and 4, step 4: and sending the state information and the photos of the luggage to a background management center.
The consigned luggage measurement and identification system comprises 3D measuring equipment, a main control unit and a background management center, wherein the main control unit is respectively connected with the 3D measuring equipment and the background management center;
the 3D measuring equipment scans the luggage and transmits a 3D cloud point depth map and a picture obtained by scanning to the main control unit;
the main control unit carries out plane fitting, filtering and thresholding on the received 3D cloud point depth map in sequence, then carries out identification and judgment to obtain the state information of the luggage, sends the state information and the picture to a background management center, and drives the 3D measuring equipment to scan after carrying out calibration and three-dimensional modeling on the 3D measuring equipment;
the background management center receives the luggage state information and the photos of the main control unit and issues luggage scanning instructions to the main control unit;
the 3D measuring equipment adopts 3D structured light and image recognition technology to scan the luggage.
The invention integrates the luggage volume measurement, the luggage photographing and the luggage identification into a whole by adopting the internet of things technology, the industrial measurement technology and the intelligent embedded system, provides the luggage measurement identification of the luggage full-flow tracking intermediate machine counter luggage consignment link for the self-service consignment equipment, and realizes the integrated luggage measurement identification functions of the luggage volume measurement, the luggage type detection, the luggage quantity detection, the luggage position detection, the luggage framing prompt, the luggage framing judgment, the luggage abnormal shape judgment, the luggage photo grabbing and the like; manual operation is not needed, millisecond-level measurement and identification time is provided, and efficiency is greatly improved; the measuring error reaches the millimeter level, can avoid super large superstandard luggage to flow into conventional luggage transfer chain completely, very big promotion consignment luggage's processing time and the degree of accuracy, promotion passenger satisfaction and flight punctuality rate.
The features and properties of the present invention are described in further detail below with reference to examples.
Example one
The preferred embodiment of the present invention provides a method for identifying trusting plum measurement, which comprises the following steps:
step 1: the method comprises the steps that after the 3D measuring equipment is calibrated and three-dimensionally modeled, luggage is scanned, and a 3D cloud point depth map and a picture of the luggage are obtained;
in the image measurement process and machine vision application, in order to determine the mutual relation between the three-dimensional geometric position of a certain point on the surface of a space object and the corresponding point in an image, a geometric model of camera imaging is established, geometric model parameters, namely camera parameters, are solved through experiments and calculation, and the process of solving the parameters is called as camera calibration, so that the camera calibration in the 3D measurement equipment is completed;
adjusting the camera according to a world coordinate system or a camera coordinate system, wherein an original point is positioned at the optical center of a lens of the camera, x and y axes are respectively parallel to two sides of a phase plane, and a z axis is a lens optical axis and is vertical to an image plane; the world coordinate system is also called as a measurement coordinate system and is a three-dimensional rectangular coordinate system, the spatial positions of the camera and the object to be measured can be described by taking the world coordinate system as a reference, the position of the world coordinate system can be freely determined according to the actual condition, and the camera coordinate system is also a three-dimensional rectangular coordinate system;
the three-dimensional model can be generated manually as data of points and other information sets, the three-dimensional model is generated through special software such as a three-dimensional modeling tool, the three-dimensional model can also be generated according to a certain algorithm, a plurality of point clouds of an object are drawn into a grid, the grid consists of the plurality of point clouds of the object, the three-dimensional model grid is formed through the point clouds, the point clouds comprise three-dimensional coordinates (XYZ), laser reflection Intensity (Intensity) and color information (RGB), the grid is a triangle, a quadrangle or other simple convex polygons, the rendering process can be simplified, and the three-dimensional model can also be an object consisting of common polygons with cavities;
mapping textures to the surface of an object based on a grid to form a three-dimensional model and finish three-dimensional modeling, wherein the textures are uneven grooves on the surface of the object and comprise color patterns on the smooth surface of the object, and are also called texture maps;
step 2: sequentially carrying out plane fitting, filtering and thresholding on the 3D cloud point depth map to obtain a boundary line, and calculating luggage data according to the boundary line;
step 2.1: performing plane fitting on the 3D cloud point depth map by adopting an OpenCV method;
step 2.2: filtering and denoising the image obtained in the step 2.1 by adopting a median filtering algorithm;
