Easy-to-operate oral cavity extracted sample full-process tracking identification method and system

Abstract

The invention relates to the technical field of image analysis, in particular to an easy-to-operate oral cavity extracted sample full-process tracking identification method and system.The method comprises the steps that initialization setting is conducted, specifically, a corresponding library and a storage library are established, and size data corresponding to collection boxes of various models and distance parameters of placement holes are stored in the corresponding library; a sampling step: making a mark on one side edge of the collection box, then continuously obtaining an overlook picture of the collection box, when the sample tube is put into the collection box after sampling, the color corresponding to the center coordinate of a single placement hole changes, and packaging and storing the patient information of the sample tube, the mark of the collection box and the information of the placement hole into a storage library; and a detection step: continuously obtaining the overlook picture of the collection box, when the sample tube is taken out of the collection box, the color corresponding to the center coordinate of the single placement hole changes, and finding the corresponding patient information from the storage library according to the collection box mark and the placement hole information. The method can effectively solve the problem of low operation efficiency of the traditional sample tracking and identification process.

Description

Technical Field

[0001] The present invention relates to the technical field of image analysis, and in particular to an easy-to-operate full-process tracking and identification method and system for oral extraction samples. Background Art

[0002] In clinical practice, it is often necessary to extract oral extracts from patients, and then analyze the extracts to respond to the patient's symptoms. Traditionally, when tracking such extracts, it is necessary to attach identification labels to the sample tubes. Each time one is collected or taken out for use, the label on the sample tube needs to be identified. At this time, the personnel need to turn the sample tube to an angle with the label facing outward, and then use a handheld reading device to identify the barcode or QR code on the label. It can be seen that the traditional operation method requires more steps. Since oral extracts are usually extracted and tested faster, the frequency of placing and removing sample tubes will be required to be faster than other sampling. Therefore, the traditional tracking method is inefficient and affects the efficiency of personnel operations. Summary of the invention

[0003] The present invention provides an easy-to-operate method and system for tracking and identifying the entire process of oral sample extraction, which can effectively solve the problem of low operating efficiency of the traditional sample tracking and identification process.

[0004] The present invention provides an easy-to-operate oral sample extraction full-process tracking and identification method, the steps comprising: Initialization setting: establish corresponding library and storage library, in which the corresponding library stores the size data of each type of collection box and the distance parameters between each placement hole and the reference point; Sampling steps: mark one side of the collection box, then continuously obtain overhead photos of the collection box, and use image analysis to obtain the collection box mark, the center coordinates of all placement holes and their corresponding colors in each photo; When the sample tube is put into the collection box after sampling, the color corresponding to the center coordinate of a single placement hole will change, and the patient information, collection box mark and placement hole information of this sample tube will be packaged and stored in the storage library; Detection steps: continuously obtain overhead photos of the collection box, and use image analysis to obtain the collection box mark, the center coordinates of all placement holes and their corresponding colors in each photo; When the sample tube is taken out of the collection box, the color corresponding to the center coordinate of a single placement hole will change, and the corresponding patient information will be found from the storage library according to the collection box mark and the placement hole information; The image analysis method specifically includes the following steps: S10: binarizing the photo to obtain a processed image; S20: judging the model of the collection box according to the area of ​​the white pixel points in the processed image, and finding the distance parameter corresponding to the collection box from the corresponding library; S30: obtaining a collection box area in the processed image; S40: Find the coordinates of the reference point corresponding to the collection box; S50: According to the found reference point coordinates and distance parameters, the center coordinates of all placement holes of the collection box are obtained.

[0005] Furthermore, the collection box is white, and at least the top of the sample tube is white; when obtaining a top-down photograph of the collection box, the collection box is placed on a platform at least the top of which is black.

