WO2019153934A1 - 一种移动终端定量分析干化学检测试条的系统和方法 - Google Patents

一种移动终端定量分析干化学检测试条的系统和方法 Download PDF

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WO2019153934A1
WO2019153934A1 PCT/CN2018/124212 CN2018124212W WO2019153934A1 WO 2019153934 A1 WO2019153934 A1 WO 2019153934A1 CN 2018124212 W CN2018124212 W CN 2018124212W WO 2019153934 A1 WO2019153934 A1 WO 2019153934A1
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test strip
image
value
concentration
color
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PCT/CN2018/124212
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English (en)
French (fr)
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陈昌云
曾嵘斌
王小锋
范勇
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曾嵘斌
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/8483—Investigating reagent band
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N21/78—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/02—Mechanical
    • G01N2201/022—Casings
    • G01N2201/0221—Portable; cableless; compact; hand-held

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  • the invention relates to a system and a method for quantitatively analyzing dry chemical test strips, in particular to a system and method for quantitative analysis of dry chemical test strips in mobile terminals.
  • instant diagnosis As a kind of on-site rapid detection technology, instant diagnosis has developed rapidly in recent years.
  • the so-called instant diagnosis means that the test results are quickly obtained by the patient.
  • the technology is convenient and fast, does not rely on expensive laboratory equipment or professional technicians, and does not require complicated sample processing steps, which greatly facilitates the analysis operation.
  • Analytical tests can be divided into liquid reagents and dry chemical reagents according to the type of analytical reagents.
  • the liquid reagent (wet chemical) method can obtain satisfactory accuracy and precision, but it requires expensive instruments and professional technicians, and the operation is cumbersome, and the results cannot be quickly determined. It is not suitable for on-site inspection, such as hospital emergency room and small.
  • Dry chemical reagents complement the wet chemical method with its advantages of simple operation, fast and flexible measurement, and no need for professionals. The measurement accuracy and precision are close to the wet chemical determination method. Dry chemical test strips are widely used in clinical testing, food safety testing, environmental quality testing and other fields, providing great convenience.
  • “Dry chemistry” is in contrast to the conventional "wet chemistry", which is a way in which the liquid in the sample to be tested is used as a reaction medium, and the analyte is directly reacted with a dry powder reagent solidified on the carrier.
  • the biggest difference between it and traditional wet chemistry is that the medium involved in the chemical reaction is different.
  • Some or all of the reagents required for the reaction are fixed in a carrier with a special structure, causing the analyte to react with the reagent in the carrier and generate The reaction signal is finally measured by visual qualitative, semi-quantitative analysis or quantitative analysis by a portable instrument to measure the concentration of the analyte in the sample.
  • Dry chemical analysis has the advantages of short-term sensitivity, simple, rapid, real-time, on-site diagnosis, wide application, etc., especially in line with the requirements of real-time diagnostic technology, suitable for basic layer inspection and large-area census, etc., with great development potential and broad Application prospects.
  • Aobe Photoshop analyzes the color of the color-developed area and quickly completes data acquisition, signal processing, data analysis, and conclusions. This method is to obtain the test paper image through the image sensor, and based on the image measurement principle, the software captures the color information of the test paper, and uses the statistical analysis of the data and the interpretation of the image to obtain the quantitative detection result.
  • the smart phone is used in the detection and analysis research work to obtain real images and process image information through the mobile phone camera function.
  • the quality of the picture taken by the mobile phone camera will face the external ambient light, as well as the exposure time, exposure rate, sensitivity, and focal length of different mobile phones, and will be affected by the position and angle of the smartphone camera.
  • a research team has developed supporting devices to eliminate these interference factors in order to obtain high-quality digital image information.
  • Patent "CN201710116895.9 an electrochemiluminescence biochemical detection system and method based on mobile phone USB-OTG interface” and "CN201610051775.0 a method for quantitative analysis of dry chemical detection reagents in mobile terminals" is to make the color information collected by the mobile phone Gray scale processing, based on the gray value as a standard curve, processing the gray value of the sample to quantify.
  • the above research is to obtain different quantitative values for color information, which has strict requirements on the image quality of photo collection. It is necessary to standardize various indicators when photographing, including special supporting equipment and lighting conditions, as well as mobile phones. Shoot angles, distances, and exposure times to get high quality image information. If necessary, you need to use the reference standard swatch to deduct the difference in the phone when taking pictures. With this type of processing technology, it is necessary to solve the distortion of the color caused by different light backgrounds, and the color of the sample itself will have no small impact on the detection.
