CN103543277B - A kind of blood group result recognizer based on gray analysis and category identification - Google Patents
A kind of blood group result recognizer based on gray analysis and category identification Download PDFInfo
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- 210000004369 blood Anatomy 0.000 title claims abstract description 76
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- 238000000034 method Methods 0.000 claims abstract description 44
- 210000005239 tubule Anatomy 0.000 claims abstract description 35
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- 239000003153 chemical reaction reagent Substances 0.000 claims description 56
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- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
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Abstract
The invention discloses a kind of blood group result recognizer based on gray analysis and category identification, it comprises the following steps：Greyscale transformation, smothing filtering, slant correction, the segmentation of microtrabeculae tubule, threshold process, gray analysis, category identification, contrasting detection result, the method that the present invention is combined with category identification using gray analysis is to Blood grouping result progress automatic identification, improve the efficiency of Blood grouping result identification, with fast and accurately advantage, operated simultaneously by jitter elimination, slant correction, the segmentation of microtrabeculae tubule, category identification etc., improve the validity of result identification.
Description
Technical Field
The invention relates to the field of blood type detection result identification, in particular to a blood type result identification algorithm based on gray level analysis and type identification.
Background
Blood type detection techniques can be classified into slide methods, test tube methods, microplate methods, blood type reagent card methods, and the like. The blood type reagent card method is the most advanced blood type detection technology recommended by the international health organization at present. The slide method and the test tube method are early blood type analysis technologies and have the advantage of simple detection conditions, but the sample adding process is often realized manually, the judgment of the reaction result is usually judged by human eyes, the automation degree is not high, the interference of human factors is serious, and the judgment of the result is strongly influenced by the subjective consciousness of people. The microplate method is a blood type analysis technique developed later, but the reacted micro platelets are inconvenient to store when the microplate method is used for blood type analysis, and the traceability of the blood transfusion requirements is not met.
The blood type reagent card consists of a microcolumn tubule and a nameplate. The microcolumn tubule is a reaction container during blood type detection, during detection, erythrocyte, serum or erythrocyte reagent is added on the upper part of the microcolumn tubule, and the detection result is judged by analyzing the distribution condition of the erythrocyte in the microcolumn tubule after reaction. The nameplate is the type and information identification of the blood type reagent card, and the name of the blood type reagent card, the one-dimensional bar code, the information of each tube of the microcolumn tubule and the like are printed on the nameplate.
The application of the domestic blood group reagent card method mainly stays in the manual stage, namely the detection result of the reagent card is read by human eyes, the detection automation degree is low, and the human misjudgment of the detection result is very likely to occur by adopting the detection result of the reagent card read by human eyes
The application of foreign blood group reagent card method has entered into the automation stage, namely, the instrument is used to interpret the detection result of the reagent card, and the bar code gun is used to scan the type of the blood group reagent card. However, when the foreign instrument interprets the detection result of the blood type reagent card, it is often default that the acquired image of the blood type reagent card is correct and clear, and the shaking condition and the inclination condition of the blood type reagent card are not eliminated and corrected; meanwhile, only the fixed area on the blood type reagent card is scanned during blood type image analysis, and the effective area (namely the microcolumn tubule) for identifying the blood type result is not intelligently segmented. Both of these problems may cause deviation of the analyzed target region from the effective region, thereby affecting the accuracy of detection result identification. Meanwhile, the type of the reagent card is identified by adopting an additional bar code gun, but the type identification cannot be carried out through the own color and character information of the nameplate, and the defects are that the complexity of an instrument and the operation steps of detection are increased.