[0006] Furthermore, the specific steps of the image analysis method step S30 are: S31: Assume that the pixel point at the xth row and yth column of the processed image is (x, y); S32: The pixel with white color and the smallest x value is recorded as A(x A ,y A ) point; if there are multiple white pixels with the smallest x value, the pixel with the smallest y value is recorded as A(x A ,y A )point; S33: Establish judgment point B(x B ,y B ) point and C(x C ,y C ) point; let x B =x C =x A ,y B =y C =y A ; S34: In the xth B+1 In the column, y B As the starting point, judge the color of the pixels upwards, stop when you first encounter a black pixel, and then judge the point B (x B ,y B ) point is updated to the white pixel point with the largest y value found at this time, and returns to S34 until no white pixel point that meets the requirements appears; S35: In the xth C+1 In the column, y C As the starting point, judge the color of the pixel points downwards, stop when you first encounter a black pixel point, and then change the judgment point C(x C ,y C ) point is updated to the white pixel point with the largest y value found at this time, and returns to S35 until no white pixel point that meets the requirements appears; S36: Calculate the lengths of line segment AB and line segment AC, and compare them with the size data of the collection box, so as to determine the length and width direction of the collection box in the processed image, and then obtain the collection box area in the processed image.

[0007] Further, in the image analysis method step S36, it is determined whether the lengths of line segment AB and line segment AC are equal to the length and width of the collection box; If the two line segments can correspond to the length and width of the collection box respectively, then the two line segments are recorded as the length and width of the collection box respectively; If a line segment can correspond to the length or width of the collection box, and the other line segment is larger than the length of the collection box, the line segment that can correspond is recorded as the length or width of the collection box; If any of the line segments is smaller than the width of the collection box, all pixels on the two line segments are updated to black, and then the process returns to S32.

[0008] Furthermore, in the image analysis method step S20, the number of collection boxes N is determined based on the area of ​​white pixels in the processed image; In the image analysis method step S30, a cycle value T is set to 0 in step S31, and further includes: S37: Add 1 to the loop value T, then remove all pixel coordinates in the determined collection box area, and then return to S32. The removed pixel coordinates will no longer participate in subsequent calculations.

[0009] Further, the collection box is marked with a bar code.

[0010] Furthermore, the specific steps of the image analysis method step S40 are: S41: according to the length or width of the side of the collection box where the barcode is located, offset the two lengths or widths of the collection box area in the processing image into the collection box area by a distance L to form two offset lines; S42: On each offset line, a change value G is first set to 0, and the colors of all two adjacent pixels on the same offset line are compared, and the change value is increased by 1 each time the colors are different; after the colors of the pixels on the two offset lines are compared, two change values ​​G1 and G2 can be obtained respectively; S43: Compare the sizes of G1 and G2, and use an endpoint of the side corresponding to the larger change value as the reference point.

[0011] Furthermore, after sampling, before the sample tube is placed in the collection box, a verification mark is affixed to the side of the sample tube, and the verification mark is stored in the storage repository together with the patient information, the collection box mark and the placement hole information.

[0012] Furthermore, before the detection step, take out any sample tube in the collection box and read its side verification mark to confirm whether the collection box mark found in its corresponding storage repository is the same as the mark on the collection box. After confirming that they are the same, put the sample tube back to its original position in the collection box.

[0013] The present invention also provides an easy-to-operate oral sample extraction full-process tracking and identification system, which is used for the above-mentioned easy-to-operate oral sample extraction full-process tracking and identification method, comprising: The collection box is provided with a plurality of placement holes distributed in an array, and the placement holes vertically penetrate the collection box; a mark is provided on the top side of the collection box; A sample tube is placed in the placement hole; A placement table, used for placing the collection box; the color of the top surface of the placement table is different from the color of the collection box and the sample tube; A camera, fixedly arranged above the placement table, for taking photos; The processor is used to process and calculate the taken photos.

