CN113418467A - Method for detecting general and black luggage size based on ToF point cloud data - Google Patents
Method for detecting general and black luggage size based on ToF point cloud data Download PDFInfo
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Abstract
The invention discloses a method for detecting the size of general and black luggage based on ToF point cloud data, which relates to the technical field of luggage size detection.A world coordinate system of related point cloud data acquired by a ToF camera is rotated along an X axis or a Y axis of the world coordinate system by related angles of the coordinate system, and the rotated new coordinate system is consistent with point cloud coordinate data of parameters when a camera projection plane is installed in parallel with the surface of a conveyor belt, so that the general luggage size detection method can be reapplied to recalculate the size data of the luggage; and in order to eliminate the interference of the pallet on the luggage size measurement, the luggage size detection is carried out after the appearance profile data of the pallet is removed.
Description
Technical Field
The invention relates to the technical field of baggage size detection, in particular to a method for detecting the size of common and black baggage based on ToF point cloud data.
Background
The 3D ToF depth camera adopts a method of optical Time-of-Flight (ToF) ranging: firstly, infrared light with a specific wavelength (850nm) is modulated and emitted by a camera, the infrared light is reflected to a ToF sensor of a depth camera when encountering an obstacle, each pixel of the ToF sensor captures the phase difference between the emitted infrared light and the received infrared light, and the phase difference is converted into the flight time of the light by an operation unit, so that the distance between the camera and a target object can be calculated. When an infrared reflection type sensor is used for testing a black object, due to the fact that reflection is small, the black luggage and the luggage with smooth surfaces are easy to interfere in detection of depth data related to a camera, accuracy of size detection of the luggage is further affected, and in order to guarantee detection accuracy of luggage with all colors, the ToF camera can conduct integration through adjustment of integration time HDR, high dynamic range measurement and long and short time exposure data. The short integration time is used for measuring a near area, the long integration time is used for measuring a far area, and the far and near measurement spaces are integrated, so that the distance measurement can be carried out on a near object and a far object, and the problem of black object detection interference is eliminated.
After the ToF camera is ensured to acquire high-quality point cloud data, the relevant size of the baggage can be detected and calculated, the detection of the baggage is to automatically start a conveyor belt to advance by self-service equipment after the passenger consigns the baggage to the surface of the conveyor belt, and the baggage is conveyed to a certain specific area of the conveyor belt for detection, and the common method for detecting the size of the baggage is discussed as follows:
step A, firstly, confirming the relevant installation height value of the camera, and enabling the emitting surface of the ToF camera to be in parallel relation with the surface of the conveyor belt, as shown in figure 1;
step B, due to the influence of relevant equipment parameters of the lens view angle of the ToF camera, detected data of the ToF camera can exceed the detection area range of actual luggage after the ToF camera is installed at a fixed position, and the relevant data of the detection range needs to be filtered in advance, so that the influence of the existence of fixed installation equipment of existing self-service equipment exceeding the detection range on the detection of the actual size of the luggage is avoided, and the size of the maximum luggage operated in an airport is as follows: (length: 900mm, width 400mm, height: 600mm), thus confirming the detection range of the baggage point cloud data as shown in FIG. 2;
step C, projecting the filtered point cloud data to an XY plane, and detecting and calculating the length and width dimensions of the luggage according to the boundaries of the boundary graphs of the relevant luggage projected on the XY plane, as shown in FIG. 3;
and step D, projecting the filtered point cloud data to an XZ plane in the same way, and detecting and calculating the height value of the luggage according to the boundary of the related luggage boundary graph projected on the XZ plane, as shown in fig. 4.
However, the above detection method is based on the premise that the emitting plane of the ToF camera is parallel to the plane of the conveyor belt, then the plane contour generated by projecting the related point cloud data on the corresponding coordinate plane is calculated to obtain the related baggage size value, and during the actual project implementation process, the emitting plane of the ToF camera is not parallel to the surface of the conveyor belt but has a certain inclination angle due to part of equipment installation reasons; in this case, the general projection detection method is still adopted, and the situation that the detected luggage is compressed inevitably leads to inaccurate detection results; therefore, the detection of the general projection can be applied only after the point cloud coordinate data is preprocessed under the condition that the ToF camera has a certain inclination angle after being installed.
In addition, due to the relevant reasons that the luggage for passenger to consign is too light or small, the luggage for passenger to consign can be required to be consigned by using the tray, so that a new problem is caused, namely the length and width of the luggage detected by the method are the length and width of the tray; in order to eliminate the interference of the pallet on the luggage size measurement, the luggage size detection of the method can be carried out only after the appearance contour data of the pallet is removed.
Therefore, as self-service baggage consignment equipment is continuously popularized in various domestic airports, the relevant size of the baggage consignment of passengers is accurately detected, and an implementation mode which is efficient, feasible and convenient and fast in equipment installation is provided, so that the requirement of the field is urgent.
