WO2022067914A1 - Procédé et appareil de vérification de médicament, terminal électronique et support de stockage - Google Patents

Procédé et appareil de vérification de médicament, terminal électronique et support de stockage Download PDF

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Publication number
WO2022067914A1
WO2022067914A1 PCT/CN2020/123274 CN2020123274W WO2022067914A1 WO 2022067914 A1 WO2022067914 A1 WO 2022067914A1 CN 2020123274 W CN2020123274 W CN 2020123274W WO 2022067914 A1 WO2022067914 A1 WO 2022067914A1
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WO
WIPO (PCT)
Prior art keywords
picture
medicine
template
medicine box
drug
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PCT/CN2020/123274
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English (en)
Chinese (zh)
Inventor
徐立
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苏州艾隆科技股份有限公司
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Publication of WO2022067914A1 publication Critical patent/WO2022067914A1/fr

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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F17/00—Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/0092—Coin-freed apparatus for hiring articles; Coin-freed facilities or services for assembling and dispensing of pharmaceutical articles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24147—Distances to closest patterns, e.g. nearest neighbour classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
    • G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
    • G06V10/757—Matching configurations of points or features

Definitions

  • the invention relates to the technical field of drug distribution, in particular to a drug detection method, device, electronic terminal and storage medium.
  • a medicine dispensing system In a pharmacy of a hospital, a medicine dispensing system is usually set up, and the medicine dispensing system is usually provided with a medicine outlet, and the medicine dispensing system sends out a preset type of medicine from the medicine outlet.
  • the medicine system may be wrong, that is, the medicine may not correspond to the preset type.
  • the error is usually corrected by manual inspection. It is understandable that this method is not only labor-intensive, but also wrong. is also more likely.
  • the purpose of the present invention is to provide a drug detection method, device, electronic terminal and storage medium.
  • an embodiment of the present invention provides a drug detection method for a drug dispensing system, including the following steps: acquiring a target drug type and corresponding template pictures, wherein each template picture contains An outer side of the medicine box containing the medicine corresponding to the target medicine type; based on the target medicine type, controlling the medicine dispensing system to send out the target medicine, and taking a picture of the medicine box of the medicine box containing the target medicine; When it is determined that any template picture matches the picture of the medicine box, the medicine dispensing system delivers the correct target medicine.
  • the "determining that any template picture matches the picture of the medicine box" specifically includes: continuously selecting an unprocessed template picture from the several template pictures, and judging the unprocessed template picture Whether it matches the picture of the medicine box, until the unprocessed template picture matches the picture of the medicine box or the several template pictures have been processed.
  • the "judging whether the unprocessed template picture matches the medicine box picture” specifically includes: respectively acquiring a plurality of first feature points of the unprocessed template picture, a plurality of first feature points corresponding to the medicine box picture, A number of second feature points are obtained, from a plurality of first and second feature points, the nearest matching feature points in the unprocessed template picture and the medicine box picture are obtained; based on the several matching feature points, the medicine box is obtained The transformation matrix from the picture to the template picture, using the transformation matrix to process the medicine box picture, and then performing the projection transformation process to obtain the picture to be compared; it is judged whether the picture to be compared matches the unprocessed template picture.
  • the "judging whether the picture to be compared matches the unprocessed template picture" specifically includes: selecting several first points in the image area corresponding to the outer side of the unprocessed template picture; When there is any first point in the picture to be compared that does not correspond to the second point, the picture to be compared does not match the unprocessed template picture.
  • the picture area corresponding to the outer side is rectangular; in the picture to be compared, several first points include: four boundaries respectively located on the outer side
  • the "judging whether the picture to be compared matches the unprocessed template picture" also includes: selecting a number of second points corresponding to a number of first points from the picture to be compared, when a number of second points When the second rectangle is formed and the absolute value of the difference between the areas of the first rectangle formed by several first points and the second rectangle is less than or equal to the preset difference, it is determined that the to-be-compared picture matches the unprocessed template picture.
  • the "respectively obtaining multiple first feature points of the unprocessed template picture and multiple second feature points corresponding to the medicine box picture” specifically includes: based on the SURF algorithm, obtaining respectively A plurality of first feature points of the unprocessed template picture, and a plurality of second feature points corresponding to the picture of the medicine box.
  • the "obtaining several nearest matching feature points in the unprocessed template picture and the medicine box picture from a plurality of first and second feature points" specifically includes: based on the KNN algorithm , and from the first and second feature points, obtain the nearest matching feature points in the unprocessed template picture and the medicine box picture.
  • a drug detection device for a drug dispensing system including the following modules: a template picture acquisition module, used to acquire a target drug type and a number of corresponding template pictures, wherein each template picture contains There is an outer side of the medicine box with the medicine corresponding to the target medicine type; the picture of the medicine box is obtained by a wooden block, which is used to control the medicine dispensing system to send out the target medicine based on the target medicine type, and take pictures of the medicine box containing the target medicine.