[0014] The technical solution of the present invention can achieve the following technical effects: The present invention continuously photographs the collection box, calculates the positions of the placement holes on the collection box, and continuously monitors the color changes of the placement holes. The placement and removal of the sample tubes are analyzed by the color changes, and the patient information corresponding to the sample tubes can be automatically found, thereby effectively reducing the operating steps of personnel and effectively improving the operating efficiency of personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a structural schematic diagram of the easy-to-operate oral sample extraction full-process tracking and identification system of the present invention; Figure 2 It is a schematic diagram of the structure of the collection box in the present invention; Figure 3 A top view of the collecting box of the present invention; Figure 4 This is a processing image when a single collection box is included in the present invention; Figure 5 For the present invention Figure 4 The enlarged view of K; Figure 6The processing image of the present invention when a plurality of collecting boxes are included and the collecting boxes are attached to each other; Figure 7 The processing image of the present invention when a plurality of collecting boxes are included and the collecting boxes are attached to each other at another angle; Figure numerals: 1. Collection box; 11. Placement hole; 2. Sample tube; 3. Placement table; 4. Camera. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0018] In the description of the present invention, it should be noted that the orientations or positional relationships indicated by “center”, “up”, “down”, “left”, “right”, “vertical”, “horizontal”, “inside” and “outside”, etc., are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0019] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0020] The present invention relates to an easy-to-operate oral sample extraction full-process tracking and identification method, which includes an initialization step of setting basic information, a sampling step of extracting oral samples from patients on site, and a detection step of taking out oral samples for use in a laboratory. The specific contents of each step are as follows: Initialization settings: establish corresponding libraries and storage libraries; the corresponding libraries are mainly used to store hardware-related data, including relevant data in the collection box 1 model, such as the size data corresponding to each model of the collection box 1, and the distance parameters between each placement hole 11 and the reference point, such as Figure 3 The collection boxes 1 of various types shown have corresponding lengths W and widths H, and take a corner as a reference point, and the horizontal distance l1 and vertical distance l2 between each placement hole 11 and the reference point O. The storage library is mainly used to store the comparison information of samples and patients.

[0021] Sampling steps: mark one side of the collection box 1, then continuously obtain overhead photos of the collection box 1, the interval between two photos should be controlled to be smaller than the interval of personnel operation, and use image analysis method to obtain the collection box 1 mark, the center coordinates of all placement holes 11 and their corresponding colors in each photo; When the sample tube 2 is placed in the collection box 1 after sampling, the color corresponding to the center coordinate of a single placement hole 11 will change from the color corresponding to the center coordinate of the corresponding placement hole 11 in the previous photo. For example, if the sample tube 2 is placed in the placement hole 11 No. 1, the color of the center coordinate of the placement hole 11 No. 1 will change from black to white for the sample tube 2 in the previous and next photos, while the color of the center coordinate of the other placement holes 11 will not change, so it can be determined which placement hole 11 the sample tube 2 is placed in. After determining the placement hole 11 in which the sample tube 2 is placed, the patient information, the collection box 1 mark, and the placement hole 11 information of the sample tube 2 can be packaged and stored in the storage library. For example, the sample tube 2 corresponding to the patient numbered 201 is in the placement hole 11 of the No. 5 box.

[0022] Detection steps: continuously obtain overhead photos of the collection box 1, the interval between two photos should be controlled to be smaller than the interval of human operation, and use image analysis method to obtain the collection box 1 mark, the center coordinates of all placement holes 11 and their corresponding colors in each photo; Similar to the above, when the sample tube 2 is taken out from the collecting box 1, the color corresponding to the center coordinate of a single placement hole 11 will change, and the corresponding patient information will be found from the storage repository based on the collection box 1 mark and the placement hole 11 information. For example, if the sample tube 2 is taken out from the placement hole 11 of box No. 5, it can correspond to the patient numbered 201.

[0023] The method uses image processing technology to intelligently detect and track the access of samples during sampling and detection, thereby eliminating the inconvenience of continuous operation by personnel in traditional tracking methods, and personnel do not need to deliberately place the position and angle of the collection box 1 during operation, greatly improving the efficiency of personnel operation. The method can be used not only in the medical field, but also in any occasion where sampling is required, and can also be used to achieve fast and efficient sampling and detection operations.