Disclosure of Invention
The invention solves the technical problem and provides a method for detecting the size of general and black luggage based on ToF point cloud data.
The invention provides a method for detecting the size of general and black luggage based on ToF point cloud data, which comprises the following steps:
step 1, confirming the installation inclination angle of a camera, and confirming the included angle of the inclination angle of the camera in the X-axis direction and the Y-axis direction;
step 2, after the vertex of the world coordinate system of the existing point cloud data is positioned and the included angle in the step 1 is rotated along the X-axis direction and the Y-axis direction, the new coordinate system is the point cloud coordinate data of the coordinate system under the condition that the emission plane of the ToF camera is parallel to the surface of the conveyor belt;
step 3, firstly, calculating a related coordinate transformation formula I of the rotation angle alpha along the Y-axis direction as follows:
z'＝xsinα+zcosα
x'＝xcosα-zsinα
after conversion is carried out according to the related trigonometric function of the formula I, the coordinate related value of the newly rotated new coordinate system point cloud data can be transformed and correspond in the new coordinate system;
and 4, substituting the coordinate values transformed in the step 3 into a second coordinate transformation formula of the following rotation angle beta along the X-axis direction again:
z'＝ysinβ+zcosβ
y'＝ycosβ-zsinβ
and 5, reusing the point cloud value in the new transformed coordinate system by a common luggage size detection method to output an accurate luggage size value.
Preferably, when the luggage is placed on the tray, the method further comprises the following steps:
step 6, the luggage to be detected can be photographed through a 2D common camera, whether a passenger ships a tray or not can be identified through a deep learning technology, and if yes, the next step is carried out;
step 7, filtering point cloud data, namely filtering data of a baggage detection range;
step 8, calculating the minimum X and Y coordinates of the point cloud data, and translating the point cloud data X and Y to a first quadrant;
step 9, generating a gray map from the point cloud data;
step 10, carrying out contour recognition on the gray level image;
and 11, recalculating the size of the luggage by using the coordinate projection contour edge calculation method again for the coordinate data after contour filtering, so that the related size of the actual luggage can be calculated correctly.
Preferably, step 10 further comprises:
step 101, if the sub-outline exists, considering the sub-outline to be a tray, if the outline identifies that deflection exists, rotating the tray to be horizontal;
102, calculating coordinates of four corners of the tray;
step 103, the coordinates related to the contour are cleared by using the coordinates.
The invention has the beneficial effects that: rotating a world coordinate system of related point cloud data acquired by a ToF camera along an X axis or a Y axis of the world coordinate system by a related angle of the coordinate system, and enabling a new rotated coordinate system to be consistent with point cloud coordinate data of parameters when a camera projection plane is installed in parallel with the surface of a conveyor belt, so that the general luggage size detection method can be reapplied, and the size data of luggage can be recalculated; and in order to eliminate the interference of the pallet on the luggage size measurement, the luggage size detection is carried out after the appearance profile data of the pallet is removed.
Drawings
FIG. 1 is a schematic diagram of the installation of a TOF camera and its related detection area in a conventional method;
FIG. 2 is a schematic diagram of a detection range of baggage point cloud data in a conventional method;
FIG. 3 is a schematic diagram of the boundary of a related baggage projected on an XY plane according to a prior art method;
FIG. 4 is a schematic diagram of the boundary of the relevant baggage projected on the XZ plane in the prior art method;
FIG. 5 is a schematic diagram of the installation and related detection areas of the ToF camera according to the present invention;
FIG. 6 is a schematic diagram of the coordinate transformation of the rotation angle α along the Y-axis direction;
FIG. 7 is a schematic diagram of coordinate transformation along the X-axis direction by a rotation angle β;
fig. 8 is a schematic view of baggage pallet contour recognition.
Detailed Description
The present invention will be further illustrated with reference to the following specific examples.
The ToF measuring technology is basically similar to the principle of a 3D laser sensor, except that the 3D laser sensor scans point by point, and a ToF camera obtains depth information of the whole image simultaneously, so that the ToF camera can calculate the depth information quickly in real time. The ToF depth calculation is not influenced by the surface gray scale and characteristics of the object, and three-dimensional detection can be accurately carried out. The binocular stereo camera requires good feature change of the target, otherwise, depth calculation cannot be performed. Therefore, the method adopts the ToF scheme to carry out the related size detection of the baggage so as to adapt to the detection of various baggage in an airport.
