CN110301891B - Hyperspectrum-based detection early warning method, detector and system - Google Patents
Hyperspectrum-based detection early warning method, detector and system Download PDFInfo
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- CN110301891B CN110301891B CN201910494845.3A CN201910494845A CN110301891B CN 110301891 B CN110301891 B CN 110301891B CN 201910494845 A CN201910494845 A CN 201910494845A CN 110301891 B CN110301891 B CN 110301891B
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0075—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
- A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
Abstract
The application discloses a hyperspectral-based detection and early warning method, which comprises the following steps: detecting the hyperspectral distribution of the surface of target skin to be detected to obtain current spectral distribution characteristic data; comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, wherein the skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing skin hyperspectral information; determining the spectral feature map change trend of the target skin according to the comparison result; and if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, prompting and early warning are carried out. The method and the device can predict the change trend of the skin state, and prompt and early warning are carried out according to the prediction result, so that the user can avoid damage to the skin and manage the health state of the skin.
Description
Technical Field
The application relates to the field of medical treatment, in particular to a hyperspectral detection early warning method, a hyperspectral detector and a hyperspectral detection early warning system.
Background
Skin cancer is a common cancer and poses a significant health hazard to humans. The causes of skin cancer can be broadly classified into the following: first, daily solarization and ultraviolet irradiation have enough evidence to support ultraviolet irradiation, and the interaction of the protection of human melanin and the functions of the immune system leads to the occurrence of skin cancer. And secondly, chemical carcinogens, and workers who are frequently contacted with arsenide, tar and asphalt are found to be easy to suffer from skin cancer through research. Third, ionizing radiation is a skin cancer that has been caused by radiation xerosis cutis due to neglect of preventive measures from radiologists for a long time. The causes of these various causes of skin cancer in patients are long-term exposure, rather than occasional brief exposure.
Therefore, how to reasonably manage the health condition of the skin and reduce the incidence rate of skin diseases is an urgent problem to be solved.
Disclosure of Invention
The application provides a hyperspectral-based detection early warning method, a hyperspectral-based detector and a hyperspectral-based detection early warning system, which are used for detecting the change state of skin and prompting and early warning the change state of the skin so as to avoid further damage to the skin and reduce the probability of skin diseases.
The application provides a hyperspectral based detection and early warning method in a first aspect, which comprises the following steps:
detecting the hyperspectral distribution of the surface of target skin to be detected to obtain current spectral distribution characteristic data;
comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, wherein a skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing high spectral information of the skin;
determining the spectral feature map change trend of the target skin according to the comparison result;
and if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, prompting and early warning.
Optionally, in some possible embodiments, before the detecting the hyperspectral distribution of the skin surface of the target to be detected to obtain the current spectral distribution characteristic data, the method may further include:
collecting spectral characteristic data of skin of each part under different health states;
and processing each spectral feature data in the same health state in the various spectral feature data to obtain the conventional spectral distribution feature data of the skin of each part in different health states.
Optionally, in some possible embodiments, the comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data to obtain a comparison result may include:
determining the conventional spectral distribution characteristic data corresponding to the target skin;
and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data, and determining the corresponding health state of the current spectral distribution characteristic data in the conventional spectral distribution characteristic data to obtain the comparison result.
Optionally, in some possible embodiments, the processing each spectral feature data in the same health state in the respective spectral feature data to obtain the conventional spectral distribution feature data of the skin of each part in different health states may include:
performing principal component analysis, linear discriminant analysis or lamp mapping on the spectral feature data in the same health state to obtain main features of the characteristic spectral features of the corresponding skin;
obtaining the conventional spectral distribution characteristic data of each skin under different health states according to the main characteristics
Alternatively, in some possible embodiments,
and if the current hyperspectral imaging quality is lower than a threshold value, an active illumination light source is turned on for illumination.
A second aspect of the present application provides a detector comprising:
the acquisition module is used for detecting the hyperspectral distribution of the surface of the target skin to be detected so as to obtain current spectral distribution characteristic data;
the analysis module is used for comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, the skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing skin hyperspectral information;
the determining module is used for determining the spectral feature map change trend of the target skin according to the comparison result;
and the early warning module is used for prompting early warning if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin.
