CN114511585A - Excrement analysis method and system - Google Patents
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Abstract
The invention provides a stool analysis method, and relates to the field of excrement analysis. The invention provides a stool analysis method, which comprises the following steps: acquiring an image including stool of a user; performing first edge detection on an image including excrement of a user to obtain area information of the excrement; carrying out second edge detection on the area where the excrement is located to obtain appearance information of the excrement; analyzing the shape information of the excrement to obtain an excrement shape analysis result; analyzing the color information of the excrement through a hue saturation value model to obtain an excrement color analysis result; obtaining a final analysis result by analyzing the shape analysis result and the color analysis result of the excrement; and storing the final analysis result into a database. In a word, the image including the excrement of the user is obtained and analyzed to obtain the excrement analysis result, and the analysis steps are simple and efficient.
Description
Technical Field
The invention relates to the field of excrement analysis, in particular to a method and a system for analyzing excrement.
Background
The food taken by people is digested through esophagus, stomach, small intestine, large intestine and the like, and the rest substances are discharged out of the body through anus after forming excrement. Sometimes, people want or need to analyze stool. At this time, in order to analyze the condition of the stool, people need to collect their own stool samples and submit them to medical or detection institutions for analysis in the prior art. However, in the process of transporting the stool sample to the medical or testing facility or in the examination process, the stool sample may be contaminated, and the stool sample may be inverted during the storage in the medical or testing facility, thereby affecting the analysis result. In addition, it takes a certain time to obtain the analysis result after submitting the stool sample to the medical or testing institution, so it is difficult to immediately obtain the analysis result of the stool.
Disclosure of Invention
The invention aims to provide a method and a system for analyzing excrement, which can analyze the excrement condition by acquiring an image including the excrement of a user.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides a stool analysis method, which includes the following steps:
acquiring an image including stool of a user;
performing first edge detection on an image including excrement of a user to obtain area information of the excrement;
carrying out second edge detection on the area where the excrement is located to obtain appearance information of the excrement;
analyzing the shape information of the excrement to obtain an excrement shape analysis result;
analyzing the color information of the excrement through a hue saturation value model to obtain an excrement color analysis result;
obtaining a final analysis result appearance analysis result by analyzing the appearance analysis result and the color analysis result of the excrement;
and storing the final analysis result into a database.
In some embodiments of the invention, the step of obtaining an image comprising the stools of the user is followed by the step of:
an image including stool of a user is subjected to image processing.
In some embodiments of the present invention, a method of image processing an image including stool of a user includes: one or more of color conversion, noise cancellation, or image quality adjustment.
In some embodiments of the invention, the first Edge Detection method uses a Canny Edge Detection algorithm, and the second Edge Detection method uses a Local Binary Pattern algorithm.
In some embodiments of the present invention, the step of analyzing the shape information of the stool to obtain the shape analysis result of the stool specifically includes:
comparing the shape information of the excrement with a set excrement classification table to obtain the classification type of the excrement;
and analyzing the shape information of the excrement according to the classification type of the excrement.
In some embodiments of the present invention, the step of comparing the shape information of the stool with the set stool classification table to obtain the classification type of the stool is performed by using an artificial neural network model.
In some embodiments of the invention, the step of storing the final analysis results in the database further comprises the steps of:
and acquiring and utilizing the bioelectric current information of the user to assist in generating a final analysis result.