  • the patent "CN104359904B, a method for detecting organophosphorus pesticide residues based on a barcode readable by a smartphone” and "the method for detecting a biological rapid detection based on a two-dimensional code of a smart phone by CN201610863598.6” are formed by etching microchannels on a chip. Barcode and QR code shape. After different samples are reacted on the chip, different barcode or QR code shape information will be formed, and the content of the sample will be obtained through the interpretation of the mobile phone.
  • this technology requires high precision of the microchannel processing of the chip, and its cost is high, and at the same time, it can only detect a certain range of samples.
  • the above-mentioned smart phone color processing analysis method and graphic processing analysis method often require external supporting equipment, and the color processing method is not easy to eliminate the interference of the sample color; the cost of the graphic processing analysis method is high and cannot be completely used for quantitative analysis, and becomes a constraint mobile phone. Quickly detect application factors on site.
  • the color processing analysis method is the absolute value of the collected color, which is the reason why this method requires an external device, and also the cause of the interference of the color of the sample itself, which is equivalent to the distortion process of the analog signal in the circuit during processing.
  • the graphics processing analysis method is equivalent to the processing of digital signals in the circuit, avoiding the distortion process; compared with the color processing analysis method, it contains less information, that is, it cannot be completely used for quantitative analysis.
  • the main idea of the present invention is to use a processing analysis method similar to the processing of digital signals and containing a large amount of information.
  • some research is to convert the concentration information of the sample into a distance signal.
  • the content of the sample is related to the distance of the color development of the chip or the test paper, and the content of the sample is obtained by reading the length of the color development distance.
  • the color of the reaction product is diffused by lateral diffusion on the channel of the paper chip, and the distance information of the color is displayed to reflect the content of the sample; the color development here is only on the channel of the paper chip.
  • the patent "CN105021596B Multilayer Membrane Dry Chemistry Test Strip Based on Concentration Gradient” is by the distribution of the titrant in a concentration gradient.
  • a titration quantitative model on the solid phase carrier is established, two color regions are formed on the test strip, and the position information of the color mutation point on the test strip can be read to obtain the sample content, which is a solution capable of quantitatively analyzing the sample.
  • This quantitative scheme due to the formation of two color regions, reflected on the components of the color system, there will be a sudden change in the position of the one or two color components at the point of the mutation, which is a relative amount, containing digital information, easy Reading and processing, this facilitates the work of the smartphone.
  • the color interference of the sample can be eliminated, and the background of the ambient light will not affect the result, so that no external device is needed, and it is completely required to use the mobile phone and test.
  • the article can achieve the purpose of rapid quantitative analysis and detection on site.
  • the present invention is directed to a system and method for quantitative analysis of dry chemical test strips for mobile terminals in view of the deficiencies of the prior art.
  • the method of the invention is simple, convenient to operate, and the concentration of the test strip can be quantitatively analyzed without external equipment.
  • the system for quantitatively analyzing a dry chemical detection test strip of the mobile terminal of the present invention comprises: a test strip and a mobile terminal, wherein the mobile terminal includes an application module, and the application module includes
  • An image capturing unit that performs image capturing on the detecting strip
  • the image processing unit denoises and extracts color edge lines from the image captured by the image acquisition unit; reduces noise and deblurs, includes reading each color component for all pixels on the image, and using weighted mean filtering and median values in the detection strip Filtering removes Gaussian noise and salt-and-salt noise in the image; extracts the color edge line, and uses the adaptive threshold fuzzy hopping cellular neural network algorithm to extract the transition line of each color component in the image along the length direction of the test strip, and the transition line of the color component Forming intersections, a plurality of intersections constituting a color edge line on the test strip;
  • the concentration calculation unit establishes a concentration curve and calculates a sample concentration value; the concentration calculation unit uses the length of the test strip as the X axis, and the sample concentration value as the Y axis to establish a concentration curve; the color edge line read by the image processing unit is The weighted average value on the X coordinate axis is taken as the X value, and the Y value corresponding to the X value is found according to the concentration curve, and the Y value is the concentration value of the sample.
  • the surface of the detection strip is provided with encoding information including a detection item name, a detection strip source, and measurement range information.
  • the application module further includes a detection result uploading unit, configured to upload the sample concentration value and the encoded information to a cloud database for the user to view and manage.