Alternatively, in some possible embodiments,
the acquisition module is further used for acquiring each spectral feature data of the skin of each part under different health states before the current spectral distribution feature data of the surface of the target skin are acquired;
the analysis module is further configured to process each spectral feature data in the spectral feature data under the same health state to obtain the conventional spectral distribution feature data of the skin at each location under different health states.
Optionally, in some possible embodiments, the analysis module is specifically configured to:
determining the conventional spectral distribution characteristic data corresponding to the target skin;
and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data, and determining the corresponding health state of the current spectral distribution characteristic data in the conventional spectral distribution characteristic data to obtain the comparison result.
Optionally, in some possible embodiments, the analysis module is specifically configured to:
performing principal component analysis, linear discriminant analysis or lamp mapping on the spectral feature data in the same health state to obtain main features of the characteristic spectral features of the corresponding skin;
and obtaining the conventional spectral distribution characteristic data of each skin in different health states according to the main characteristics.
Optionally, in some possible embodiments, the detector further comprises:
and the switch module is used for turning on the active illumination light source for illumination if the current hyperspectral imaging quality is lower than a threshold value.
A third aspect of the present application provides a detection system comprising: the device comprises a hyperspectral point detector, an active illumination light source and an online learning module;
the hyperspectral point detector is used for acquiring current spectral distribution characteristic data of the surface of target skin to be detected;
the online learning module is used for acquiring conventional spectral distribution characteristic data, skin parts corresponding to the conventional spectral distribution characteristic data correspond to the target skin, and the conventional spectral distribution characteristic data are obtained by acquiring, analyzing and summarizing high spectral information of the skin;
the hyperspectral point detector is also used for comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, and determining the spectral characteristic diagram change trend of the target skin according to the comparison result;
the hyperspectral point detector is also used for prompting and early warning if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin;
the active illumination light source is used for illuminating if the current hyperspectral imaging quality is lower than a threshold value.
A fourth aspect of the present application provides a detector, which includes a processor and a memory, where the processor executes a computer program stored in the memory to implement the hyperspectral-based detection early warning method.
A fifth aspect of the present application provides a readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the hyperspectral-based detection and early warning method as described in the foregoing embodiments of the first aspect.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
in the embodiment of the application, the current spectral distribution characteristic data of the target skin can be detected, the current spectral distribution characteristic data is compared with the conventional spectral distribution characteristic data to obtain a comparison result, and the spectral characteristic diagram change trend of the target skin is predicted according to the comparison result. If the predicted state of the target skin is determined to be a preset state by the change trend of the spectral feature map of the target skin, prompt and early warning can be carried out. Therefore, after the front spectral distribution characteristic data of the target skin is obtained through detection, the spectral characteristic diagram change trend of the target skin can be predicted, and prompt and early warning is carried out. Therefore, the change of the skin can be found in advance, so that the health condition of the skin of a user can be reasonably managed, the damage to the skin is reduced, and the incidence rate of skin diseases is reduced.
Drawings
FIG. 1 is a schematic view of one embodiment of a detection system provided herein;
FIG. 2 is a schematic flow chart of the detection method provided herein;
FIG. 3 is a schematic diagram of one embodiment of the assays provided herein;
FIG. 4 is a schematic illustration of current spectral distribution characterization data provided herein;
FIG. 5a is a schematic representation of conventional spectral distribution characterization data provided herein;
FIG. 5b is another schematic of conventional spectral distribution characterization data provided herein;
FIG. 6a is a schematic representation of the current spectral distribution profile provided herein;
FIG. 6b is a schematic illustration of predicted spectral distribution characteristic data provided herein;
FIG. 7 is a schematic view of one embodiment of a detector provided herein;
FIG. 8 is a schematic view of another embodiment of a detector provided herein;
fig. 9 is a schematic diagram of an embodiment of a storage medium provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
It is to be understood that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the invention and the above-described drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
The application provides a hyperspectral-based detection and early warning method, a hyperspectral-based detector and a hyperspectral-based detection and early warning system, which are used for detecting the change state of skin and prompting and early warning the change state of the skin so as to avoid further damage to the skin and reduce the probability of skin diseases. The hyperspectral detection early warning method comprises the following steps: acquiring current spectral distribution characteristic data of the surface of target skin to be detected; comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, wherein a skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing high spectral information of the skin; determining the spectral feature map change trend of the target skin according to the comparison result; and if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, prompting and early warning. Therefore, the skin can be detected, the health state of the skin is predicted according to the spectral distribution characteristic diagram obtained by detection, and prompt early warning is carried out, so that a user can avoid damage to the skin according to the prompt early warning, and the disease probability of skin cancer is reduced.