Disclosure of Invention
The invention aims to overcome the defects of the existing blood type detection result identification method and provide a blood type result identification algorithm based on gray level analysis and type identification.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
a blood type result recognition algorithm based on gray level analysis and type recognition comprises the following steps:
1. a blood type result recognition algorithm based on gray level analysis and type recognition is characterized by comprising the following steps:
step 1) Gray level conversion
Carrying out gray scale transformation on 24-bit true color images of the blood type reagent card by adopting a weighted average method, and setting coordinates (A and B)) The brightness values of the respective components are respectively、、The gray value of the point after the gray conversion，
Wherein、、respectively weighting each color component to obtain a converted gray level image;
step 2) smoothing filtering
Noise filtering is carried out on the gray level image of the blood type reagent card by adopting a median filtering methodTo select a set of gray values in a local region,the operation is to find the median value of the sequence,to want to replace a designated point of the gray scale value:
a clearer gray level image is obtained;
step 3) jitter elimination
The gray image of the blood type reagent card is shaken and eliminated by adopting an expansion corrosion method, so that a clearer gray image is obtained;
step 4) Tilt correction
Obtaining the inclination angle of the blood type reagent card by adopting a slope calculation method, correcting the inclination state of the blood type reagent card by reversely rotating the corresponding angle, finding out a parallelogram area in four blank parallelogram areas in a nameplate of the blood type reagent card, and taking the upper left corner coordinate of the parallelogram area (the step (c) () And coordinates of lower left corner: () By the formula:=calculating the inclination angle of the image;
step 5) micro-column tubule segmentation
Adopting a template matching method, namely, through a correlation formula: segmenting an effective area for image identification in the blood type reagent card, namely a microcolumn tubule;
step 6) threshold processing
Threshold processing is carried out on the divided microcolumn tubule images by a binarization method, the microcolumn tubule images are converted into binarization images with only black and white colors from gray level images, and a certain threshold value is setThe pixel value of each pixel of the original gray imageAnd a threshold valueBy comparison, is greater thanIs 255, otherwise is 0, and the pixel value after the threshold processing is set asNamely:
step 7) Gray level analysis
Dividing the lower end of each micro-column tubule into an upper small area, a middle small area and a lower small area by adopting a pixel summation method, respectively calculating the sum of pixels of the upper small area, the middle small area and the lower small area, namely representing the distribution condition of red blood cells at the lower end of the micro-column tubule by the distribution condition of the pixels;
step 8) species identification
The method combining color recognition and character recognition is adopted, and the difference of the types of the blood type reagent card is recognized by analyzing the character difference in different color areas in the nameplate of the blood type reagent card.
Step 9) comparing the detection results
And according to the distribution condition of the red blood cells in the microcolumn tubules, simultaneously combining the types of the current blood type reagent cards to obtain the blood type detection result of the blood type reagent card.
The invention has the beneficial effects that:
by adopting the technical scheme of the invention, the accuracy of blood type detection result identification is improved by inclination correction and jitter elimination, the accuracy of target area identification is improved by adopting the template matching and segmenting the microcolumn tubules, and the complexity of the instrument and the operation steps of detection are reduced by adopting a reagent card type identification method combining color identification and character identification.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a diagram illustrating a process of performing tilt correction according to the present invention;
FIG. 3 shows three matching templates for micro-column tubule segmentation according to the present invention;
FIG. 4 is a binarized image of a micropillar tubule grayscale image of the present invention after thresholding;
FIG. 5 is a schematic illustration of a nameplate of seven blood type reagent cards of the present invention;
FIG. 6 is a diagram illustrating the characters extracted from the nameplate during the class identification according to the present invention;
fig. 7 shows an interception method of 11 feature points used in character recognition in the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Referring to fig. 1, a blood type result identification algorithm based on gray level analysis and type identification includes the following steps:
step 1) Gray level conversion
Carrying out gray scale transformation on 24-bit true color images of the blood type reagent card by adopting a weighted average method, and setting coordinates (A and B)) The brightness values of the respective components are respectively、、The gray value of the point after the gray conversion，
Wherein、、respectively weighting each color component to obtain converted gray image, and taking the image=0.299、=0.587、Carrying out gray scale conversion on a 24-bit true color image of the blood type reagent card by =0.114 minute to obtain a converted gray scale image;
step 2) smoothing filtering