  • the medicine box picture of the medicine box; the processing module is used for sending out the correct target medicine by the medicine dispensing system when it is determined that any template picture matches the medicine box picture.
  • An embodiment of the present invention further provides a storage medium storing program instructions, and when the program instructions are executed, the above-mentioned drug detection method is implemented.
  • Embodiments of the present invention further provide an electronic terminal, including a processor and a memory, wherein the memory stores program instructions, and the processor executes the program instructions to implement the embodiments of the present invention.
  • a drug detection method is also provided.
  • the embodiment of the present invention provides a drug detection method, device, electronic terminal and storage medium, and the drug detection method includes the following steps: obtaining a target drug type and corresponding several Template pictures, wherein each template picture contains an outer side of the medicine box of the medicine corresponding to the target medicine type; based on the target medicine type, the medicine dispensing system is controlled to send out the target medicine, and the pictures containing The picture of the medicine box of the medicine box of the target medicine; when it is determined that any template picture matches the picture of the medicine box, the medicine dispensing system sends out the correct target medicine. This enables automatic identification of medication dispensing errors.
  • FIG. 1 is a schematic structural diagram of a medicine dispensing system in an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a drug detection method in an embodiment of the present invention.
  • spatially relative positions are used herein for ease of illustration to describe one element or feature relative to another as shown in the figures The relationship of a unit or feature.
  • the term spatially relative position may be intended to encompass different orientations of the device in use or operation in addition to the orientation shown in the figures. For example, if the device in the figures is turned over, elements described as “below” or “beneath” other elements or features would then be oriented “above” the other elements or features. Thus, the exemplary term “below” can encompass both an orientation of above and below.
  • the device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
  • Embodiment 1 of the present invention provides a drug detection method for a drug dispensing system.
  • the specific structure of the drug dispensing system may be shown in FIG. 1 , including: a drug storage device, a conveyor belt device, and a drug dispensing device.
  • the medicine device is provided with a medicine outlet and can store medicines.
  • the medicine storage device sends out medicines from the medicine outlet, and then the medicines drop onto the conveyor belt device, which can deliver the medicines to the delivery device.
  • the drug dispenser can then dispense the drug.
  • the camera can take pictures of the medicines delivered from the medicine outlet. For example, when the medicines are sent out of the medicine outlet, they will fall onto the transmission belt device. At this time, the camera can take pictures.
  • the camera is provided with a light bulb, which can be turned on when the environment is relatively dim; the medicine is a boxed medicine; The camera, and the lens in the camera is facing the conveyor belt device, so as to reduce the probability of crooked photos.
  • Step 201 Obtain the target drug type and several corresponding template pictures, wherein each template picture contains an outer side of the medicine box of the drug corresponding to the target drug type; They are all packaged in a medicine box, which is usually a square box, with six outer sides, and each outer side is printed with information such as patterns or words, and each template picture can be a photo obtained by taking one outer side. ;
  • the medicine box may have multiple styles, so each side of the medicine box of all styles can be photographed, and then all the obtained photos can be used as the corresponding template of the medicine picture.
  • Step 202 Based on the type of the target medicine, control the medicine dispensing system to send out the target medicine, and take a picture of the medicine box containing the target medicine; here, the medicine dispensing system will obtain the medicine box from its internal storage space The medicine corresponding to the target medicine type is sent out. At this time, the camera can be controlled to take a picture of the medicine box corresponding to the target medicine. Optionally, when the target medicine is dropped from the medicine outlet, it will fall on the conveyor belt device. At this time, after the medicine box is stationary, the camera can be controlled to take a picture of the outer side of the medicine box of the target medicine.
  • Step 203 When it is determined that any template picture matches the picture of the medicine box, the medicine dispensing system sends out the correct target medicine.
  • the medicine dispensing system delivers the correct target medicine.
  • the outer side of the medicine box is usually a rectangle.
  • this area can be a rectangular area. If it is not a rectangular area, the image can be horizontally corrected.
  • the picture of the medicine box may also be crooked. Therefore, the picture of the medicine box may contain several outer sides. You can select the clearest outer side in the picture of the medicine box, and then perform horizontal correction processing on the picture of the medicine box.
  • the reason for the distortion of the picture of the medicine box may be: (1) the lens is not correct when shooting, and the image taken has a plane inclination angle; (2) the horizontal plane of the lens when shooting It is not parallel to the upper side of the medicine box, resulting in perspective distortion of the captured image.
  • the step of performing horizontal correction processing on the image may specifically include: (1)
  • the outer side of the medicine box is usually a rectangle, so the rectangle has two sides parallel to each other. Therefore, the two sides can be detected by using the Hough change. Then, the plane inclination angle of the whole picture of the medicine box can be calculated, and then the matrix operation is performed according to the coordinate system, and the geometric change of all pixels is performed to realize the horizontal correction of the picture of the medicine box.
  • Perspective deformation can also be used, that is, through the coordinate calculation and transformation of the opposite sides of the outer side of the medicine box, after the horizontal tilt correction is completed, the coordinate calculation and transformation are performed on the two sides, and the perspective deformation correction and
  • the scaling deformation correction can specifically be: grayscale processing of the medicine box image ⁇ noise removal processing ⁇ binarization processing ⁇ corner point coordinateization ⁇ horizontal plane inclination correction ⁇ perspective deformation correction ⁇ scaling deformation correction ⁇ obtaining a corrected image.