When the skin of a human body is injured towards the outside, a layer of protective barrier is formed to protect the skin from irreversible injury within a period of time. However, over time, the protective properties of the protective barrier may diminish or even disappear. The dermal layer of the skin will be damaged, resulting in the transmission of skin cancer. Therefore, the hyperspectral detection and early warning method is used for detecting the health state of the skin epidermis, the hyperspectral identification capability of the hyperspectral technology on different substances is utilized, the skin spectra in different states are recorded, the skin health state and the tolerance capability of a human body at the moment are predicted according to the current spectral characteristics of the skin of the human body, and prompt and early warning are carried out. The technical solutions of the present application are described in detail below by way of the drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and the examples of the present application may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic diagram of an information control system according to an embodiment.
As shown in fig. 1, the information control system may include: a hyperspectral point detector 11, an active illumination source 12 and an online learning module 13. It should be noted that the information control system shown in fig. 1 may include, but is not limited to, the components shown in fig. 1, and may also include other components, such as a power supply device.
The hyperspectral point detector 11 is used for detecting hyperspectral distribution of the skin surface of a target to be detected so as to obtain current spectral distribution characteristic data; comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data to obtain a comparison result, and determining the spectral characteristic diagram change trend of the target skin according to the comparison result; and the hyperspectral point detector is also used for prompting and early warning if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin.
It should be understood that the manner of prompting the warning may be various, for example, sending a prompt message to a terminal device connected to the user, playing a prompt sound, displaying a prompt text, and the like, and the details are not limited herein.
The online learning module 12 is configured to store spectral characteristics of the skin in different health states, including the above conventional spectral distribution characteristic data, where a skin portion corresponding to the conventional spectral distribution characteristic data corresponds to a target skin, and the conventional spectral distribution characteristic data is obtained by collecting, analyzing, and summarizing hyperspectral information of the skin. Specifically, the spectral features of different health states stored in the online learning module 12 can be obtained from a large amount of experimental data, and high spectral point detection is performed on the skin of different health states, so that the stored spectral features have robustness, and a large amount of detected data can be processed. In addition, when the online learning module 12 is connected to the internet, a large amount of data can be acquired through the internet to update the stored spectral characteristics of the skin under different health states, so that the judgment of the hyperspectral point detector 11 is more accurate.
And the active illumination light source 13 is used for illuminating if the current hyperspectral imaging quality is lower than a threshold value so as to improve the hyperspectral imaging quality. The hyperspectral imaging quality can be determined based on the detected current spectral distribution characteristic data. Illustratively, the hyperspectral imaging quality can be measured by detecting noise in the current spectral distribution characteristic data, and the higher the noise is, the lower the hyperspectral imaging quality is. Further, the hyperspectral imaging quality may be measured by a maximum value of noise, an average value of noise, a noise amount, and the like, and correspondingly, the hyperspectral imaging quality may be considered to be lower than a threshold when one of the terms is higher than the threshold, for example, when one of the maximum value of noise is higher than a first threshold, the average value of noise is higher than a second threshold, the noise amount is larger than a third threshold, and the like is satisfied. At this time, the active illumination light source 13 may be turned on to illuminate, so as to improve the hyperspectral imaging quality.
The active lighting source 13 provides a good light source environment for the high spectrum point detector, so that the high spectrum point detector can work under different natural light environments. May be illumination or the like, or may be Near Infrared (NIR) light source or the like. The NIR light source has strong penetrating power, and when the NIR light source is used for light supplement, unique spectral characteristics can be detected for different tissues and skins in different states.
Referring to fig. 2, fig. 2 is a schematic flow chart of a hyperspectral-based detection and early warning method according to an embodiment of the present disclosure. As shown in fig. 2, the hyperspectral-based detection and early warning method may include the following steps:
201. and collecting spectral characteristic data of the skin of each part under different health states.
Before the skin is subjected to hyperspectral detection, spectral characteristic data of the skin of each part under different health states are collected firstly.