  • the image acquisition unit includes an imaging recognition device for automatically identifying whether the detection strip image is clear; if the image is clear, the test strip image is manually or automatically photographed; if the image is not clear, the photograph cannot be photographed. Check the image of the test strip.
  • the invention also provides a method for quantitatively analyzing a dry chemical detection test strip of a mobile terminal, opening a camera of the mobile terminal, adjusting the camera, the aperture and the test strip on the same straight line, comprising the following steps,
  • the image processing unit denoises and extracts color edge lines from the image captured by the image acquisition unit; reduces noise and deblurs, including reading each color component on all pixels on the image, and using weighted mean filtering on the detection strip Median filtering removes Gaussian noise and salt and pepper noise in the image; extracts the color edge line, and uses the adaptive threshold fuzzy hopping cellular neural network algorithm to extract the transition line of each color component in the image along the length direction of the test strip, and the color component The transition lines form intersections, and a plurality of intersections form a color edge line on the test strip;
  • the concentration calculation unit establishes a concentration curve and calculates a sample concentration value; the concentration calculation unit uses the length of the test strip as the X axis, and the sample concentration value as the Y axis to establish a concentration curve; the color read by the image processing unit The weighted average value of the edge line on the X coordinate axis is taken as the X value, and the Y value corresponding to the X value is found according to the concentration curve, and the Y value is the concentration value of the sample;
  • the detection result uploading unit uploads the detection result to the cloud database for the user to view and manage.
  • the invention directly quantitatively analyzes the concentration of the test strip through the mobile terminal, and does not require an external device, and the method is simple, the operation is convenient, and the convenience is greatly improved.
  • the detection process of the present invention has low requirements on the background of the ambient light, and can be detected under the background of ordinary lights, and has strong adaptability.
  • the application module of the mobile terminal of the present invention is for detecting the distance information of the color change on the test strip, and reading the relative change value of the color, and performing the weighted average processing after the image is subjected to the break point of the divided region, and the analysis processing workload is small.
  • the processing speed is fast, the error is small, the task is simple, the versatility is strong, and it can be applied to different color changing series; as a universal platform, it can be used for detecting content of different projects, and at the same time, direct quantitative detection of multiple items on one mobile phone is completed. Wide range of applications.
  • Figure 1 is a diagram showing the distribution of color components of a test strip of the present invention.
  • Figure 2 is a graph showing the concentration of the present invention.
  • Figure 3 is a prior art color component standard curve diagram.
  • Embodiment 1 A system for quantitatively analyzing dry chemical test strips of a mobile terminal, including a test strip, a mobile terminal, and a cloud database.
  • the mobile terminal includes an application module, and the application module includes an image acquisition unit, an image processing unit, a concentration calculation unit, and a detection result uploading unit.
  • the mobile terminal includes mobile devices such as mobile phones and tablet computers, and the application module implements functions through software programming, and the user can install the application modules on the mobile terminal.
  • the surface of the test strip is provided with coding information, and the coded information is in the form of a barcode and a two-dimensional code, and the coded information includes the name of the test item, the source of the test strip, and the measurement range information.
  • the image acquisition unit is configured to capture image information of the test strip, and adjust the camera, the aperture, and the detection strip of the mobile terminal on the same line before performing the detection of the test strip image.
  • the image acquisition unit includes an imaging recognition device for automatically identifying whether the encoded information of the test strip and the color information are imaged. If the image is clear, the test strip image is taken manually or automatically; if the image is not clear, the test strip image cannot be taken.
  • the image processing unit denoises and extracts color edge lines from the image captured by the image acquisition unit; reduces noise and deblurs, includes reading each color component for all pixels on the image, and using weighted mean filtering and median values in the detection strip Filtering removes Gaussian noise and salt-and-salt noise in the image; extracts the color edge line, and uses the adaptive threshold fuzzy hopping cellular neural network algorithm to extract the transition line of each color component in the image along the length direction of the test strip, and the transition line of the color component An intersection is formed, and a plurality of intersections constitute a color edge line on the test strip.
  • the test strip is divided into a plurality of horizontal blocks, and the position of the color edge line of each block is found according to the above method, for all color edge lines.
  • the position weighted average value is obtained, thereby obtaining the color edge line of the entire test strip.
  • the concentration calculation unit establishes a concentration curve and calculates a sample concentration value; as shown in FIG. 2, the concentration calculation unit uses the length of the test strip as the X axis, and the sample concentration value as the Y axis to establish a concentration curve; the image processing unit reads The weighted average value of the obtained color edge line on the X coordinate axis is taken as the X value, and the Y value corresponding to the X value is found according to the concentration curve, and the Y value is the concentration value of the sample.