  • the "determining that any template picture matches the medicine box picture” specifically includes: continuously selecting an unprocessed template picture from the several template pictures, and judging whether the unprocessed template picture and the medicine box picture are not Match until the unprocessed template picture matches the medicine box picture or the several template pictures have been processed.
  • the template pictures can be processed one by one. If there is a template picture that matches the picture of the medicine box, the medicine dispensing system will send the correct target medicine; , after all the template pictures are processed, if a template picture that matches the picture of the medicine box is still not found, it means that the medicine dispensing system sends the wrong target medicine.
  • the "judging whether the unprocessed template picture matches the medicine box picture” specifically includes:
  • the first and second feature points are the image features of the unprocessed template picture and the medicine box picture, respectively.
  • the shooting angles and orientations of the template picture and the medicine box picture may be different. Therefore, SURF (Speed Up Robust Feature) algorithm performs corresponding processing, so that graphics transformation and projection transformation can be performed on the picture of the medicine box, and the picture to be compared can be obtained. It can be understood that the picture to be compared and the unprocessed template picture are taken. The angle and orientation are the same, after that, the feature descriptors of the two images can be obtained, and then the features of the two images are matched according to the similarity of the descriptors.
  • SURF Speed Up Robust Feature
  • the "judging whether the picture to be compared matches the unprocessed template picture" specifically includes: selecting several first points in the image area corresponding to the outer side from the unprocessed template picture; When one point does not correspond to the second point in the image to be compared, the image to be compared does not match the unprocessed template image.
  • the picture to be compared if there is a match between the picture to be compared and the unprocessed template picture, then in the unprocessed template picture, all points in the image area corresponding to the outer side should have corresponding points in the picture to be compared
  • the picture to be compared does not match the unprocessed template picture.
  • the picture area corresponding to the outer side is rectangular; in the picture to be compared, several first points include: a plurality of points respectively located on the four boundaries of the outer side ; Described "judging whether the picture to be compared is matched with the unprocessed template picture" also includes: selecting some second points corresponding to some first points from the picture to be compared, when some second points form a second rectangle, And when the absolute value of the difference between the areas of the first rectangle and the second rectangle formed by several first points is less than or equal to the preset difference, it is determined that the image to be compared matches the unprocessed template image.
  • first points include points located on the four boundaries of the outer side surface
  • second points should also be able to form a rectangle
  • the area of the rectangle should be similar, that is, there is some error, but the absolute value of the difference is small (that is, the absolute value of the difference ⁇ the preset difference, and the preset difference ⁇ 0) is equal.
  • the "absolute value of the difference between the area of the first rectangle and the second rectangle formed by several first points ⁇ preset difference" may include:
  • the "respectively obtaining multiple first feature points of the unprocessed template picture and multiple second feature points corresponding to the medicine box picture” specifically includes: based on the SURF (Speed Up Robust Feature) algorithm, respectively A plurality of first feature points of the unprocessed template picture and a plurality of second feature points corresponding to the picture of the medicine box are acquired.
  • the SURF algorithm can be regarded as an accelerated version of the Sift algorithm. It has the following characteristics: use integral image to complete image convolution (correlation) operation, use Hessian matrix to detect eigenvalues, use distribution-based descriptors (local information); the steps are usually: feature extraction, feature matching and radiation transformation.
  • the "obtaining the nearest matching feature points in the unprocessed template picture and the medicine box picture from a plurality of first and second feature points” specifically includes: based on KNN (K-Nearest Neighbor)
  • KNN K-Nearest Neighbor
  • the algorithm obtains the closest matching feature points in the unprocessed template picture and the medicine box picture from the first and second feature points.
  • the basic steps of the KNN algorithm can include: 1. Prepare the data and preprocess the data; 2. Calculate the distance from the test sample point (that is, the point to be classified) to each other sample point; 3. Sort each distance, Then select the K points with the smallest distance; 4. Compare the categories to which the K points belong, and classify the test sample points into the category with the highest proportion of the K points according to the principle that the minority obeys the majority.
  • the second embodiment of the present invention provides a drug detection device for a drug dispensing system, including the following modules:
  • a template picture acquisition module used for acquiring a target drug type and a number of corresponding template pictures, wherein each template picture contains an outer side of the medicine box of the drug corresponding to the target drug type;
  • the medicine box picture acquisition wooden block is used to control the medicine dispensing system to send out the target medicine based on the target medicine type, and take a medicine box picture of the medicine box containing the target medicine;
  • the processing module is configured to send the correct target medicine by the medicine dispensing system when it is determined that any template picture matches the medicine box picture.
  • the third embodiment of the present invention provides a storage medium storing program instructions, and when the program instructions are executed, the drug detection method described in the first embodiment is implemented.
  • the fourth embodiment of the present invention provides an electronic terminal, including a processor and a memory, wherein the memory stores program instructions, and the processor executes the program instructions to implement the drug detection method described in the first embodiment.