Noise filtering is carried out on the gray level image of the blood type reagent card by adopting a median filtering methodTo select a set of gray values in a local region,the operation is to find the median value of the sequence,to want to replace a designated point of the gray scale value:
obtaining a clearer gray image, wherein the filtering unit is taken as a square area of 3 x 3 for filtering in the figure;
step 3) jitter elimination
The blood type reagent card gray level image is subjected to jitter elimination by adopting an expansion corrosion method, so that a clear parallelogram area in a nameplate is obtained, and a more clear gray level image after correction is obtained;
step 4) Tilt correction
Referring to fig. 2, the inclination angle of the blood type reagent card is obtained by a slope calculation method, the inclination state is corrected by reversely rotating the corresponding angle, four blank parallelogram regions are arranged in the nameplate of the blood type reagent card, the parallelogram region is found, and the upper left corner coordinate of the parallelogram region is taken (a)) And coordinates of lower left corner: () By the formula:=calculating the inclination angle of the image;
step 5) micro-column tubule segmentation
Adopting a template matching method, namely, through a correlation formula: segmenting an effective area for image identification in the blood type reagent card, namely a microcolumn tubule, and the specific operation process is as follows: and simplifying the two-dimensional distribution of the image into a form of two-dimensional array storage data. Suppose that the pixel information of the template image is stored in an arrayWherein, the data in each row of the array sequentially correspond to the pixel values of each row of the template image. Similarly, assume that the pixel information of the original image is stored in an arrayIn (1). Wherein,，i.e. the size of the template image must be smaller than or equal to the size of the original image, first, the autocorrelation value of the template image is determinedThe calculation formula is as follows:
in the formula,is an array ofMiddle behaviorColumn asThe above pixel value is a binary image, so、Can only be 0 or 1, then, scanning the coordinates of the upper left corner in the original image from left to right and from top to bottom in sequence to be (）Of size ofI.e. local image areas of the same size as the template imageCalculating the autocorrelation value of the local regionAnd cross-correlation value with template image。
In the formula,is an array ofMiddle behaviorColumn asThe value of the pixel(s) in the scan, and thus the cross-correlation coefficient of the scanComprises the following steps:
then comparing the cross correlation coefficient obtained each timeTo find the maximum cross correlation coefficient corresponding toPre-scan coordinates: () That is, the coordinates of the upper left corner of the local image matching the template image, and the coordinates of the upper right corner of the local image region matching the template image in the original image are () The coordinate of the lower left corner is) The coordinate of the lower right corner is () Referring to fig. 3, the second of the three matching templates is used to perform template matching on the grayscale image, and the effective region of the microcolumn tubule is found for segmentation. Wherein, the size of the original gray image is 768 × 576, the size of the second matching template is 118 × 268, six microcolumn tubules in the blood type reagent card can be found by performing template matching operation once and are divided, and the time required by the matching operation is 3.167 s;
step 6) threshold processing
Threshold processing is carried out on the divided microcolumn tubule images by a binarization method, the microcolumn tubule images are converted into binarization images with only black and white colors from gray level images, and a certain threshold value is setThe pixel value of each pixel of the original gray imageAnd a threshold valueBy comparison, is greater thanIs heavyThe new value is 255, otherwise, the new value is 0, and the pixel value after threshold processing is set asNamely:
referring to fig. 4, taking the threshold value as 80, and performing binarization processing on the segmented microcolumn tubule image to obtain a binarized image with only black and white colors;
step 7) Gray level analysis
Dividing the lower end of each micro-column tubule into an upper small area, a middle small area and a lower small area by adopting a pixel summation method, respectively calculating the sum of pixels of the upper small area, the middle small area and the lower small area, namely representing the distribution condition of red blood cells at the lower end of the micro-column tubule by the distribution condition of the pixels;
step 8) species identification
The method of combining color identification and character identification is adopted, the difference of the types of the blood type reagent card is identified by analyzing the character difference in different color areas in the nameplate of the blood type reagent card, as shown in figure 5, seven nameplates of common blood type reagent cards have great difference of colors and characters, firstly, a gray level conversion method is adopted, and the nameplates are sequentially taken、、The nameplates of the blood type reagent cards are subjected to monochromatic treatment for 100, 010 and 001 to obtain the monochromatic distribution conditions of different kinds of nameplates, and then, as shown in figure 6, character areas are adoptedExtracting characters in different monochromatic areas, then intercepting 11 areas T1-T11 of a single character by adopting an 11-characteristic point method as shown in figure 7, calculating the sum Tsum of pixels in each area to form a pixel sum vector (T1 sum, T2sum, … and T11 sum), identifying different characters according to the difference of the pixel sum vector and further obtaining the type of the corresponding blood type reagent card;
step 9) comparing the detection results