In a second aspect, an embodiment of the present application provides a stool analysis system, which includes:
an image acquisition module for acquiring an image including stool of a user;
the first edge detection module is used for carrying out first edge detection on the image including the excrement of the user to obtain the area information of the excrement;
the second edge detection module is used for carrying out second edge detection on the area where the excrement is located to obtain appearance information of the excrement;
the appearance analysis module is used for analyzing the appearance information of the excrement to obtain an excrement appearance analysis result;
the color analysis module is used for analyzing the color information of the excrement through the hue saturation value model to obtain a color analysis result of the excrement;
the judgment module is used for obtaining a final analysis result by analyzing the shape analysis result and the color analysis result of the excrement;
and the storage module is used for storing the final analysis result into the database.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory for storing one or more programs; a processor. The one or more programs, when executed by the processor, implement the method as described in any of the first aspects above.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the method as described in any one of the above first aspects.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
in the prior art, in order to analyze the condition of the excrement of a person, the person is required to collect an excrement sample of the person in the prior art and submit the excrement sample to a medical or detection mechanism for analysis. According to the method and the device, the image including the excrement of the user is obtained and analyzed, so that the excrement analysis result can be obtained, the process is simple and convenient, the analysis efficiency is greatly improved, and the phenomenon that the analysis result is influenced by pollution in the excrement sample submitting and analyzing process is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart of an exemplary method of stool analysis according to the present invention;
FIG. 2 is a flow chart of another embodiment of a stool analysis method according to the present invention;
FIG. 3 is a flow chart of a stool analysis method according to another embodiment of the present invention;
FIG. 4 is a detailed flowchart of analyzing the shape information of stool to obtain the result of analyzing the shape of the stool according to an embodiment of the stool analysis method of the present invention;
FIG. 5 is a block diagram of an embodiment of a stool analysis system according to the present invention;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present invention;
fig. 7 is a chart of bristol stool classification in an embodiment of the present invention.
Icon: 1. a memory; 2. a processor; 3. a communication interface; 11. an image acquisition module; 12. a first edge detection module; 13. a second edge detection module; 14. a shape analysis module; 15. a color analysis module; 16. a judgment module; 17. and a storage module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Examples
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Referring to fig. 1 to 4, fig. 1 is a flowchart illustrating an embodiment of a stool analysis method according to the present invention, fig. 2 is a flowchart illustrating another embodiment of the stool analysis method according to the present invention, fig. 3 is a flowchart illustrating another embodiment of the stool analysis method according to the present invention, and fig. 4 is a flowchart illustrating an embodiment of the stool analysis method according to the present invention, which analyzes shape information of stool to obtain a shape analysis result of the stool. The excrement analysis method comprises the following steps:
step s1, an image including the stool of the user is acquired.
In the prior art, in order to analyze the condition of the excrement of a person, the person is required to collect an excrement sample of the person in the prior art and submit the excrement sample to a medical or detection mechanism for analysis. The process is cumbersome and the stool sample may be contaminated during the submission and examination process, thereby affecting the results of the analysis. In the steps, the image including the excrement of the user is obtained, so that an original basis is provided for subsequent processing and analysis of the image, the analysis process and efficiency are greatly simplified, and the phenomenon that the analysis result is influenced by pollution in the process of submitting and checking the excrement sample is avoided. For example, a camera device may be installed on the toilet to acquire an image including stool of the user.
Referring to fig. 2, fig. 2 is a flowchart illustrating a stool analysis method according to another embodiment of the present invention. The step of acquiring an image including stool of the user may further include the following steps:
step s 11: an image including stool of a user is subjected to image processing.
In the above steps, the image processing is performed on the image including the stool of the user, so that better image information can be provided for subsequent shape analysis of the stool. Illustratively, the method of image processing an image including stool of a user includes: one or more of color conversion, noise cancellation, or image quality adjustment. Generally, an image including stool of a user may not be good in image quality due to the fact that the image may be affected by an imaging device and an external environment during digitization and transmission, and according to actual needs, the image may be subjected to image processing, such as one or more of color conversion, noise elimination, or image quality adjustment. The quality of the processed image can be better, so that the image can be better analyzed and judged, and the processing efficiency and accuracy are improved.
And step s2, performing first edge detection on the image including the excrement of the user to obtain the area information of the excrement.