The spectral characteristic data of the skin of each part under different health states can be historical data collected by a hyperspectral point detector or can be obtained from a database in the Internet.
202. And analyzing the spectral characteristic data to obtain the conventional spectral distribution characteristic data of the skin of each part under different health states.
And analyzing the spectral characteristic data of the skin of each part under different health states to obtain the conventional spectral distribution characteristic data of the skin of each part under different states.
It can be understood that the data of the skin of each part under different health states is analyzed to obtain the spectrum distribution rule of the skin of each part under different health states, and then the health state of the skin can be determined according to the spectrum distribution rule.
Specifically, a large amount of detected spectral distribution characteristic data may be processed, for example, spectral characteristic maps in the same health state are fused to obtain final spectral characteristics, or spectral characteristics in the same health state are subjected to linear discriminant analysis, equidistant mapping, and the like to obtain main characteristics characterizing the spectral characteristics, and then the final spectral characteristic map is given according to the principal components to determine the spectral characteristics that most reflect one state in the large amount of spectral characteristic maps. In different environments, the spectral characteristic diagram of the skin detected within a period of time is recorded, the change trend of the spectral characteristic diagram of the skin in the current environment is summarized, and a relation between the time and the spectral trend change is fitted according to the trend and the known edge spectral characteristic diagram, so that the time within which the skin state of the human body reaches the dangerous edge is predicted.
It should be noted that the foregoing steps 201 and 202 are optional steps.
It should be further noted that, in the embodiment of the present application, the spectral feature data may be collected by the hyperspectral point detector 11 in fig. 1, and the conventional spectral distribution feature data of the skin of each part under different health conditions may be stored in the online learning module 12 in fig. 1, or may be directly stored in the memory of the hyperspectral point detector 11, and may be specifically adjusted according to an actual application scenario, which is not limited herein.
203. And detecting the hyperspectral distribution of the surface of the target skin to be detected to obtain the current spectral distribution characteristic data.
Detecting the hyperspectral distribution of the surface of target skin to be detected, and collecting the hyperspectrum of the surface of the target skin to obtain current spectral distribution characteristic data corresponding to the target skin.
The detection process is as shown in fig. 3, the target skin is detected by the high spectrum point detector, and the current spectral distribution characteristic data of the target skin is acquired.
Illustratively, the obtained current spectral distribution characteristic data may be as shown in fig. 4.
204. And comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data to obtain a comparison result.
And determining conventional spectral distribution characteristic data corresponding to the target skin, and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data to determine the current state of the target skin.
Illustratively, if the skin state is divided into three healthy state ranges including a dangerous state, an edge state and a healthy state, the current state of the target skin is determined according to the range of the current spectral distribution characteristic data.
205. And determining the spectral feature map change trend of the target skin according to the comparison result.
And after the comparison result is obtained, predicting the change trend of the spectral feature map of the target skin according to the comparison result. For example, if the target skin is currently in a healthy state, it is predicted that the target skin will be in an edge state after a period of time according to the current spectral distribution characteristic data of the target skin.
Illustratively, the trend of the skin spectral feature map in the conventional spectral distribution feature data is first determined, as shown in fig. 5a and 5 b. Fig. 5a is a spectrum characteristic diagram of original skin, and fig. 5b is a spectrum characteristic diagram of skin after a preset time length, so that the change trend of the skin from the spectrum characteristic diagram of the original skin can be obtained. Then, after the current spectral distribution characteristic data of the target skin is obtained, the spectral characteristic diagram change trend of the target skin is predicted according to the rule summarized in the conventional spectral distribution characteristic data, and the spectral characteristic diagram change trend of the target skin is obtained. As shown in fig. 6a and 6b, fig. 6a is current spectral distribution characteristic data of the target skin, and the spectral distribution characteristic data of the target skin after a preset time duration is predicted according to a rule in the conventional spectral distribution characteristic data to obtain the spectral distribution characteristic data in fig. 6 a.
206. And judging whether the predicted state of the target skin is a preset state or not according to the change trend of the spectral feature map of the target skin, if so, executing step 207, and if not, executing step 208.
And if the predicted state of the target skin is the preset state after the preset time period according to the spectral characteristic change trend of the target skin, executing step 207 and prompting and early warning. If the predicted state of the target skin is not the preset state after the preset time period, step 208, i.e., other steps, may be performed.