As discussed in the above general detection method, the projection plane of the ToF camera needs to be parallel to the surface of the conveyor belt, so that when the ToF camera is installed with a certain inclination angle, the world coordinate system of the relevant point cloud data acquired by the ToF camera needs to be rotated by the relevant angle of the coordinate system along the X axis or the Y axis thereof, and the new rotated coordinate system is made to be consistent with the point cloud coordinate data of the parameters when the projection plane of the camera is installed parallel to the surface of the conveyor belt, so that the general baggage size detection method can be reapplied to recalculate the size data of the baggage; the following steps are related calculation methods:
1. firstly, confirming the installation inclination angle of a camera, and confirming the included angle of the inclination angle of the camera in the X-axis direction and the Y-axis direction;
2. after the vertex of the world coordinate system residing in the existing point cloud data rotates the angle in the step 1 along the directions of the X axis and the Y axis, as shown in fig. 5, the new coordinate system is the point cloud coordinate data of the coordinate system under the condition that the emission plane of the ToF camera is parallel to the surface of the conveyor belt;
3. converting the coordinate correlation value of the newly rotated new coordinate system point cloud data in a new coordinate system according to the related trigonometric function of the following formula;
as shown in fig. 6, the related coordinate transformation formula of the rotation angle α along the Y-axis direction is first calculated as follows:
z'＝xsinα+zcosα
x'＝xcosα-zsinα
as shown in fig. 7, the transformed coordinate values are then re-substituted into the following coordinate transformation formula two of the rotation angle β in the X-axis direction as follows:
z'＝ysinβ+zcosβ
y'＝ycosβ-zsinβ
4. the point cloud value in the new coordinate system after transformation can output the accurate value of the luggage size by reusing the general luggage size detection method;
in addition, due to the relevant reasons that the luggage for passenger to consign is too light or small, the luggage for passenger to consign can be required to be consigned by using the tray, so that a new problem is caused, namely the length and width of the luggage detected by the method are the length and width of the tray; in order to eliminate the interference of the pallet on the measurement of the size of the luggage, the size of the luggage can be detected by the method after the appearance contour data of the pallet is removed.
The method for eliminating the interference of the size of the tray after the luggage is placed in the tray comprises the following steps:
5. firstly, the luggage to be detected can be photographed by a 2D common camera, whether a passenger has a tray for checking the luggage or not can be identified by a deep learning technology, and if so, the luggage is removed in the following mode;
6. filtering point cloud data; firstly, data filtering of a baggage detection range is carried out according to the general method;
7. calculating the minimum X and Y coordinates of the point cloud data; translating the point cloud data X and Y to a first quadrant;
8. generating a gray scale map from the point cloud data;
9. carrying out contour recognition on the gray-scale image, as shown in FIG. 8;
a. if the sub-profile exists, the tray is considered to be a tray, if the profile identifies that deflection exists, the tray is rotated to be horizontal;
b. calculating coordinates of four corners of the tray;
c. the coordinates related to the contour are cleared by using the coordinates;
10. and (4) recalculating the size of the luggage by using the coordinate projection contour edge calculation method again for the coordinate data after contour filtering, so that the related size of the actual luggage can be calculated correctly.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (3)
1. A method for detecting the sizes of general and black luggage based on ToF point cloud data is characterized by comprising the following specific steps:
step 1, confirming the installation inclination angle of a camera, and confirming the included angle of the inclination angle of the camera in the X-axis direction and the Y-axis direction;
step 2, after the vertex of the world coordinate system of the existing point cloud data is positioned and the included angle in the step 1 is rotated along the X-axis direction and the Y-axis direction, the new coordinate system is the point cloud coordinate data of the coordinate system under the condition that the emission plane of the ToF camera is parallel to the surface of the conveyor belt;
step 3, firstly, calculating a related coordinate transformation formula I of the rotation angle alpha along the Y-axis direction as follows:
z'＝xsinα+zcosα
x'＝xcosα-zsinα
after conversion is carried out according to the related trigonometric function of the formula I, the coordinate related value of the newly rotated new coordinate system point cloud data can be transformed and correspond in the new coordinate system;
and 4, substituting the coordinate values transformed in the step 3 into a second coordinate transformation formula of the following rotation angle beta along the X-axis direction again:
z'＝ysinβ+zcosβ
y'＝ycosβ-zsinβ
and 5, reusing the point cloud value in the new transformed coordinate system by a common luggage size detection method to output an accurate luggage size value.
2. The method of claim 1, wherein when the baggage is placed on the pallet, the method further comprises:
step 6, the luggage to be detected can be photographed through a 2D common camera, whether a passenger ships a tray or not can be identified through a deep learning technology, and if yes, the next step is carried out;
step 7, filtering point cloud data, namely filtering data of a baggage detection range;
step 8, calculating the minimum X and Y coordinates of the point cloud data, and translating the point cloud data X and Y to a first quadrant;
step 9, generating a gray map from the point cloud data;
step 10, carrying out contour recognition on the gray level image;
and 11, recalculating the size of the luggage by using the coordinate projection contour edge calculation method again for the coordinate data after contour filtering, so that the related size of the actual luggage can be calculated correctly.
3. The method of claim 2, wherein step 10 further comprises:
step 101, if the sub-outline exists, considering the sub-outline to be a tray, if the outline identifies that deflection exists, rotating the tray to be horizontal;
102, calculating coordinates of four corners of the tray;
step 103, the coordinates related to the contour are cleared by using the coordinates.
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