In the above steps, if stool is located below the water surface in the image including the stool of the user, the analysis of the stool is affected by information such as the light reflection of the water surface and the color of the water surface. Especially when stool is not in a fixed position in the image, the analysis process will be more difficult. And the image including the excrement of the user is subjected to first edge detection, so that excrement and image areas except the excrement can be distinguished, and more accurate data is provided for the subsequent analysis of the appearance of the excrement. After the area where the excrement is located is identified, when the information of the excrement is specifically analyzed subsequently, the area where the excrement is located can be calculated only, and unnecessary calculation amount is greatly reduced.
Illustratively, the first Edge Detection may employ the Canny Edge Detection algorithm. The Canny Edge Detection algorithm specifically comprises the following steps: 1. gaussian filtering; 2. calculating gradient values and gradient directions; 3. filtering the non-maximum values; 4. edges are detected using upper and lower thresholds. The image including the stool of the user is processed by gaussian filtering to obtain a de-noised image, so that the original image can be smoothed, and the width of the edge can be increased. And then, the change degree and direction of the gray value of the denoised image can be identified through the gradient value and gradient direction of the denoised image obtained through calculation. Since the edges are likely to be amplified during the gaussian filtering process. Then, a rule is used to filter points which are not edges through a step of filtering non-maximum values, so that the width of the edges is 1 pixel point as far as possible. Finally, the area where the excrement is located in the image comprising the excrement of the user can be clearly defined by detecting the edge by using the upper threshold and the lower threshold.
And step s3, performing second edge detection on the area where the excrement is located to obtain the shape information of the excrement.
In the above steps, the area where the excrement is located is subjected to the second edge detection, so that the shape of the excrement can be better calculated, and the texture of the excrement can be better analyzed. Illustratively, the second edge detection may employ a Local Binary Pattern algorithm. The Local Binary Pattern algorithm is used for calculating the area where the excrement is located, so that the influence of illumination change on the appearance of the excrement can be avoided, and the appearance information of the excrement can be accurately identified.
And step s4, analyzing the shape information of the excrement to obtain the shape analysis result of the excrement.
In the above steps, the result of analyzing the shape information of the stool includes information such as the size, the number of pieces, the shape of the pieces, the size of the pieces, and the degree of agglomeration of the pieces of the stool. But is not limited thereto and may contain other shape information that may be used for classification.
Referring to fig. 4, fig. 4 is a flowchart illustrating an embodiment of a stool analysis method for analyzing shape information of the stool to obtain a shape analysis result of the stool according to the present invention. Specifically, the step of analyzing the shape information of the stool to obtain the shape analysis result of the stool includes the following steps:
step s 4-1: and comparing the shape information of the excrement with a set excrement classification table to obtain the classification type of the excrement.
In the above steps, an artificial neural network model can be used for execution, and the shape information of the excrement is compared with a set excrement classification table to obtain the classification type of the excrement. The artificial neural network model is used for processing classification of the excrement, and the type of the excrement can be classified more quickly and accurately by utilizing the learning and association functions of the artificial neural network model.
Referring to fig. 7, fig. 7 is a chart of the bursitoto stool classification in the embodiment of the present invention. For example, the set stool classification table may be a bristoc stool classification table. When the Bristol excrement classification table is used, effective data can be provided for subsequent analysis by classifying which of the first type to the seventh type of the Bristol excrement classification table the excrement belongs to. In the classification using the bristol stool classification table, if the shape information of the stools belongs to the first type, the fifth type, the sixth type, and the seventh type of the bristol stool classification table, it may be classified as the stool first type. In addition, when not belonging to the first type candidate group, or when belonging to the second to fourth type candidate groups, it may be classified as the stool second type. At this time, the second type of stool is classified according to the massive lines of the stool, has different characteristics from the first type of stool, and needs to further analyze and judge the massive internal texture of the stool.
Step s 4-2: and analyzing the shape information of the excrement according to the classification type of the excrement.