For example, if the target skin is predicted to be in a dangerous state for 1 hour according to the variation trend of the spectral feature map of the target skin, step 207 of prompting an early warning may be performed.
207. And prompting and early warning.
After the predicted state of the target skin is judged to be a preset state according to the spectral feature map change trend of the target skin, a prompt early warning can be performed, and the prompt early warning can be performed in various ways, for example, an alarm prompt tone can be played, early warning prompt information can be sent to a terminal device of a user to prompt the user to avoid damage to the skin, and the like.
For example, the current damage component of the skin can be analyzed, for example, whether the target skin is in high-intensity sunlight or in a radioactive environment, and then corresponding prompt and early warning can be performed according to different environments.
Taking a specific application scenario as an example, in recent years, people want to go outdoors to carry out entertainment activities more than to stay indoors, but people inevitably come into contact with sunlight when carrying out outdoor activities. For some outdoor activities with high sunlight irradiation, such as sea surfing, sunbathing, field hiking and the like, people are exposed to ultraviolet irradiation for a long time, the skin is very likely to be damaged, and the skin state is not spectral according to the feeling of the human body. Under the condition, through the technical scheme provided by the application, people can sense the health state of the skin of people in real time and learn the longest duration of the people staying in the current environment, so that the activity area and duration of the people are better controlled, and the skin is not damaged.
In another specific application scenario, for industries needing to be exposed to physical radiation or chemical carcinogens for a long time, practitioners cannot know the health state of skin of the practitioners, enterprises cannot make safety guarantee for employees, and establishment of trust of the two parties is not facilitated. In the industries, the technical scheme provided by the application can remind a practitioner of the skin state in real time, and the working efficiency is improved within limited working time. For enterprises, the enterprises can make the shift system of the employees according to the duration prompt of the equipment, so that the worry of the employees on health is effectively relieved, and the working progress of the enterprises is not influenced. In addition, different carcinogenic substance is different with the severity of carcinogenesis when carcinogenesis, if adopt same kind of early warning mode deviation probably to appear, consequently in physics, in the detection of chemistry carcinogenic substance, can be according to the spectral feature that detects in the environment, at first confirm the carcinogenic substance in the environment, then to the physics or chemical injury environment that carcinogenic capacity is strong, open early warning mechanism in advance, in the first half hour that appears danger (this time can be set up by the user by oneself) early warning immediately, and set for different early warning performances according to carcinogenic substance's strong degree, like sharp-pointed chimes of doom etc. thereby reach the better protective effect to the user.
208. Other steps are performed.
After the predicted state of the target skin is judged not to be the preset state according to the change trend of the spectral feature map of the target skin, no prompt and early warning can be carried out. Or, according to the spectral feature map change trend of the target skin, determining that the target skin is about to be in a dangerous state after the time length T, then, performing voice prompt to prompt that the target skin is about to be in the dangerous state after the time length T, or sending prompt information to a terminal device of a user to prompt that the target skin is about to be in the dangerous state after the time length T, and informing the user to take evasive measures in advance.
In the embodiment of the application, the current spectral distribution characteristic data of the target skin can be detected, the current spectral distribution characteristic data is compared with the conventional spectral distribution characteristic data to obtain a comparison result, and the spectral characteristic diagram change trend of the target skin is predicted according to the comparison result. If the predicted state of the target skin is determined to be a preset state by the change trend of the spectral feature map of the target skin, prompt and early warning can be carried out. The method can be understood as summarizing the spectral feature distribution of the skin at different parts according to a large amount of detected spectral distribution feature data, finding out the change rule of the spectral distribution feature, predicting the change trend of the spectral feature diagram of the target skin according to the change rule, and prompting and early warning to avoid the damage to the skin of a user. Therefore, the embodiment of the application can find the change of the skin in advance, so that the health condition of the skin of a user can be reasonably managed, the damage to the skin is reduced, and the incidence rate of skin diseases is reduced.