  • the detection result uploading unit uploads the detection result of the coded information on the surface of the test strip and the concentration value of the sample to the cloud database resource sharing. After the user registers the account through the application module, the test result can be uploaded to the cloud database, which facilitates the analysis and management of the test data in the future.
  • Application modules enable data synchronization based on systems such as Android, IOS, Windows, BlackBerry, Symbian, and JAVA.
  • a method for quantitatively analyzing a dry chemical test strip by a mobile terminal comprising the following steps:
  • the image acquisition unit automatically adjusts the aperture and auto focus, and automatically recognizes the coding information and color information on the test strip.
  • the image information is acquired by manual or automatic photographing; when the image is not clear, it cannot be photographed.
  • the image processing unit receives the image captured by the image acquisition unit, and reads the coded information area and the color information area on the surface of the test strip.
  • the image processing unit denoises and extracts color edge lines from the image captured by the image acquisition unit; reduces noise and deblurs, and includes reading color components for all pixels on the image, such as R, G, and B in the RGB system. Extraction of color components; Gaussian noise and salt and pepper noise in the image are removed using a weighted mean filter and a median filter on the test strip.
  • the color edge line is extracted, and the adaptive hopping fuzzy hopping cell neural network algorithm extracts the transition line of each color component in the image along the length direction of the detection strip, and the transition line of the color component forms an intersection point, as shown in FIG.
  • a sudden change in the color of the test strip in the length direction results in a longitudinal transition of the color component at the abrupt position, and the transition lines of the two color components form an intersection A; a number of intersections constitute the color edge line on the test strip.