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  • Databases & Information Systems (AREA)
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  • Medical Informatics (AREA)
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Abstract

L'invention concerne un procédé et un appareil de vérification d'un médicament, un terminal électronique et un support de stockage. Le procédé de vérification d'un médicament comprend les étapes suivantes : l'obtention d'un type de médicament cible et d'une pluralité d'images de modèle correspondantes, chaque image de modèle comprenant une surface latérale externe d'une boîte de médicament d'un médicament correspondant au type de médicament cible (201) ; la commande d'un système d'administration de médicament pour administrer un médicament cible sur la base du type de médicament cible et la photographie d'une image de boîte de médicament de la boîte à médicament contenant le médicament cible (202) ; et lors de la détermination qu'une image de modèle quelconque correspond à l'image de boîte de médicament, le système d'administration de médicament administre le médicament cible correct (203). Par conséquent, une erreur d'administration de médicament peut être automatiquement identifiée.
PCT/CN2020/123274 2020-09-30 2020-10-23 Procédé et appareil de vérification de médicament, terminal électronique et support de stockage WO2022067914A1 (fr)

Applications Claiming Priority (2)

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CN202011065130.5A CN112200976B (zh) 2020-09-30 2020-09-30 药品检测方法、装置、电子终端及存储介质
CN202011065130.5 2020-09-30

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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103158987A (zh) * 2011-12-13 2013-06-19 苏州艾隆科技有限公司 快速发药系统中药品识别及处理方法
CN103744886A (zh) * 2013-12-23 2014-04-23 西南科技大学 一种直接提取的k个最近邻点搜索方法
EP2902004A1 (fr) * 2012-09-27 2015-08-05 Fujifilm Corporation Dispositif et procédé d'inspection de médicament
CN106938755A (zh) * 2016-11-29 2017-07-11 上海无线电设备研究所 智能药房自动化上药出药系统及方法
CN108538356A (zh) * 2018-01-18 2018-09-14 深圳市瑞驰致远科技有限公司 药品自动核对系统及方法
CN110738216A (zh) * 2019-09-04 2020-01-31 南京理工大学 基于改进surf算法的药品识别方法
CN111243192A (zh) * 2020-03-20 2020-06-05 上海健麾信息技术股份有限公司 一种视觉复核装置
CN111428622A (zh) * 2020-03-20 2020-07-17 上海健麾信息技术股份有限公司 一种基于分割算法的图像定位方法及其应用

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5916032B2 (ja) * 2012-09-27 2016-05-11 富士フイルム株式会社 薬剤検査支援装置及び方法
CN107492091B (zh) * 2017-07-06 2020-09-04 东莞理工学院 基于机器视觉的标签外观检测方法及终端设备

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103158987A (zh) * 2011-12-13 2013-06-19 苏州艾隆科技有限公司 快速发药系统中药品识别及处理方法
EP2902004A1 (fr) * 2012-09-27 2015-08-05 Fujifilm Corporation Dispositif et procédé d'inspection de médicament
CN103744886A (zh) * 2013-12-23 2014-04-23 西南科技大学 一种直接提取的k个最近邻点搜索方法
CN106938755A (zh) * 2016-11-29 2017-07-11 上海无线电设备研究所 智能药房自动化上药出药系统及方法
CN108538356A (zh) * 2018-01-18 2018-09-14 深圳市瑞驰致远科技有限公司 药品自动核对系统及方法
CN110738216A (zh) * 2019-09-04 2020-01-31 南京理工大学 基于改进surf算法的药品识别方法
CN111243192A (zh) * 2020-03-20 2020-06-05 上海健麾信息技术股份有限公司 一种视觉复核装置
CN111428622A (zh) * 2020-03-20 2020-07-17 上海健麾信息技术股份有限公司 一种基于分割算法的图像定位方法及其应用

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