In the above steps, according to the classification type of the excrement, the shape information of the excrement can be further analyzed under the classification type, so that more accurate shape information can be obtained.
And step s5, analyzing the color information of the excrement through the hue saturation value model to obtain an excrement color analysis result.
The step s5 may be performed before or simultaneously with the step s3, and the sequence of the two steps is not strictly distinguished.
In the step s5, the color information of the stool is analyzed by using the hue saturation value model, so that the information such as the color, the color saturation, the color concentration relation and the like of the stool can be more clearly obtained, and accurate color information of the stool is provided for subsequent analysis.
And step s6, obtaining a final analysis result shape analysis result by analyzing the shape analysis result and the color analysis result of the excrement.
For example, when analyzing the shape of the stool based on the bristol stool classification table, if the shape of the stool of the user is a piece separated like a peanut, the stool belongs to the bristol stool classification table type I; if the shape of the user's stool is like a sausage and there are rugged pieces in it, it is classified as the second type of the bristol stool classification table. When the color of feces is analyzed, the feces can be classified into those of red, gray, dark yellow, yellow brown, green, black, etc.
In the above steps, by analyzing the appearance analysis result and the color analysis result of the stool, double analysis is performed, and a more accurate stool analysis result can be obtained.
And step s7, storing the final analysis result in a database.
In the above steps, the final analysis result is stored in the database, and when analysis is performed next time, the comprehensive analysis can be performed according to the historical storage data and the existing analysis data, so that the analysis result is more rational.
Referring to fig. 3, fig. 3 is a flowchart illustrating a stool analysis method according to another embodiment of the present invention. The step of storing the final analysis result in the database may further comprise the following steps:
and step s61, acquiring and utilizing the bioelectrical current information of the user to assist in generating a final analysis result.
In the step s61, a bioelectric current collecting module may be exemplarily disposed on the toilet, and then the bioelectric current of the user is collected and acquired, and then an analysis result related to the bioelectric current is generated after the judgment processing, so as to assist in analyzing the stool, so that the final analysis result of the stool analysis is more accurate and effective.
Referring to fig. 5, fig. 5 is a block diagram of a stool analysis system according to an embodiment of the present invention. The invention also provides a stool analysis system, which specifically comprises:
an image acquisition module 11 for acquiring an image including stool of a user;
a first edge detection module 12, configured to perform first edge detection on an image including stool of a user to obtain information of an area where the stool is located;
the second edge detection module 13 is configured to perform second edge detection on the area where the stool is located to obtain shape information of the stool;
the appearance analysis module 14 is used for analyzing the appearance information of the excrement to obtain an excrement appearance analysis result;
the color analysis module 15 is configured to analyze color information of the stool through the hue saturation value model to obtain a color analysis result of the stool;
the judging module 16 is used for obtaining a final analysis result by analyzing the shape analysis result and the color analysis result of the excrement;
and the storage module 17 is used for storing the final analysis result into the database.
For a specific implementation process of the above system, please refer to a method for analyzing stool provided in the embodiments of the present application, which is not described herein again.
Referring to fig. 6, fig. 6 is a block diagram of an electronic device according to an embodiment of the present invention. The electronic device comprises a memory 1, a processor 2 and a communication interface 3, wherein the memory 1, the processor 2 and the communication interface 3 are electrically connected with each other directly or indirectly to realize the transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 1 can be used for storing software programs and modules, such as program instructions/modules corresponding to a block chain data copyright protection system for live video big data provided by the embodiment of the application, and the processor 2 executes various functional applications and data processing by executing the software programs and modules stored in the memory 1. The communication interface 3 may be used for communication of signaling or data with other node devices.