  • the concentration calculation unit establishes a concentration curve and calculates a sample concentration value; the concentration calculation unit uses the length of the test strip as the X axis, and the sample concentration value as the Y axis to establish a concentration curve; the color read by the image processing unit The weighted average value of the edge line on the X coordinate axis is taken as the X value, and the Y value corresponding to the X value is found according to the concentration curve, and the Y value is the concentration value of the sample.
  • the detection result uploading unit uploads the detection information such as the coded information on the surface of the test strip and the detected concentration value to the cloud database for the user to view and manage.

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Abstract

一种移动终端定量分析干化学检测试条的系统，包括检测试条和移动终端，所述移动终端包括应用模块，所述应用模块包括，图像采集单元，对所述检测试条进行图像拍摄；图像处理单元，对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条的长度作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值。一种运用所述系统获取所述试条的定量方法，该方法简单、操作方便、无需外接设备，即可定量分析检测试条的浓度。

Description

一种移动终端定量分析干化学检测试条的系统和方法 技术领域
本发明涉及一种定量分析干化学检测试条的系统和方法，具体涉及一种移动终端定量分析干化学检测试条的系统和方法。
背景技术
人们对自身健康安全以及生活环境的关注，离不开分析检验的支持，包括医疗临床检验、食品安全检测和环境质量检测等，这些分析检测从以前的手工实验的方法正在朝着全自动、智能化和现场检测方向发展，极大地减轻了分析操作人员的工作负担。
即时诊断作为一种现场快速检测技术，近年来发展迅速。所谓即时诊断，是指在病人身旁迅速获得检测结果。该技术方便快捷，不依赖昂贵的实验仪器设备或者专业的技术人员，亦不需借助复杂的样品处理步骤，极大地方便了分析操作。
分析检验按分析试剂类型可以分为液体试剂和干化学试剂两种方法。采用液体试剂(湿化学)方法可以获得较为满意的准确度和精密度，但需昂贵的仪器和专业技术人才，并且操作繁琐、不能快速测定出结果，不适合现场检验，如医院急诊室和小批量样品的检测的需求。而干化学试剂以其操作简便、测定快速灵活以及无需专业人士等优点，能很好地补充了湿化学法的不足之处，其测定准确度和精密度已经接近湿化学测定方法，其中尤以干化学检测试条广泛地应用于临床检验、食品安全检测、环境质量检测等领域，提供了极大的便利。“干化学”是与传统的“湿化学”是相对而言的，它是以被检测样品中的液体作为反应介质，待测物直接与固化于载体上的干粉试剂反应的一种方式。它与传统湿化学的最大区别就在于参与化学反应的媒介不同，预先将反应所需的部分或全部试剂固定在具有特殊结构的载体中，引起待测物与载体中的试剂发生化学反应并产生反应信号，最后通过目视定性、半定量分析或通过便携式仪器定量分析，从而测得样品中待测物的浓度。随着生物化学中酶的分离、提纯和存储等技术的发展，传感器、光度计和电极技术的进步，以及计算机应用的普及，干化学技术在近20年里得到了长足的进步。干化学分析因其微量敏感、简易、快速、实时、可做现场诊断、适用面广等优点，特别符合即时诊断技术的要求，适合基层检测和大面积普查等需求，具有巨大的发展潜力和广阔的应用前景。
然而，干化学直接目视分析存在着分辨率低、只能定性不能定量、检测结果依赖操作者的主观经验、检测具有极大主观性、误判率较高、检测结果只能手工记录、不易保存、只适用于专业人员使用等弊端。由于对检测分析的精确度要求不断提高，这就需要能够提供 一个定量数据的新的解决方案。随着技术的进步，传统的通过目视结果的方法正逐步被使用仪器设备读取所代替，使用仪器设备读取结果从一定程度上避免了人为主观因素的影响，从而使得检测结果更为准确。基于图像处理的试条定量检测方法广泛受到关注，成为获取定量结果数据的有效方法。试条图像的采集一般通过专门的CCD或CMOS图像传感器，然后使用个人计算机或者昂贵的处理器进行下一步的处理，这种方法影响了便携性和实用性，对现场检测不能提供很好的支持。
随着电子信息的快速发展，人们可以随时随地以多种方式进行信息访问，其中智能手机是最常用的方法之一，许多研究采用智能手机、照相机或扫描仪记录试纸的显色区域，再用Aobe Photoshop分析显色区域的颜色，快速完成数据采集、信号处理、数据分析和获得结论等步骤。这种方法是通过图像传感器获取试纸图像，以图像测量原理为基础运用软件捕获试纸的颜色信息，利用数据统计分析和判读图像，得到定量检测结果。
基于智能手机的即时诊断技术引起了广泛的关注，是国内外众多科研机构的热门研究课题。如专利“CN206270246U一种用于智能手机拍照成像快检水中毒害物质的智能检水光盒”、“CN201610122771.7一种现场快速检测邻苯二酚及其衍生物的系统及检测方法”、“CN201380058363.4用于生物分子反应点收集测量的设备和方法”、“CN104730265B手持式POCT流式基因分析系统”、“CN201610914030.2基于颜色主波长和补色波长的分子智能手机速测方法”、“CN201610981565.1一种微型毛细管荧光仪”和“CN102165321B用于检测生物和环境检测样品的一次性手持式诊断检测设备和相关系统与方法”，在使用智能手机作为检测设备的信号采集系统的研究做了有益的尝试。虽然图像传感器的分辨率对试纸图像的分析精度有一些影响，但是这种方法因具有成本低廉、操作简单、检测快速、便于携带等优势，越来越受到人们的关注。
