CN116392077A - Razor back detection system based on three-dimensional depth image and control method - Google Patents
Razor back detection system based on three-dimensional depth image and control method Download PDFInfo
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Abstract
The invention relates to a razor back detection and evaluation method based on a three-dimensional depth image, belonging to the technical field of photoelectric detection technology and three-dimensional depth image processing. Acquiring three-dimensional depth images of the back of the subject in different positions under the forward bending state by a depth camera; selecting and dividing the upper edge and the lower edge of the back ROI area; the method comprises the steps of (1) constructing a back spine reference line model by carrying out feature point identification on a detection area; coordinate conversion is carried out on the point cloud data, and the height difference of the left side and the right side of the back is obtained through calculation; and the comprehensive evaluation of the back razor back condition of the tested person is realized by combining a preset razor back height difference threshold value. According to the invention, the three-dimensional depth image obtained by multi-pose acquisition is combined with the artificial intelligence related digital image processing technologies such as feature point extraction, section profile analysis and the like, so that the problems that the traditional razor back detection process depends on the experience of a professional doctor, is non-uniform in standard, has large human error, and has large X-ray radiation and the like are well solved.
Description
Technical Field
The invention relates to the technical field of photoelectric detection and the technical field of three-dimensional depth image processing, in particular to a razor back detection system based on a three-dimensional depth image and a control method.
Background
In China, scoliosis has become the third biggest disease seriously threatening the physical and mental health of children and teenagers after myopia and obesity. In scoliosis, due to the protrusion or depression of two ribs caused by axial rotation of the spine, the bilateral asymmetry of the back not only affects the physical appearance of a patient, but also can cause the patient to feel painful in daily sitting and standing and breathe unsmooth, thereby further causing the patient to feel more severe in the sped feeling and a series of psychological disorders. The observation of whether the back of the tested person has uneven left and right sides, namely the phenomenon of razor back, through the forward bending test posture is a very important examination in scoliosis screening.
The current method for checking the back of the shaver in clinic mainly adopts a method of measuring the rotation angle of the trunk manually by means of manual visual observation or scoliosis ruler. According to the diagnosis standard of the scoliosis patient in the clinical diagnosis and treatment guide and orthopedics minute book, the subject is guided to carry out the anteflexion test. The method for manual visual observation comprises the following steps: eyes of the inspector are at the same height with the back of the inspector, eyes are parallel to the eyes of the inspector and bend from head to tail along with the inspector, and from thoracic vertebrae to lumbar vertebrae, whether the two sides of the spine are uneven or not is observed; method of measurement using scoliosis ruler: and (5) respectively measuring each section (chest section, chest waist section and waist section) of the spine of the tested person by using a trunk rotation measuring instrument, and recording the maximum rotation angle and the position, wherein if the most serious position of back asymmetry exceeds 5 degrees, the spine is highly suspected to be bent sideways. Both methods are based on manual detection, depend on the skills and experience of professional doctors seriously, are not uniform in standard, are easy to generate false detection and omission detection, and are poor in screening effect.
Aiming at the problems, in order to meet the requirement of screening scoliosis of large-scale children and young people, and realize early screening, early diagnosis and early treatment, a safe, effective and rapid razor back detection method is urgently needed, and automatic acquisition, detection and evaluation of razor back data are realized.
Disclosure of Invention
Aiming at the problems of non-uniform razor back inspection standard and complex process in the prior art, the invention aims to provide a razor back detection system based on a three-dimensional depth image and a control method.
The embodiment of the invention is realized by the following technical scheme:
in a first aspect, the present invention provides a razor back detection system control method based on a three-dimensional depth image, comprising;
collecting three-dimensional depth images of a subject at different bending angles;
based on the obtained three-dimensional depth image, selecting the upper and lower edge range of the back, and determining the position of the spine reference line of the back;
based on the three-dimensional depth image and the spine reference line, extracting key points of the three-dimensional depth image protruding along two sides of the reference line, and measuring and calculating the height difference of the left side and the right side of the back;
and analyzing and processing the height difference data, and comprehensively evaluating the razor back detection result of the tested person.