The Memory 1 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor 2 may be an integrated circuit chip having signal processing capabilities. The Processor 2 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
It will be appreciated that the configuration shown in fig. 6 is merely illustrative and that the electronic device may include more or fewer components than shown in fig. 6 or have a different configuration than shown in fig. 6. The components shown in fig. 6 may be implemented in hardware, software, or a combination thereof.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The above-described functions, if implemented in the form of software functional modules and sold or used as a separate product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In summary, the present application provides a method and a system for analyzing stool. In the prior art, in order to analyze the condition of the excrement of a person, the person needs to collect an excrement sample of the person and submit the sample to a medical or detection mechanism for analysis. According to the method and the device, the image including the excrement of the user is obtained and analyzed, so that the excrement analysis result can be obtained, the process is simple and convenient, the analysis efficiency is greatly improved, and the phenomenon that the analysis result is influenced by pollution in the excrement sample submitting and analyzing process is avoided.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A stool analysis method, comprising the steps of:
acquiring an image including stool of a user;
carrying out first edge detection on an image including excrement of a user to obtain area information of the excrement;
carrying out second edge detection on the area where the excrement is located to obtain appearance information of the excrement;
analyzing the shape information of the excrement to obtain an excrement shape analysis result;
analyzing the color information of the excrement through a hue saturation value model to obtain an excrement color analysis result;
obtaining a final analysis result by analyzing the appearance analysis result and the color analysis result of the excrement;
and storing the final analysis result into a database.
2. A stool analysis method according to claim 1, further comprising the step of, after said step of acquiring an image including the user's stool, the steps of:
an image including stool of a user is subjected to image processing.
3. A stool analysis method according to claim 2, wherein said image processing of the image including the user's stool comprises: one or more of color conversion, noise cancellation, or image quality adjustment.
4. A stool analysis method according to claim 1, wherein the first Edge Detection method uses Canny Edge Detection algorithm and the second Edge Detection method uses Local Binary Pattern algorithm.
5. The stool analysis method according to claim 1, wherein the step of analyzing the shape information of the stool to obtain the result of analyzing the shape of the stool specifically includes:
comparing the shape information of the excrement with a set excrement classification table to obtain the classification type of the excrement;
and analyzing the shape information of the excrement according to the classification type of the excrement.
6. The stool analysis method according to claim 5, wherein the step of comparing the shape information of the stool with the set stool classification table to obtain the stool classification type is performed using an artificial neural network model.
7. A stool analysis method according to claim 1, wherein said step of storing the final analysis results in a database further comprises the steps of:
and acquiring and utilizing the bioelectric current information of the user to assist in generating a final analysis result.
8. A stool analysis system, comprising:
an image acquisition module for acquiring an image including stool of a user;
the first edge detection module is used for carrying out first edge detection on the image including the excrement of the user to obtain the area information of the excrement;
the second edge detection module is used for carrying out second edge detection on the area where the excrement is located to obtain appearance information of the excrement;
the appearance analysis module is used for analyzing the appearance information of the excrement to obtain an excrement appearance analysis result;
the color analysis module is used for analyzing the color information of the excrement through the hue saturation value model to obtain a color analysis result of the excrement;
the judging module is used for obtaining a final analysis result by analyzing the appearance analysis result and the color analysis result of the excrement;
and the storage module is used for storing the final analysis result into the database.
9. An electronic device, comprising:
a memory for storing one or more programs;
a processor;
the one or more programs, when executed by the processor, implement the method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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| CN112102257A (en) * | 2020-08-26 | 2020-12-18 | 电子科技大学 | Automatic human body excrement identification method based on convolutional neural network |
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| CN105654469A (en) * | 2015-12-22 | 2016-06-08 | 深圳贝申医疗技术有限公司 | Infant stool color automatic analysis method and system |
| CN106651883A (en) * | 2016-12-30 | 2017-05-10 | 四川沃文特生物技术有限公司 | Machine vision-based excrement shape identification method |
| CN106682633A (en) * | 2016-12-30 | 2017-05-17 | 四川沃文特生物技术有限公司 | Method for classifying and identifying visible components of microscopic excrement examination images based on machine vision |
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