智能手机运用在检测分析研究工作，是通过手机拍照功能，获取真实的图像以及对图像信息进行处理。而手机摄像头拍照得到图片的质量，将会面临外界环境光线，以及不同手机的曝光时间、曝光率、感光度，焦距的因素的影响，还会受到智能手机摄像头的位置和角度的重要影响。为此，有研究团队开发了配套装置，以排除这些干扰因素，以期获取高质量的数字图像信息。如专利“CN205982094U一种基于智能移动终端的食品安全检测装置”、“CN201710305207.3一种基于智能手机的免疫层析芯片定量分析系统”、和“CN201610707152.4基于移动终端的变色诊断试纸定量成像系统”中专门设计能固定手机和试条的装置，并在装置中分布光源以避免外界光的干扰。如专利“CN201710541399.8一种快速量化信息化的肿瘤相关特异抗原的检测方法、检测装置及其制备方法”通过给手机加 装能固定试条的简易塑料卡座，提高手机对试条拍照效果。
如何对图像信息处理，从中读取样品的含量，不少研究团队以图像颜色分析手段，实现对数据的读取，如专利“CN201480017254.2基于智能手机的装置和用于获取可重复的定量比色测量的方法”，将手机采集到的RGB颜色系统转换成色调-饱和度-明度(HSL)颜色系统的信号，HSL颜色系统的色调值与常规通用指示剂材料的pH值呈近似线性变化，从而达到定量的效果；如专利“PCT/US2012/064856纸基诊断测试”，通过手机采集测试区的图像颜色；软件处理判读，以标准化颜色强度值为判断依据，将图像转换成RGB、HSV或CMYK颜色体系，读取所需的体系颜色分量(如RGB体系中的R,G,B中的某一分量)，根据颜色分量标准曲线来实现定量；专利“CN201610031888.4一种基于手机颜色分析的半胱氨酸检测方法”、“CN201510508573.X一种基于智能手机快速现场检测金属离子的方法”、“CN105181959B一种免疫层析试条定量检测装置及方法”和“CN103954751B纸基微流控免疫传感器芯片和现场及时检测免疫分析平台”也采用同类的颜色分量的处理方法，如图3所示。
专利“CN201710116895.9一种基于手机USB-OTG接口的电化学发光生化检测系统及方法”和“CN201610051775.0一种移动终端定量分析干化学检测试剂的方法”是将手机采集到的颜色信息做灰度处理，根据灰度值做标准曲线，处理样品的灰度值来定量。
以上的研究是对颜色信息进行不同处理获取定量数值，这就对拍照采集的图像质量有严格的要求，需要对拍照时各项指标进行规范，包括专用的配套设备和采光条件，还有对手机拍摄角度、距离和曝光时间的要求，以期获取高质量的图像信息。必要时，需要用参考的标准色板以扣除拍照时手机各自的差异。采用此类处理技术，需要解决针对不同光背景带来的颜色的失真，同时样品本身的颜色也会给检测带来不小的影响。
同时，在探寻智能手机在检测分析技术中还有不同的研究方法，其中不再采集图像的颜色信息，而通过事先的对芯片的结构处理，会导致分析前后的芯片上显示的图形的形状变化，对图形处理分析，以实现快速检测的目的。现有的条形码和二维码的识别技术成熟，将条形码和二维码的技术运用在检测分析中，便于手机把条形码或二维码包含的信息处理成数字信息。如专利“CN104359904B一种基于智能手机可读条形码式样的有机磷农残检测方法”和“CN201610863598.6基于智能手机二维码式样的生物快速检测方法”就是通过在芯片上刻蚀微通道分别形成条形码和二维码形状，不同含量的样品在芯片上反应后，会形成不同的条形码或二维码形状信息，通过手机的解读获取样品的含量。然而，此项技术对芯片的微通道加工精度要求高，其成本较高，同时只能对某一范围的含量样品检测。
上述智能手机颜色处理分析方法和图形处理分析方法往往需要外接配套设备，同时颜色处理方法不容易消除样品本身颜色的干扰；图形处理分析方法的成本较高且不能完全用于定量分析，成为制约手机在现场快速检测应用的因素。
利用移动终端设计一种能避免样品本身颜色的干扰、无需外接设备，可以定量分析干化学检测试剂的方法，就成为本发明的关键。
颜色处理分析方法是采集的颜色的绝对值，这就是此方法需要外接设备的原因，也是样品本身颜色的干扰的原因，这就相当于电路中模拟信号在处理过程中的失真过程。图形处理分析方法，相当于电路中数字信号的处理，避免了失真过程；相对于颜色处理分析方法，其包含的信息少，也就是不能完全用于定量分析的原因。采用类似于数字信号的处理并包含大量信息的处理分析方法，是本发明的主要思路。
在可视化分析研究中，有研究是将样品的浓度信息转变为距离信号的方法，样品的含量与芯片或试纸的显色的距离相关，通过读取显色距离的长短获取样品的含量。如文献“Microfluidic Distance Readout Sweet Hydrogel Integrated Paper-based Analytical Device(μDiSH-PAD)for Visual Quantitative Point-of-Care Testing，”和专利“CN201710670159.8一种3D集成纸芯片及可视化快速定量检测靶标方法”，通过反应生成物在纸芯片的通道上侧向流扩散显色，显示出颜色的距离信息，从而反映样品的含量；这里的显色只在纸芯片的通道上。专利“CN105021596B基于浓度梯度的多层膜干化学检测试条”是通过将滴定剂以浓度梯度的分布。建立起固相载体上的滴定定量模型，在试条上形成两个颜色区域，读取颜色突变点在试条上的位置信息可以获取样品含量，这就是能够定量分析检测样品的解决方案。这种定量的方案，由于形成两个颜色区域，反映到颜色体系的分量上，就会有一个或两个颜色分量在突变点位置的突然变化，是个相对量，包含着数字量的信息，容易读取和处理，这方便了智能手机工作，同时，由于是相对量，样本的颜色干扰可以排除，环境光的背景不会影响结果，从而不额外需要外接设备，完全达到只需用手机和试条就能实现现场快速定量分析检测的目的。