In an embodiment of the invention, the selecting the upper and lower back edge range further includes;
according to the three-dimensional depth image, determining that the upper edge of the back is the highest position of the back which can be shot, and the lower edge of the back is the position above the underpants belt of the detected person;
the three-dimensional depth data area between the upper edge and the lower edge is defined as a razor back detection area;
in one embodiment of the present invention, the determining the location of the dorsal spinal reference line further comprises;
measuring and calculating the lowest concave point of the profile of the back section in the razor back detection area;
all nadir points are connected and recorded as where the spinal reference line is located.
In an embodiment of the present invention, the key points further include;
searching the protruding extreme points on the left side and the right side as key points by taking the spine reference line as the center along the back section outline of the tested person.
In an embodiment of the invention, the height difference further comprises;
establishing an XYZ-direction three-dimensional coordinate system;
and calculating a Z-direction data difference value according to the depth information of the key points on the left side and the right side of the back to obtain the height difference on the left side and the right side of the current back.
In one embodiment of the present invention, the analyzing and processing the height difference data further comprises;
sequentially measuring and calculating the height difference of the left side and the right side of the back of the tested person from top to bottom along the back;
extracting a data result with the largest height difference;
determining that the data result is derived from the chest position, chest waist position or waist position of the subject;
processing the three-dimensional depth images of the back of the testee under different bending angles;
and setting a threshold value for comparison and analysis to obtain a result.
In a second aspect, the present invention provides a razor back detection system based on a three-dimensional depth image, which is characterized by comprising;
the first module is used for collecting and shooting back morphology of the subject under different bending angles when the subject is bent forwards;
the second module is used for reconstructing the three-dimension of the back and establishing a three-dimension coordinate point so as to generate a depth model with the height consistent with the actual shape of the back of the detected person;
a third module for selecting the upper and lower edges of the back of the subject to be examined and segmenting the three-dimensional depth model;
and the processing unit is connected with the first module, the second module and the third module and is used for executing the razor back detection system control method based on the three-dimensional depth image.
In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the method for controlling a razor back detection system based on a three-dimensional depth image when executing the computer program.
In a fourth aspect, the present invention provides a computer readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, implements a method for controlling a razor back detection system based on a three-dimensional depth image as described above.
The technical scheme of the embodiment of the invention has at least the following advantages and beneficial effects:
the embodiment of the invention provides a safe, effective and quick razor back detection method based on three-dimensional depth image data and by utilizing artificial intelligence related digital image processing technologies such as characteristic point extraction, section contour analysis and the like around the aspects of multi-pose acquisition, accurate algorithm analysis, high-efficiency data processing and the like, and can effectively solve the problems that the traditional razor back detection process depends on the experience of a professional doctor, is non-uniform in standard, has large human error, has large X-ray radiation, is difficult to realize large-scale screening and the like.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a general flow chart of the detection method of the present invention;
FIG. 2 is a schematic illustration of a subject bending 30 degrees;
FIG. 3 is a schematic view of a subject bent 45 degrees;
FIG. 4 is a schematic illustration of a subject bent 90 degrees;
FIG. 5 is a back depth data map of a small anterior flexion angle (about 30);
FIG. 6 is a back depth data map of a large angle of forward flexion (about 45);
fig. 7 is a back depth data map of forward flexion to a limit (about 90 °).
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. The naming or numbering of the steps in the present application does not mean that the steps in the method flow must be executed according to the time/logic sequence indicated by the naming or numbering, and the execution sequence of the steps in the flow that are named or numbered may be changed according to the technical purpose to be achieved, so long as the same or similar technical effects can be achieved.
The invention provides a razor back detection system control method based on a three-dimensional depth image, which aims to simplify the traditional razor back detection process and integrate three-dimensional depth image acquisition, an artificial intelligence algorithm and razor back evaluation analysis:
the shaver back evaluation analysis is to sequentially calculate the height difference of the left side and the right side of the back of the tested person from top to bottom along the back, extract the data result with the largest height difference, and determine the position of the chest section, the chest and waist section or the waist section of the tested person from which data is sourced. The comprehensive evaluation result of the shaver back examination is finally generated by processing three-dimensional depth images of the back of the testee under different bending angles and combining set threshold comparison analysis.