The foregoing describes in detail a specific process of the system and method provided in the embodiments of the present application, and the following describes the apparatus provided in the embodiments of the present application. Referring to fig. 7, a schematic diagram of an embodiment of a detector according to the present application may include:
the acquisition module 701 is used for detecting the hyperspectral distribution of the surface of the target skin to be detected to obtain current spectral distribution characteristic data;
an analysis module 702, configured to compare the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, where a skin portion corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by collecting and analyzing and summarizing skin hyperspectral information;
a determining module 703, configured to determine a variation trend of the spectral feature map of the target skin according to the comparison result;
and the early warning module 704 is configured to prompt and early warn if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin.
Alternatively, in some possible embodiments,
the acquisition module 701 is further configured to acquire each spectral feature data of the skin of each site in different health states before the current spectral distribution feature data of the surface of the target skin is acquired;
the analysis module is further configured to process each spectral feature data in the spectral feature data under the same health state to obtain the conventional spectral distribution feature data of the skin at each location under different health states.
Optionally, in some possible embodiments, the analysis module 702 is specifically configured to:
determining the conventional spectral distribution characteristic data corresponding to the target skin;
and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data, and determining the corresponding health state of the current spectral distribution characteristic data in the conventional spectral distribution characteristic data to obtain the comparison result.
Optionally, in some possible embodiments, the analysis module 702 is specifically configured to:
performing principal component analysis, linear discriminant analysis or lamp mapping on the spectral feature data in the same health state to obtain main features of the characteristic spectral features of the corresponding skin;
and obtaining the conventional spectral distribution characteristic data of each skin in different health states according to the main characteristics.
Optionally, in some possible embodiments, the detector may further include:
the switching module 705 is configured to turn on the active illumination light source for illumination if the current hyperspectral imaging quality is lower than a threshold.
An embodiment of the present application further provides a detector, including: a processor, a memory and a computer program stored in the memory and operable on the processor, as shown in fig. 8, for example, a program corresponding to the method for skin detection in the embodiment of the present application in fig. 2. The processor, when executing the computer program, implements the steps of the method for skin detection in the above embodiments. Alternatively, the processor implements the functions of the modules/units in the detector of the above embodiments when executing the computer program.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments describing the execution of the computer program in the computer apparatus.
The server may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that the illustrations are merely examples of a computer apparatus and are not meant to be limiting as a server may include more or less components than those shown, or some components may be combined, or different components, e.g., the server may also include input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like which is the control center for the computer device and which connects the various parts of the overall computer device using various interfaces and lines.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the computer apparatus by executing or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, video data, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Embodiments of the present application also provide a computer readable storage medium, on which a computer program is stored, as shown in fig. 9, where the detector integrated functional unit described in fig. 2 of the present application can be stored in a computer readable storage medium if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method for skin detection described above may also be implemented by a computer program, which may be stored in a computer-readable storage medium and can implement the steps of the above-described method embodiments when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (8)
1. A hyperspectral detection early warning method is characterized by comprising the following steps:
detecting the hyperspectral distribution of the surface of target skin to be detected to obtain current spectral distribution characteristic data;
comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, wherein a skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing high spectral information of the skin;
determining the spectral feature map change trend of the target skin according to the comparison result; determining the spectral feature map change trend of the target skin according to the comparison result, wherein the determining comprises the following steps: according to the rule in the conventional spectral distribution characteristic data, predicting the spectral distribution characteristic data of the target skin after preset time to predict the spectral characteristic graph change trend of the target skin;
if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, prompting and early warning are carried out; wherein, if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, the method comprises the following steps: determining the predicted state of the target skin after a preset time period as a preset state according to the spectral characteristic variation trend of the target skin;
before the detecting the hyperspectral distribution of the surface of the target skin to be detected to obtain the current spectral distribution characteristic data, the method further comprises:
collecting spectral characteristic data of skin of each part under different health states;
and processing each spectral feature data in the same health state in the various spectral feature data to obtain the conventional spectral distribution feature data of the skin of each part in different health states.
2. The method of claim 1, wherein comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result comprises:
determining the conventional spectral distribution characteristic data corresponding to the target skin;
and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data, and determining the corresponding health state of the current spectral distribution characteristic data in the conventional spectral distribution characteristic data to obtain the comparison result.
3. The method according to claim 1 or 2, wherein the processing each spectral feature data in the same health state in the respective spectral feature data to obtain the conventional spectral distribution feature data of the skin of each part in different health states comprises:
performing principal component analysis or linear discriminant analysis on the spectral feature data in the same health state to obtain main features of the characteristic spectral features of the corresponding skin;
and obtaining the conventional spectral distribution characteristic data of the skin of each part under different health states according to the main characteristics.