the method is characterized in that the noise of an image is eliminated as much as possible under the condition of keeping the details of the image, the subsequent image processing is facilitated, filtering needs to meet two conditions, the contour of the image cannot be damaged, and important characteristic information of edges cannot be damaged, so that the visual effect of the image is better, the filtering has five basic algorithms, namely, square filtering, mean filtering, Gaussian filtering, median filtering and bilateral filtering, the first three algorithms are linear filtering algorithms, the second two algorithms are nonlinear filtering algorithms, and the median filtering algorithm is adopted in the embodiment;
step 2.3: setting a threshold value by utilizing an image pixel point distribution rule, and carrying out pixel point segmentation on the denoised image by adopting a self-adaptive thresholding method so as to obtain a binary image of the image;
there are many methods for image thresholding, the common methods include classical OTSU, fixed threshold, adaptive threshold, double threshold and semi-thresholding, and this embodiment adopts the adaptive thresholding method;
step 2.4: adopting a Canny algorithm to obtain a boundary line of the binary image, and calculating luggage data according to the boundary line;
because the binary image obtained by thresholding has two disadvantages, one is that the detected edge is too thick and is difficult to realize accurate positioning of an object, and the other is difficult to find a proper threshold value which can be sufficiently lower than all detected important edges and can not contain too many minor edges, in this embodiment, a Canny algorithm is adopted to perform border line extraction on the binary image, the Canny operator is usually based on a Sobel operator, a low threshold value and a high threshold value are used to respectively determine which points belong to contours, the low threshold value is used for including all edge pixels belonging to contours of obvious images, the high threshold value is used for defining the boundaries of all important contours, and the Canny operator combines two edge images of the low threshold value and the high threshold value to generate an optimal contour map so as to obtain the border line;
the baggage data comprises a size and a position of the baggage, the size comprising a length, a width, a height and a volume of the baggage, the position comprising a rotation angle, a horizontal offset length and a vertical offset length data of the baggage;
and step 3: carrying out identification and judgment on the luggage data to obtain luggage state information;
carrying out sample training on a plurality of pieces of luggage data by using a deep learning algorithm, carrying out iteration to obtain a sample model, then identifying the luggage data, realizing luggage classification identification and special-shaped luggage detection, and obtaining luggage state information, wherein the luggage state information comprises the type of the luggage, the number of the luggage, whether the luggage is in a measurement range and whether the luggage is regular;
and 4, step 4: and sending the state information and the photos of the luggage to a background management center.
Based on the consigned baggage measuring and identifying method, the consigned baggage measuring and identifying system comprises 3D measuring equipment, a main control unit and a background management center, wherein the main control unit is respectively connected with the 3D measuring equipment and the background management center;
the 3D measuring equipment scans the luggage and transmits a 3D cloud point depth map and a picture obtained by scanning to the main control unit;
the main control unit carries out plane fitting, filtering and thresholding on the received 3D cloud point depth map in sequence, then carries out identification and judgment to obtain the state information of the luggage, sends the state information and the picture to a background management center, and drives the 3D measuring equipment to scan after carrying out calibration and three-dimensional modeling on the 3D measuring equipment; the main control unit can also store the state information and the photos of the luggage, so that the luggage can be conveniently called at a later stage;
the background management center receives the luggage state information and the photos of the main control unit and issues luggage scanning instructions to the main control unit;
the 3D measuring equipment adopts the 3D structured light and image recognition technology to scan the luggage, and realizes automatic measurement and recognition of the consigned luggage.
Furthermore, the system also comprises an RFID identification unit connected with the main control unit, wherein the RFID identification unit is used for reading and verifying the data of the RFID label in the picture obtained by the 3D measuring equipment, feeding the result back to the main control unit and sending the result to the background management center.
Specifically, the RFID identification unit adopts industrial integrated RFID identification equipment, and is internally provided with a circularly polarized ceramic antenna and a buzzer, so that interference, serial reading and misreading of adjacent equipment can be avoided, the reading rate is greater than 99.5%, the reading rate is not lower than 200ms, 7 × 24H operation can be guaranteed, and the specific parameters are as follows:
the working frequency is as follows: 920 MHZ-925 MHZ;
the supporting protocol is as follows: ISO18000-6C (EPC GEN 2);
the support standard is as follows: IATA 1740 Standard;
radio frequency power: 0-26 dBm (software adjustable);
identifying the distance: 0-3 m;
the recognition rate is as follows: not less than 99.9%;
the recognition rate is as follows: more than or equal to 192 Tag/S;
IO interface: one set of triggers and one set of relay outputs;
secondary development: secondary development of languages such as VC, VB and C # is supported;
and (3) reading the label: timing automatic reading, external trigger control reading and command interactive reading;
reading and writing the data area: and the data reading of the EPC, TID and USER areas is supported, and the protection can be written.