The invention provides a razor back detection system control method based on a three-dimensional depth image, which comprises the following steps of;
s101: collecting three-dimensional depth images of a subject at different bending angles;
in this step, it is necessary to stand the subject in the forward flexed position: the subject faces away from the camera, the two feet are gathered together to expose the back, a natural standing posture is adopted, the forward bending action is completed according to prompt of a detector, and the bending angle of the back is continuously increased under the forward bending posture until 90-degree bending is achieved.
Acquiring three-dimensional depth image data: as shown in fig. 2, a plurality of three-dimensional depth images of the back of the subject are acquired by using a depth camera to analyze whether the razor back phenomenon exists in different parts such as the chest section, the chest and waist section, the waist section and the like.
S102: based on the obtained three-dimensional depth image, selecting the upper and lower edge range of the back, and determining the position of the spine reference line of the back;
and (3) dividing target areas of the human back depth images acquired in the step (S101) to generate back spine reference line trend.
Target area division: and determining the positions of the upper edge of the back of the human body, the shooting background, the lower edge of the back and the trouser bands of the tested person in the depth image, and defining an ROI (region of interest) for detecting the razor back.
Dorsal spinal reference line trend: and searching the lowest point of the concave of the profile curve of the vertical back section in the razor back detection area, recording the lowest point as the position of the spine reference line of the back of the razor, and continuously repeating the steps from top to bottom until a spine reference line model of the whole razor back detection area is generated, so as to obtain the trend of the spine reference line of the back.
S103: based on the three-dimensional depth image and the spine reference line, extracting key points of the three-dimensional depth image protruding along two sides of the reference line, and measuring and calculating the height difference of the left side and the right side of the back;
and (3) according to the back spine reference line obtained in the step (S102), carrying out coordinate conversion by utilizing depth information, searching key points protruding at two sides of the back spine reference line, and measuring and calculating the height difference of the two sides of the back.
Depth coordinate conversion: and (3) dividing the back spine reference line obtained in the step (S102) into a plurality of sections according to a certain proportion, selecting a back region for measurement and calculation in a segmented mode according to the forward bending degree, and taking the spine reference line in the section as the reference line of each pose. As shown in the figure, a plane is formed by selecting a normal vector which is connected with a first pixel point and a last pixel point of each section and is common to a Z axis (a direction perpendicular to a camera lens is called a Z axis), the normal vector perpendicular to an XY plane is a rotation direction, all 3D point data of the section are rotated around an X axis by a corresponding angle, and the heights of the back of the section are all converted into new Z axis coordinates to finish depth coordinate conversion;
searching key points of the back of the two sides: as shown in fig. 3, 4 and 5, for the chest section, chest waist section and waist section corresponding to different poses, taking a spine reference line as a distinction, searching the most obvious key points of the protrusions on two sides, and thus locating 1-3 pixel areas where the maximum points of the Z-direction coordinates are located, namely the coordinates of the key points;
s104: and analyzing and processing the height difference data, and comprehensively evaluating the razor back detection result of the tested person.
Bilateral back height difference: calculating the height difference of the area where the key point is located, finding the maximum height difference of each section, and comparing the height differences of each section to find the maximum height difference of the pose.
And integrating the double-sided back height differences of the testee in multiple postures, and carrying out analysis and comparison by combining with a set threshold value to generate an evaluation conclusion of the shaver back so as to complete the detection flow.
In summary, the height difference of the left and right sides of the back of the subject is sequentially measured from top to bottom along the back, the data result with the largest height difference is extracted, and the position of the chest section, the chest and waist section or the waist section of the subject from which the data is derived is determined. The comprehensive evaluation result of the shaver back examination is finally generated by processing three-dimensional depth images of the back of the testee under different bending angles and combining set threshold comparison analysis.
In an embodiment of the invention, the selecting the upper and lower back edge range further includes determining, according to the three-dimensional depth image, that the upper back edge is a highest position of the back that can be photographed, that the lower back edge is a position above the underpants of the subject, and defining a three-dimensional depth data area between the upper and lower edges as a razor back detection area; in the razor back detection area, the lowest points of the back section profile depression were measured, all of which were connected and recorded as the locations of the spinal reference lines.