[0024] Of course, due to possible interference and other factors, when determining the color corresponding to the center coordinates of each placement hole 11, the average value of the pixel point corresponding to the center coordinate and all the pixel points within a set range around it can be used, and this average value can be used as the color corresponding to the center coordinate of the placement hole 11, thereby further ensuring the accuracy of the judgment.

[0025] The image analysis method specifically includes the following steps: S10: Binarizing the photo, so that the photo is firstly converted into a black-and-white image with only grayscale, and then the pixel points with grayscale greater than a threshold are converted into white, and the pixel points with grayscale less than or equal to the threshold are converted into black, so as to obtain a processed image with only black and white colors; S20: Since the length W and width H of the collection box 1 model are different, the collection box 1 model can be determined according to the area of ​​the white pixel points in the processed image. For example, if the actual area corresponding to one pixel is 1 cm², and if there are 600 white pixel points in the image, then the top view area of ​​the corresponding collection box 1 is 600 cm², and then the collection box 1 with a length of 30 cm and a width of 20 cm can be determined. After the collection box 1 model is determined, the distance parameter corresponding to the collection box 1 can be found from the corresponding library; S30: obtaining the collection box 1 area in the processed image; S40: Find the coordinates of the reference point corresponding to the collection box 1; S50: According to the found reference point coordinates and distance parameters, the center coordinates of all placement holes 11 of the collecting box 1 are obtained. For example, the found reference point 0 coordinates are (500,500), and the horizontal distance and vertical distance between placement hole 11 and reference point O are 6 cm and 6 cm, respectively. If the length and width of a pixel correspond to the actual 1 cm×1 cm, then the coordinates of placement hole 11 No. 1 are (506,506).

[0026] The collecting box 1 is preferably designed to be white, and at least the top of the sample tube 2 is white; when obtaining a top-down photograph of the collecting box 1, the collecting box 1 is placed on a platform with at least the top being black; through this color setting, the collecting box 1 and the sample tube 2 are better distinguished from the background; the sample tube 2 may also use other colors when necessary, but the color brightness needs to be made as high as possible so that the value is larger and closer to white when converted to grayscale, which is easy to distinguish.

[0027] The image analysis method can be implemented using an existing feature recognition algorithm. However, the traditional feature recognition algorithm usually requires complex calculations of all pixels in the image to identify the box features, which requires a large amount of calculation. For scenes where images need to be updated frequently in this method, the processor is heavily loaded. Therefore, this method proposes a better image analysis method for calculation. The specific steps of the image analysis method step S30 are: S31: Assume that the pixel point at the xth row and yth column of the processed image is (x, y); S32: The pixel with white color and the smallest x value is recorded as A(x A ,y A ) point; if there are multiple white pixels with the smallest x value, the pixel with the smallest y value is recorded as A(x A ,y A ) points, such as Figure 4 As shown; S33: Establish judgment point B(x B ,y B ) point and C(x C ,y C ) point; let x B =x C =x A ,y B =y C =y A ; S34: In the xth B+1 In the column, y B As the starting point, judge the color of the pixels upwards, stop when you first encounter a black pixel, and then judge the point B (x B ,y B ) point is updated to the white pixel point with the largest y value found at this time, and returns to S34 until no white pixel point that meets the requirements appears. The search logic is as follows: Figure 5 As shown, the shaded part in the figure represents black pixels, which can make point B start from point A and continue to climb along the edge, and finally make point B stop at a corner of the collection box 1; S35: In the xth C+1 In the column, y C As the starting point, judge the color of the pixel points downwards, stop when you first encounter a black pixel point, and then change the judgment point C(x C ,y C ) point is updated to the white pixel point with the largest y value found at this time, and returns to S35 until no white pixel point that meets the requirements appears. The search logic is as follows: Figure 5 As shown, point C can be made to start from point A and slide down along the edge continuously, and finally point C can be made to stop at another corner of the collection box 1; S36: Calculate the lengths of line segment AB and line segment AC, and compare them with the size data of the collecting box 1, so as to determine the length and width direction of the collecting box 1 in the processed image, and then obtain the collecting box 1 area in the processed image.