Specifically, the system further comprises a switching power supply, the switching power supply is respectively connected with the 3D measuring device, the RFID identification unit, the main control unit and the background management center, and all devices are guaranteed to run safely and stably by adopting industrial power supply configuration with stable output.
Specifically, the system further comprises a communication unit, wherein the communication unit is connected with the main control unit and the background management center, different modules are selected and matched, the system is suitable for various industrial bus communication and network communication, and communication modes such as RS232, TCP/IP, PROFINET, PROFIBUS, EtherNet/IP and the like are supported.
Specifically, the 3D measuring equipment is industrial-grade 3D measuring equipment, adopts a plurality of cameras, adapts to various complex application environments, can keep 7 × 24H stable operation, and the specific parameters are:
the number of cameras: more than or equal to 2;
measurement range: full coverage of the detection zone (120cm by 90 cm);
and (3) data output: outputting an aligned and synchronized RGB map and a depth map, a point cloud map and an IR map;
measurement error: less than 1cm (not affected by changes in environmental conditions);
power consumption situation: < 2W.
Specifically, the main control unit is an embedded main control system with a deep learning algorithm, in this embodiment, the background management center is a main control system of an on-board counter, and 2 sets of the 3D measurement devices and 2 sets of the RFID identification units share one main control system of the on-board counter.
Further, the luggage state information comprises the type of the luggage, the number of the luggage, whether the luggage is in the measuring range or not and whether the luggage is regular or not, so that the irregular luggage can be conveniently framed subsequently.
The invention integrates the luggage volume measurement, the luggage photographing and the luggage identification (irregular luggage detection, multi-frame detection and the like) into a whole by adopting an Internet of things technology, an industrial measurement technology and an intelligent embedded system, provides the luggage measurement identification of the luggage full-flow tracking intermediate-value machine counter luggage consignment link for self-service consignment equipment, and realizes the integrated luggage measurement identification functions of luggage volume measurement, luggage type detection, luggage quantity detection, luggage position detection, luggage framing prompt, luggage framing judgment, luggage abnormal shape judgment, luggage photo grabbing and the like; the manual operation is not needed, and the efficiency is greatly improved due to the millisecond-level measurement and identification time; the measuring error reaches millimeter level, can avoid super large superstandard luggage to flow into conventional luggage transfer chain completely, very big promotion consignment's processing time and the degree of accuracy, promotion passenger satisfaction and flight punctuality rate.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents and improvements made by those skilled in the art within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. The consigned baggage measurement identification method is characterized by comprising the following steps of:
step 1: the method comprises the steps that after the 3D measuring equipment is calibrated and three-dimensionally modeled, luggage is scanned, and a 3D cloud point depth map and a picture of the luggage are obtained;
step 2: sequentially carrying out plane fitting, filtering and thresholding on the 3D cloud point depth map to obtain a boundary line, and calculating luggage data according to the boundary line;
and step 3: carrying out identification and judgment on the luggage data to obtain luggage state information;
and 4, step 4: and sending the state information and the photos of the luggage to a background management center.
2. The method for consignment baggage measurement identification according to claim 1, wherein said 3D measuring device performs calibration and three-dimensional modeling, comprising in particular the steps of:
establishing a geometric model of camera imaging, solving parameters of the geometric model, namely camera parameters, and completing camera calibration in the 3D measuring equipment;
adjusting the camera according to a camera coordinate system, wherein an original point is positioned at the optical center of a lens of the camera, x and y axes are respectively parallel to two sides of a phase plane, and a z axis is a lens optical axis and is vertical to an image plane;
and drawing a plurality of point clouds of the object into a grid, and then mapping textures, namely the uneven grooves on the surface of the object to form a three-dimensional model, thereby completing three-dimensional modeling.
3. The method for consigned baggage measurement identification as claimed in claim 1, wherein said step 2 comprises the steps of:
step 2.1: performing plane fitting on the 3D cloud point depth map by adopting an OpenCV method;
step 2.2: filtering and denoising the image obtained in the step 2.1 by adopting a median filtering algorithm;
step 2.3: setting a threshold value by utilizing an image pixel point distribution rule, and carrying out pixel point segmentation on the denoised image by adopting a self-adaptive thresholding method so as to obtain a binary image of the image;
step 2.4: and adopting a Canny algorithm to obtain a boundary line of the binary image, and calculating luggage data according to the boundary line.