The invention also provides a razor back detection system based on the three-dimensional depth image, which is characterized by comprising the following components;
the first module is used for collecting and shooting back morphology of the subject under different bending angles when the subject is bent forwards;
the second module is used for reconstructing the three-dimension of the back and establishing a three-dimension coordinate point so as to generate a depth model with the height consistent with the actual shape of the back of the detected person;
a third module for selecting the upper and lower edges of the back of the subject to be examined and segmenting the three-dimensional depth model;
and the processing unit is connected with the first module, the second module and the third module and is used for executing the razor back detection system control method based on the three-dimensional depth image.
The above modules are further explained as:
the three-dimensional depth image acquisition mainly comprises the steps of shooting back morphology of a tested person under different bending angles through a depth camera, realizing three-dimensional reconstruction of the back, establishing three-dimensional coordinate points, and further generating a depth model which is highly consistent with the actual back morphology of the tested person.
The artificial intelligence algorithm is to complete the automatic selection of the upper and lower edge ROI areas of the back of the testee and divide the three-dimensional depth model by means of training and learning the prior human back knowledge by a high-performance computer; obtaining the lowest points of the concave section profiles at different positions of the back through searching and traversing, and realizing the extraction of the spine reference line of the back of the human body; searching the raised extreme points on the left side and the right side of the spine reference line along the contour of the back section, and calculating to obtain the height difference on the left side and the right side of the current position.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. The computer software product is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the various embodiments of the invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The razor back detection system control method based on the three-dimensional depth image is characterized by comprising the following steps of;
collecting three-dimensional depth images of a subject at different bending angles;
based on the obtained three-dimensional depth image, selecting the upper and lower edge range of the back, and determining the position of the spine reference line of the back;
based on the three-dimensional depth image and the spine reference line, extracting key points of the three-dimensional depth image protruding along two sides of the reference line, and measuring and calculating the height difference of the left side and the right side of the back;
and analyzing and processing the height difference data, and comprehensively evaluating the razor back detection result of the tested person.
2. The method for controlling a razor back detection system based on three-dimensional depth images according to claim 1, wherein selecting the upper and lower back edge ranges further comprises;
according to the three-dimensional depth image, determining that the upper edge of the back is the highest position of the back which can be shot, and the lower edge of the back is the position above the underpants belt of the detected person;
the three-dimensional depth data area between the upper and lower edges is defined as the razor back detection area.
3. The method of claim 2, wherein determining the location of the dorsal spinal reference line further comprises;
measuring and calculating the lowest concave point of the profile of the back section in the razor back detection area;
all nadir points are connected and recorded as where the spinal reference line is located.
4. The method for controlling a razor back detection system based on a three-dimensional depth image according to claim 1, wherein the key points further comprise;
searching the protruding extreme points on the left side and the right side as key points by taking the spine reference line as the center along the back section outline of the tested person.
5. The method of claim 4, wherein the height difference further comprises;
establishing an XYZ-direction three-dimensional coordinate system;
and calculating a Z-direction data difference value according to the depth information of the key points on the left side and the right side of the back to obtain the height difference on the left side and the right side of the current back.
6. The method of claim 1, wherein analyzing and processing the height difference data further comprises;
sequentially measuring and calculating the height difference of the left side and the right side of the back of the tested person from top to bottom along the back;
extracting a data result with the largest height difference;
determining that the data result is derived from the chest position, chest waist position or waist position of the subject;
processing the three-dimensional depth images of the back of the testee under different bending angles;
and setting a threshold value for comparison and analysis to obtain a result.
7. A razor back detection system based on three-dimensional depth images, comprising;
the first module is used for collecting and shooting back morphology of the subject under different bending angles when the subject is bent forwards;
the second module is used for reconstructing the three-dimension of the back and establishing a three-dimension coordinate point so as to generate a depth model with the height consistent with the actual shape of the back of the detected person;
a third module for selecting the upper and lower edges of the back of the subject to be examined and segmenting the three-dimensional depth model;
a processing unit, which is connected to the first module, the second module and the third module, and performs a method for controlling a razor back detection system based on a three-dimensional depth image according to any one of claims 1 to 6.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements a three-dimensional depth image based razor back detection system control method according to any one of claims 1 to 6 when executing the computer program.
9. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when executed by a processor, the computer program implements a method for controlling a razor back detection system based on a three-dimensional depth image according to any one of claims 1 to 6.
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