针对互联网行业的发展，基于智能平台的检测设备也逐渐成为研发的热点，各大互联网公司布局互联网医疗发展，将智能手机作为移动检测终端是个重要的方向，能直接使用手机作为检测设备，给现场检测带来极大的方便，更能方便非专业人士的使用，拓展应用领域，也为分析检测数据的云计算提供数据基础。
发明内容
发明目的：本发明目的在于针对现有技术的不足，提供一种移动终端定量分析干化 学检测试条的系统和方法。本发明方法简单、操作方便、无需外接设备，即可定量分析检测试条的浓度。
技术方案：本发明所述移动终端定量分析干化学检测试条的系统，包括检测试条和移动终端，所述移动终端包括应用模块，所述应用模块包括，
图像采集单元，对所述检测试条进行图像拍摄；
图像处理单元，对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去模糊，包括对图像上所有像素点读取各颜色分量，在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声；提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，若干交叉点构成检测试条上的颜色边缘线；
浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条的长度作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值。
进一步地，所述检测试条的表面设置有编码信息，所述编码信息包括检测项目名称、检测试条来源和测量范围信息。
进一步地，所述应用模块还包括检测结果上传单元，用于将样品浓度值和所述编码信息上传至云端数据库供用户查看和管理。
进一步地，所述图像采集单元包括成像识别装置，用于自动识别所述检测试条成像是否清晰；若成像清晰，则手动或自动拍摄检测试条图像；若成像不清晰，则无法拍摄所述检测试条图像。
本发明还提供一种移动终端定量分析干化学检测试条的方法，开启移动终端的摄像头，调节摄像头、光圈和检测试条处于同一直线上，包括以下步骤，
(1)启动应用模块，图像采集单元对所述检测试条进行图像拍摄；
(2)图像处理单元对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去模糊，包括对图像上所有像素点读取各颜色分量，在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声；提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，若干交叉点构成检测试条上的颜色边缘线；
(3)浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条的长度 作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值；
(4)检测结果上传单元将检测结果上传至云端数据库供用户查看和管理。
有益效果：(1)本发明通过移动终端直接定量分析检测试条的浓度，无需外接设备，方法简单、操作方便，极大地提高了便捷性。
(2)本发明的检测过程对环境灯光背景的要求不高，在普通灯光背景下即可进行检测，适应性较强。
(3)本发明移动终端的应用模块是针对检测试条上变色的距离信息，读取的是颜色的相对变化值，将图像进行分区域取突变点后进行加权平均处理，分析处理工作量少、处理速度快、误差小、任务简单、通用性强，可以适用于不同变色系列；作为通用性平台，可用于不同项目的检测内容，同时在一部手机上完成多个项目的直接定量检测，适用范围广泛。
附图说明
图1为本发明检测试条颜色分量分布图。
图2为本发明浓度曲线图。
图3为现有技术颜色分量标准曲线图。
具体实施方式
下面通过附图对本发明技术方案进行详细说明，但是本发明的保护范围不局限于所述实施例。
实施例1：一种移动终端定量分析干化学检测试条的系统，包括检测试条、移动终端和云端数据库。所述移动终端包括应用模块，应用模块包括图像采集单元、图像处理单元、浓度计算单元和检测结果上传单元。移动终端包括手机、平板电脑等移动设备，应用模块通过软件编程实现功能，用户将应用模块安装在移动终端上即可使用。
检测试条的表面设置有编码信息，编码信息为条形码和二维码等形式，编码信息包括检测项目名称、检测试条来源和测量范围信息。
图像采集单元用于拍摄检测试条的图像信息，在进行检测试条图像拍摄前，调节移动终端的摄像头、光圈和检测试条位于同一直线上。图像采集单元包括成像识别装置，用于自动识别检测试条的编码信息和颜色信息成像是否清晰。若成像清晰，则手动或自动拍摄检测试条图像；若成像不清晰，则无法拍摄检测试条图像。
图像处理单元，对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去 模糊，包括对图像上所有像素点读取各颜色分量，在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声；提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，若干交叉点构成检测试条上的颜色边缘线。优选地，为了使提取的检测试条上颜色边缘线的位置更加精确，将检测试条划分成若干个横向区块，按照上述方法找出各区块颜色边缘线的位置，对所有颜色边缘线的位置加权平均取值，从而得出整个检测试条的颜色边缘线。