4. The method according to any one of claims 1-2, wherein:
and if the hyperspectral imaging quality is lower than the threshold value, the active illumination light source is turned on for illumination.
5. A detector, comprising:
the acquisition module is used for detecting the hyperspectral distribution of the surface of the target skin to be detected so as to obtain current spectral distribution characteristic data; before acquiring current spectral distribution characteristic data of the surface of the target skin, acquiring various spectral characteristic data of the skin of each part under different health states;
the analysis module is used for comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, the skin part corresponding to the conventional spectral distribution characteristic data corresponds to the target skin, and the conventional spectral distribution characteristic data is obtained by acquiring, analyzing and summarizing skin hyperspectral information; processing each spectral feature data in the spectral feature data under the same health state to obtain the conventional spectral distribution feature data of the skin of each part under different health states;
the determining module is used for determining the spectral feature map change trend of the target skin according to the comparison result; determining the spectral feature map change trend of the target skin according to the comparison result, wherein the determining comprises the following steps: according to the rule in the conventional spectral distribution characteristic data, predicting the spectral distribution characteristic data of the target skin after preset time to predict the spectral characteristic graph change trend of the target skin;
the early warning module is used for prompting and early warning if the predicted state of the target skin is determined to be a preset state according to the spectral feature map change trend of the target skin; wherein, if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, the method comprises the following steps: and determining the predicted state of the target skin after a preset time period as a preset state according to the spectral characteristic change trend of the target skin.
6. The detector of claim 5, wherein the analysis module is specifically configured to:
determining the conventional spectral distribution characteristic data corresponding to the target skin;
and comparing the current spectral distribution characteristic data with the conventional spectral distribution characteristic data, and determining the corresponding health state of the current spectral distribution characteristic data in the conventional spectral distribution characteristic data to obtain the comparison result.
7. The detector according to claim 5 or 6, wherein the analysis module is specifically configured to:
performing principal component analysis or linear discriminant analysis on the spectral feature data under the same health state to obtain main features of the characteristic spectral features of the corresponding skin;
and obtaining the conventional spectral distribution characteristic data of the skin of each part under different health states according to the main characteristics.
8. A detection system, comprising: the system comprises a hyperspectral point detector, an active illumination light source and an online learning module;
the hyperspectral point detector is used for acquiring current spectral distribution characteristic data of the surface of target skin to be detected;
the online learning module is used for acquiring conventional spectral distribution characteristic data, skin parts corresponding to the conventional spectral distribution characteristic data correspond to the target skin, and the conventional spectral distribution characteristic data are obtained by acquiring, analyzing and summarizing high spectral information of the skin;
the hyperspectral point detector is also used for comparing the current spectral distribution characteristic data with conventional spectral distribution characteristic data to obtain a comparison result, and determining the spectral characteristic map change trend of the target skin according to the comparison result; determining the spectral feature map change trend of the target skin according to the comparison result, wherein the determining comprises the following steps: according to the rule in the conventional spectral distribution characteristic data, predicting the spectral distribution characteristic data of the target skin after preset time to predict the spectral characteristic graph change trend of the target skin;
the hyperspectral point detector is also used for prompting and early warning if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin; wherein, if the predicted state of the target skin is determined to be a preset state according to the change trend of the spectral feature map of the target skin, the method comprises the following steps: determining the predicted state of the target skin after a preset time period as a preset state according to the spectral characteristic variation trend of the target skin;
and the active illumination light source is used for illuminating if the current hyperspectral imaging quality is lower than a threshold value.
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| EP1921994A4 (en) * | 2005-08-16 | 2010-12-29 | Skin Cancer Scanning Ltd | Combined visual-optic and passive infra-red technologies and the corresponding system for detection and identification of skin cancer precursors, nevi and tumors for early diagnosis |
| WO2008103918A1 (en) * | 2007-02-22 | 2008-08-28 | Wisconsin Alumni Research Foundation | Hyperspectral imaging spectrometer for early detection of skin cancer |
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| US20150044098A1 (en) * | 2012-01-30 | 2015-02-12 | Scanadu Incorporated | Hyperspectral imaging systems, units, and methods |
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