4. The checked baggage measurement identification method according to claim 3, wherein the baggage data includes a size and a position of the baggage, the size includes a length, a width, a height and a volume of the baggage, and the position includes a rotation angle, a horizontal offset length and a vertical offset length data of the baggage.
5. The method of claim 1, wherein said identifying baggage data comprises: and carrying out sample training on a plurality of baggage data by using a deep learning algorithm, carrying out iteration to obtain a sample model, and then identifying the baggage data to realize baggage classification identification and special-shaped baggage detection.
6. The checked baggage measurement identification method according to claim 1, wherein the baggage status information includes a baggage type, a baggage amount, whether the baggage is within a measurement range, and whether the baggage is regular.
7. The consigned luggage measurement and identification system is characterized by comprising 3D measuring equipment, a main control unit and a background management center, wherein the main control unit is respectively connected with the 3D measuring equipment and the background management center;
the 3D measuring equipment scans the luggage and transmits a 3D cloud point depth map and a picture obtained by scanning to the main control unit;
the main control unit carries out plane fitting, filtering and thresholding on the received 3D cloud point depth map in sequence, then carries out identification and judgment to obtain the state information of the luggage, sends the state information and the picture to a background management center, and drives the 3D measuring equipment to scan after carrying out calibration and three-dimensional modeling on the 3D measuring equipment;
the background management center receives the luggage state information and the photos of the main control unit and issues luggage scanning instructions to the main control unit;
the 3D measuring equipment adopts 3D structured light and image recognition technology to scan the luggage.
8. The consigned baggage measurement and identification method according to claim 7, wherein the system further comprises an RFID identification unit connected to the main control unit, and the RFID identification unit reads and verifies data of the RFID tag in the picture obtained by the 3D measurement device and sends the result to the background management center through the main control unit.
9. The checked baggage measurement identification system according to claim 7, wherein the baggage status information comprises a baggage type, a baggage amount, whether the baggage is within a measurement range, and whether the baggage is regular.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911239311.2A CN110866944A (en) | 2019-12-06 | 2019-12-06 | Consigned luggage measurement and identification method and system |
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| CN112801050A (en) * | 2021-03-29 | 2021-05-14 | 民航成都物流技术有限公司 | Intelligent luggage tracking and monitoring method and system |
| CN113418467A (en) * | 2021-06-16 | 2021-09-21 | 厦门硅谷动能信息技术有限公司 | Method for detecting general and black luggage size based on ToF point cloud data |
| CN113487257A (en) * | 2021-06-30 | 2021-10-08 | 中国民航信息网络股份有限公司 | Luggage management method, related device and storage medium |
| CN113506373A (en) * | 2021-06-29 | 2021-10-15 | 超节点创新科技(深圳)有限公司 | Real-time luggage three-dimensional modeling method, electronic device and storage medium |
| CN114890025A (en) * | 2022-06-02 | 2022-08-12 | 成都思锐因智造科技有限公司 | Garbage pool water material identification method and system based on weighing data |
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| CN111410022A (en) * | 2020-03-31 | 2020-07-14 | 中云智慧（北京）科技有限公司 | Automatic luggage packaging and identifying system and method |
| CN111310740A (en) * | 2020-04-14 | 2020-06-19 | 深圳市异方科技有限公司 | Pedestrian luggage volume measuring device under motion condition |
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| CN111899258A (en) * | 2020-08-20 | 2020-11-06 | 广东机场白云信息科技有限公司 | Self-service consignment luggage specification detection method |
| CN112801050A (en) * | 2021-03-29 | 2021-05-14 | 民航成都物流技术有限公司 | Intelligent luggage tracking and monitoring method and system |
| CN112801050B (en) * | 2021-03-29 | 2021-07-13 | 民航成都物流技术有限公司 | Intelligent luggage tracking and monitoring method and system |
| CN113418467A (en) * | 2021-06-16 | 2021-09-21 | 厦门硅谷动能信息技术有限公司 | Method for detecting general and black luggage size based on ToF point cloud data |
| CN113506373A (en) * | 2021-06-29 | 2021-10-15 | 超节点创新科技(深圳)有限公司 | Real-time luggage three-dimensional modeling method, electronic device and storage medium |
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| CN114890025A (en) * | 2022-06-02 | 2022-08-12 | 成都思锐因智造科技有限公司 | Garbage pool water material identification method and system based on weighing data |
| CN114890025B (en) * | 2022-06-02 | 2023-08-04 | 成都思锐因智造科技有限公司 | Garbage pool water material identification method and system based on weighing data |
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