[0028] In step S36 of the image analysis method, it is determined whether the lengths of the line segments AB and AC are equal to the length and width of the collection box 1. At this time, the line segments AB and AC in the figure need to be converted from the lengths on the figure to the actual lengths before the determination can be made. For example, if the line segment AB is calculated to be 50 pixels long, the corresponding actual length is 50 cm. Of course, in most cases, the calculated length of the line segment will not be exactly the same as the length and width of the collection box 1. Therefore, an error range will be artificially set. As long as the difference between the actual length of the line segment and the length and width of the collection box 1 is within the error range, it is considered that the length of the line segment is equal to the length and width of the collection box 1. If the two line segments can correspond to the length and width of the collection box 1 respectively, the two line segments are recorded as the length and width of the collection box 1 respectively; If one line segment can correspond to the length or width of the collection box 1, and the other line segment is larger than the length of the collection box 1, then the following may occur: Figure 6-7 In the special case (the collection boxes 1 are too close to the ground and the boundaries cannot be clearly distinguished), only the length of one line segment can be determined, but it is enough to determine the area of ​​the collection box 1. At this time, the corresponding line segment can be recorded as the length or width of the collection box 1, and then the other data can be supplemented according to the size data of the collection box 1 in the corresponding library; If any line segment is smaller than the width of collection box 1, it means that there is a high probability that impurities and other factors appear on the platform, resulting in noise in the processed image. Usually, the area occupied by the noise will be much smaller than collection box 1, and the lengths of the two line segments will be much smaller than the width of collection box 1. At this time, all pixels on the two line segments can be updated to black, the noise can be removed, and then return to S32 for recalculation.

[0029] It can be seen that this image analysis method does not need to traverse all the pixels in the processed image, and the overall calculation method is simpler, so the processing speed is faster and the burden on the processor is smaller, and it can effectively adapt to the occasions of high-frequency refresh of photos required by this method.

[0030] When only one collecting box 1 is placed on the placing table 3, the image will be as follows: Figure 4 As shown, it is relatively easy to make a judgment at this time; however, in order to improve efficiency, the method further sets the following steps so that personnel can operate multiple collection boxes 1 at the same time: In the image analysis method step S20, the combination of the collection boxes 1 can be found according to the area of ​​the white pixels in the processed image. For example, if there are 1200 white pixels in the image, then the top view area of ​​the corresponding collection box 1 is 1200cm², which corresponds to two collection boxes 1 of 30cm long and 20cm wide. Or, if there are 1100 white pixels in the image, then the top view area of ​​the corresponding collection box 1 is 1100cm², which corresponds to one collection box 1 of 30cm long and 20cm wide and one collection box 1 of 25cm long and 20cm wide. After determining the combination of the collection boxes 1, the number N of the collection boxes 1 can be obtained; In the image analysis method step S30, a cycle value T is set to 0 in step S31, and further includes: S37: Add 1 to the loop value T, then remove all pixel coordinates in the determined collection box 1 area, and then return to S32. The removed pixel coordinates will no longer participate in subsequent calculations. This method is used to find the collection box 1 area one by one.

[0031] It is preferred to mark the collection box 1 with a barcode. The generation and recognition of a barcode is faster and more convenient than a QR code or a text mark, and can assist in finding the coordinates of the reference point corresponding to the collection box 1. The specific assistance method is as follows: The specific steps of the image analysis method step S40 are: S41: according to the length or width of the side of the collecting box 1 where the barcode is located, the two lengths or widths of the collecting box 1 area in the processed image are offset by a distance of L into the collecting box 1 area to form two offset lines, and only one of the length or width is selected. For example, if the barcode is on the width side of the collecting box 1, then the two width sides of the collecting box 1 area are offset to obtain two offset lines, and the offset lines must be able to pass through the barcode; S42: On each offset line, a change value G is first set to 0, and the colors of all two adjacent pixels on the same offset line are compared, and the change value is increased by 1 each time the colors are different; after the colors of the pixels on the two offset lines are compared, two change values ​​G1 and G2 can be obtained respectively; S43: Compare the sizes of G1 and G2. The larger the value, the more black and white intersections there are on this offset line, and the greater the possibility that it passes through the barcode. At this time, the side corresponding to the larger numerical change value can be used as the reference side; since the collection box 1 is usually set symmetrically, any endpoint on the reference side can be used as the reference point O.