浓度计算单元，建立浓度曲线，并计算样品浓度值；如图2所示，浓度计算单元以检测试条的长度作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值。
检测结果上传单元将检测试条表面的编码信息和样品的浓度值等检测结果上传至云端数据库资源共享。用户通过应用模块注册账户后，可将检测结果上传至云端数据库，方便日后对检测数据的分析和管理。应用模块可实现基于Android、IOS、Windows、BlackBerry、Symbian和JAVA等系统的数据同步功能。
一种移动终端定量分析干化学检测试条的方法，包括以下步骤：
(1)启动应用模块，打开移动终端的摄像头，调节摄像头、光圈和检测试条位于同一直线上。
(2)图像采集单元自动调节光圈、自动对焦，自动识别检测试条上的编码信息和颜色信息。当屏幕上成像清晰时，通过手动或自动拍照的方式采集图像信息；当成像不清晰时，则无法拍摄。
(3)图像处理单元接收图像采集单元拍摄的图像，读取试条表面的编码信息区和颜色信息区。图像处理单元，对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去模糊，包括对图像上所有像素点读取各颜色分量，如RGB体系中R、G和B三种颜色分量的提取；在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声。提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，如图1所示，由于检测试条在长度方向上颜色的突变，导致了颜色分量在突变位置处的纵向跃迁，两种颜色分量的跃迁线形成了交叉点A；若干交叉点构成了检测试条上的颜色边缘线。
(4)浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条 的长度作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值。
(5)检测结果上传单元将检测试条表面的编码信息和检测的浓度值等检测结果上传至云端数据库供用户查看和管理。
如上所述，尽管参照特定的优选实施例已经表示和表述了本发明，但其不得解释为对本发明自身的限制。在不脱离所附权利要求定义的本发明的精神和范围前提下，可对其在形式上和细节上作出各种变化。

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  1. 一种移动终端定量分析干化学检测试条的系统，包括检测试条和移动终端，所述移动终端包括应用模块，其特征在于：所述应用模块包括，
    图像采集单元，对所述检测试条进行图像拍摄；
    图像处理单元，对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去模糊，包括对图像上所有像素点读取各颜色分量，在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声；提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，若干交叉点构成检测试条上的颜色边缘线；
    浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条的长度作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值。
  2. 根据权利要求1所述的移动终端定量分析干化学检测试条的系统，其特征在于：所述检测试条的表面设置有编码信息，所述编码信息包括检测项目名称、检测试条来源和测量范围信息。
  3. 根据权利要求2所述的移动终端定量分析干化学检测试条的系统，其特征在于：所述应用模块还包括检测结果上传单元，用于将样品浓度值和所述编码信息上传至云端数据库供用户查看和管理。
  4. 根据权利要求1所述的移动终端定量分析干化学检测试条的系统，其特征在于：所述图像采集单元包括成像识别装置，用于自动识别所述检测试条成像是否清晰；若成像清晰，则手动或自动拍摄检测试条图像；若成像不清晰，则无法拍摄所述检测试条图像。
  5. 一种移动终端定量分析干化学检测试条的方法，开启移动终端的摄像头，调节摄像头、光圈和检测试条处于同一直线上，其特征在于：包括以下步骤，
    (1)启动应用模块，图像采集单元对所述检测试条进行图像拍摄；
    (2)图像处理单元对图像采集单元拍摄的图像降噪去模糊和提取颜色边缘线；降噪去模糊，包括对图像上所有像素点读取各颜色分量，在检测试条使用加权均值滤波和中值滤波去除图像中的高斯噪声和椒盐噪声；提取颜色边缘线，使用自适应阈值的模糊跳变细胞神经网络算法沿检测试条的长度方向提取图像中各颜色分量的跃迁线，颜色分量的跃迁线形成交叉点，若干交叉点构成检测试条上的颜色边缘线；
    (3)浓度计算单元，建立浓度曲线，并计算样品浓度值；浓度计算单元以检测试条的长度 作为X轴，以样品浓度值作为Y轴建立浓度曲线；将图像处理单元读取到的颜色边缘线在X坐标轴上的加权平均值作为X值，根据浓度曲线找到与该X值对应的Y值，Y值即为样品的浓度值；
    (4)检测结果上传单元将检测结果上传至云端数据库供用户查看和管理。
PCT/CN2018/124212 2018-02-07 2018-12-27 一种移动终端定量分析干化学检测试条的系统和方法 WO2019153934A1 (zh)

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