And according to the distribution condition of the red blood cells in the microcolumn tubules, simultaneously combining the types of the current blood type reagent cards to obtain the blood type detection result of the blood type reagent card.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A blood type result identification method based on gray level analysis and type identification is characterized by comprising the following steps:
step 1) Gray level conversion
Carrying out gray scale transformation on 24-bit true color image of blood type reagent card by adopting weighted average method, and setting coordinatesThe brightness values of the respective components are respectively、、The gray value of the coordinate after gray conversion，
Wherein、、respectively weighting each color component to obtain a converted gray level image;
step 2) smoothing filtering
Noise filtering is carried out on the gray level image of the blood type reagent card by adopting a median filtering methodTo select a set of gray values in a local region,the operation is to find the median value of the sequence,to want to replace a designated point of the gray scale value:
a clearer gray level image is obtained;
step 3) jitter elimination
The gray image of the blood type reagent card is shaken and eliminated by adopting an expansion corrosion method, so that a clearer gray image is obtained;
step 4) Tilt correction
Obtaining the inclination angle of the blood type reagent card by adopting a slope calculation method, correcting the inclination state of the blood type reagent card by reversely rotating the corresponding angle, finding out a parallelogram area in four blank parallelogram areas in a nameplate of the blood type reagent card, and taking the coordinate of the upper left corner of the parallelogram areaAnd coordinates of lower left cornerBy the formula:calculating the inclination angle of the image;
step 5) micro-column tubule segmentation
Adopting a template matching method, namely, through a correlation formula:segmenting an effective area for image identification in the blood type reagent card, namely a microcolumn tubule;
step 6) threshold processing
Threshold processing is carried out on the divided microcolumn tubule images by a binarization method, the microcolumn tubule images are converted into binarization images with only black and white colors from gray level images, and a certain threshold value is setThe original gray scale mapPixel value of each pixelAnd a threshold valueBy comparison, is greater thanIs 255, otherwise is 0, and the pixel value after the threshold processing is set asNamely:
step 7) Gray level analysis
Dividing the lower end of each micro-column tubule into an upper small area, a middle small area and a lower small area by adopting a pixel summation method, respectively calculating the sum of pixels of the upper small area, the middle small area and the lower small area, namely representing the distribution condition of red blood cells at the lower end of the micro-column tubule by the distribution condition of the pixels;
step 8) species identification
Identifying the difference of the types of the blood type reagent card by analyzing the character difference in different color areas in the nameplate of the blood type reagent card by adopting a method combining color identification and character identification;
step 9) comparing the detection results
And according to the distribution condition of the red blood cells in the microcolumn tubules, simultaneously combining the types of the current blood type reagent cards to obtain the blood type detection result of the blood type reagent card.
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| CN105550507A (en) * | 2015-12-09 | 2016-05-04 | 上海斐讯数据通信技术有限公司 | Intelligent terminal for measuring blood type and measuring method |
| CN105678752A (en) * | 2015-12-30 | 2016-06-15 | 合肥天一生物技术研究所 | Blood type identification method through segmentation of microcolumn vasculum based on fixed parameters |
| CN106199014A (en) * | 2016-06-29 | 2016-12-07 | 中山生物工程有限公司 | A kind of blood group method of discrimination based on blood type card |
| CN106372596A (en) * | 2016-08-30 | 2017-02-01 | 孟玲 | Biological information collection device |
| CN107167616B (en) * | 2017-03-13 | 2019-06-07 | 中国科学院苏州生物医学工程技术研究所 | Blood type testing methods and device |
| CN107389957B (en) * | 2017-06-28 | 2018-10-16 | 苏州长光华医生物医学工程有限公司 | Micro-column gel card is aggregated testing result identifying system and blood type analytical instrument |
| CN107356774B (en) * | 2017-06-28 | 2018-10-16 | 苏州长光华医生物医学工程有限公司 | Micro-column gel card is aggregated testing result recognition methods |
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| CN109409395A (en) * | 2018-07-29 | 2019-03-01 | 国网上海市电力公司 | Using the method for template matching method identification target object region electrical symbol in power monitoring |
| CN109919054B (en) * | 2019-02-25 | 2023-04-07 | 电子科技大学 | Machine vision-based reagent card automatic classification detection method |
| CN110794151A (en) * | 2019-10-30 | 2020-02-14 | 中山生物工程有限公司 | Method, device, terminal, medium and equipment for detecting quality of blood type card |
| CN112485457B (en) * | 2020-11-18 | 2023-04-18 | 天津德祥生物技术股份有限公司 | Detection result identification method |
| CN112907665B (en) * | 2021-02-07 | 2022-06-10 | 吉林大学 | Micro-fluidic blood type detection card micro-cavity reaction tank precise positioning method based on RGB color space |
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Inventor after: Luo Gangyin Inventor after: Wang Bidou Inventor after: Chen Yueyan Inventor after: Zhang Yunping Inventor before: Luo Gangyin |
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| COR | Change of bibliographic data |
Free format text: CORRECT: INVENTOR; FROM: LUO GANGYIN TO: LUO GANGYIN WANG BIDOU CHEN YUEYAN ZHANG YUNPING |
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| C14 | Grant of patent or utility model | ||
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