[0032] In order to avoid the situation where the collection box 1 is knocked over by human error, resulting in the sample tube 2 being unable to correspond to the various placement holes 11 of each collection box 1, it is preferred to affix a verification mark to the side of the sample tube 2 before the sample tube 2 is placed in the collection box 1 after sampling, and the verification mark and patient information, collection box 1 mark and placement hole 11 information are stored in the storage repository together. In this way, the sample tube 2 can also determine its corresponding collection box 1 mark and placement hole 11 information through the verification mark, so that it can be restored.

[0033] Before the detection step, you can also take out any sample tube 2 in the collection box 1 and read its side verification mark to confirm whether the collection box 1 mark found in the corresponding storage repository is the same as the mark on the collection box 1 to ensure the correspondence of the data. For example, if a sample tube 2 is found in the storage repository to belong to collection box 1 No. 1, but it is actually taken out from collection box 1 No. 2, then there may be a problem of mixing up collection boxes 1 at this time, and this method cannot be used for tracking, but only the verification mark of sample tube 2 can be used; only after confirming that they are the same can the sample tube 2 be put back into the original position of the collection box 1, and then this method can be used to operate.

[0034] The present invention also relates to an easy-to-operate oral sample extraction full-process tracking and identification system, which is used to implement the above-mentioned easy-to-operate oral sample extraction full-process tracking and identification method, such as Figure 1~2 As shown, including: The collection box 1 is provided with a plurality of placement holes 11 distributed in an array, and the placement holes 11 vertically penetrate the collection box 1; a mark is provided on the top side of the collection box 1; The sample tube 2 is placed in the placement hole 11; A placement table 3, used for placing the collection box 1; the color of the top surface of the placement table 3 is different from the color of the collection box 1 and the sample tube 2; A camera 4 is fixedly arranged above the placing table 3 and is used for taking pictures; The processor is used to process and calculate the taken photos.

[0035] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An easy-to-operate oral sample extraction full-process tracking and identification method, characterized in that the steps include: Initialization setting: establish corresponding library and storage library, in which the corresponding library stores the size data of each type of collection box and the distance parameters between each placement hole and the reference point; Sampling steps: mark one side of the collection box, then continuously obtain overhead photos of the collection box, and use image analysis to obtain the collection box mark, the center coordinates of all placement holes and their corresponding colors in each photo; When the sample tube is put into the collection box after sampling, the color corresponding to the center coordinate of a single placement hole will change, and the patient information, collection box mark and placement hole information of this sample tube will be packaged and stored in the storage library; Detection steps: continuously obtain overhead photos of the collection box, and use image analysis to obtain the collection box mark, the center coordinates of all placement holes and their corresponding colors in each photo; When the sample tube is taken out of the collection box, the color corresponding to the center coordinate of a single placement hole will change, and the corresponding patient information will be found from the storage library according to the collection box mark and the placement hole information; The image analysis method specifically includes the following steps: S10: binarizing the photo to obtain a processed image; S20: judging the model of the collection box according to the area of ​​the white pixel points in the processed image, and finding the distance parameter corresponding to the collection box from the corresponding library; S30: obtaining a collection box area in the processed image; S40: Find the coordinates of the reference point corresponding to the collection box; S50: According to the found reference point coordinates and distance parameters, the center coordinates of all placement holes of the collection box are obtained.

2. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 1 is characterized in that: The collection box is white and at least the top of the sample tube is white; when taking a top-down photo of the collection box, place the collection box on a platform that is at least black on the top.

3. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 1 is characterized in that: The specific steps of the image analysis method step S30 are: S31: Assume that the pixel point at the xth row and yth column of the processed image is (x, y); S32: The pixel with white color and the smallest x value is recorded as A(x A ,y A ) point; if there are multiple white pixels with the smallest x value, the pixel with the smallest y value is recorded as A(x A ,y A )point; S33: Establish judgment point B(x B ,y B ) point and C(x C ,y C ) point; let x B =x C =x A ,y B =y C =y A ; S34: In the xth B+1 In the column, y B As the starting point, judge the color of the pixels upwards, stop when you first encounter a black pixel, and then judge the point B (x B ,y B ) point is updated to the white pixel point with the largest y value found at this time, and returns to S34 until no white pixel point that meets the requirements appears; S35: In the xth C+1 In the column, y C As the starting point, judge the color of the pixel points downwards, stop when you first encounter a black pixel point, and then change the judgment point C(x C ,y C ) point is updated to the white pixel point with the largest y value found at this time, and returns to S35 until no white pixel point that meets the requirements appears; S36: Calculate the lengths of line segment AB and line segment AC, and compare them with the size data of the collection box, so as to determine the length and width direction of the collection box in the processed image, and then obtain the collection box area in the processed image.

4. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 3 is characterized in that: In the image analysis method step S36, it is determined whether the lengths of line segment AB and line segment AC are equal to the length and width of the collection box; If the two line segments can correspond to the length and width of the collection box respectively, then the two line segments are recorded as the length and width of the collection box respectively; If a line segment can correspond to the length or width of the collection box, and the other line segment is larger than the length of the collection box, the line segment that can correspond is recorded as the length or width of the collection box; If any of the line segments is smaller than the width of the collection box, all pixels on the two line segments are updated to black, and then the process returns to S32.

5. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 3 is characterized in that: In the image analysis method step S20, the number of collection boxes N is also determined based on the area of ​​white pixels in the processed image; In the image analysis method step S30, a cycle value T is set to 0 in step S31, and further includes: S37: Add 1 to the loop value T, then remove all pixel coordinates in the determined collection box area, and then return to S32. The removed pixel coordinates will no longer participate in subsequent calculations.

6. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 1 is characterized in that: The collection boxes are marked with bar codes.

7. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 6 is characterized in that: The specific steps of the image analysis method step S40 are: S41: according to the length or width of the side of the collection box where the barcode is located, offset the two lengths or widths of the collection box area in the processing image into the collection box area by a distance L to form two offset lines; S42: On each offset line, a change value G is first set to 0, and the colors of all two adjacent pixels on the same offset line are compared, and the change value is increased by 1 each time the colors are different; after the colors of the pixels on the two offset lines are compared, two change values ​​G1 and G2 can be obtained respectively; S43: Compare the sizes of G1 and G2, and use an endpoint of the side corresponding to the larger change value as the reference point.

8. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 1 is characterized in that: After sampling, before the sample tube is placed in the collection box, a verification mark is attached to the side of the sample tube, and the verification mark is stored in the storage repository together with the patient information, the collection box mark and the placement hole information.

9. The easy-to-operate oral sample extraction full-process tracking and identification method according to claim 8, characterized in that: Before the detection step, take out any sample tube in the collection box and read its side verification mark to confirm whether the collection box mark found in its corresponding storage repository is the same as the mark on the collection box. After confirming that they are the same, put the sample tube back to its original position in the collection box.

10. An easy-to-operate oral sample extraction full-process tracking and identification system, characterized in that: The easy-to-operate oral sample extraction full-process tracking and identification method as claimed in any one of claims 1 to 9 comprises: The collection box is provided with a plurality of placement holes distributed in an array, and the placement holes vertically penetrate the collection box; a mark is provided on the top side of the collection box; A sample tube is placed in the placement hole; A placement table, used for placing the collection box; the color of the top surface of the placement table is different from the color of the collection box and the sample tube; A camera, fixedly arranged above the placement table, for taking photos; The processor is used to process and calculate the taken photos.

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