CN115778317B - Skin testing methods, skin testing equipment, and storage media - Google Patents
Skin testing methods, skin testing equipment, and storage mediaInfo
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- CN115778317B CN115778317B CN202211395607.5A CN202211395607A CN115778317B CN 115778317 B CN115778317 B CN 115778317B CN 202211395607 A CN202211395607 A CN 202211395607A CN 115778317 B CN115778317 B CN 115778317B
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Abstract
The invention discloses a skin evaluation method, a skin evaluation device and a storage medium. The method comprises the steps of obtaining test sample data of a target evaluation dimension, determining a target corresponding relation between a measured value and a grading value according to the test sample data, and determining a skin grading value of a target object according to the target corresponding relation and the measured data of the target object corresponding to the target evaluation dimension. The invention aims to improve the accuracy of skin evaluation results.
Description
Technical Field
The present invention relates to the field of skin testing technologies, and in particular, to a skin evaluation method, a skin evaluation apparatus, and a storage medium.
Background
Skin management is becoming more and more popular in everyday life, as is the need for skin testing. At present, a spectrum imaging technology is generally applied to perform qualitative and quantitative analysis on indexes such as color plates, pores, running stability and smoothness of skin, and evaluation results with different dimensions are fed back to a user according to analysis results.
At present, when evaluating the skin of a user based on data of different dimensions, a plurality of fixed numerical intervals are generally preset through theoretical calculation, each numerical interval is correspondingly provided with a score, and the skin score is determined based on the numerical interval where the actual detection value of the target dimension is located, however, the evaluation result is easily mismatched with the actual situation of the user in such a way, so that the accuracy of the skin evaluation result of the user is insufficient.
Disclosure of Invention
The main object of the present invention is to provide a skin evaluation method, a skin evaluation apparatus and a storage medium, aiming at improving the accuracy of the skin evaluation result.
In order to achieve the above object, the present invention provides a skin evaluation method comprising the steps of:
Obtaining test sample data of a target evaluation dimension;
Determining a target corresponding relation between the measured value and the scoring value according to the test sample data;
and determining the skin grading value of the target object according to the target corresponding relation and the measurement data of the target object corresponding to the target evaluation dimension.
Optionally, the test sample data includes a plurality of test sample values, and the step of determining the target correspondence between the measured value and the scoring value according to the test sample data includes:
Determining a reference measurement value corresponding to a preset grading value according to the distribution characteristics of the plurality of test sample values;
and determining the target corresponding relation according to the preset grading value and the corresponding reference measured value.
Optionally, the step of determining the reference measurement value corresponding to the preset score value according to the distribution characteristics of the plurality of test samples includes:
determining a numerical value interval in which each test sample is located in a plurality of preset numerical value intervals, and counting the number of the test samples distributed in each preset numerical value interval;
determining the preset numerical value interval with the largest number as a target numerical value interval;
and determining the reference measured value according to the numerical value in the target numerical value interval.
Optionally, the step of determining the target correspondence according to the preset scoring value and the corresponding reference measurement value includes:
Dividing at least two measurement value intervals according to the reference measurement value;
determining a scoring value interval corresponding to each measuring value interval according to the corresponding relation between the reference measuring value and the preset scoring value;
and determining the corresponding relation between the measured value interval and the grading value interval as the target corresponding relation.
Optionally, the step of determining the target correspondence according to the preset scoring value and the corresponding reference measurement value includes:
Determining a target change trend of the grading value along with the change of the measured value according to a target correlation corresponding to the target evaluation dimension, wherein the target correlation comprises correlation between the size of the measured value and the represented skin quality degree;
And determining the target corresponding relation according to the target change trend, the preset grading value and the reference measured value.
Optionally, the number of the target evaluation dimensions is more than one, different target evaluation dimensions correspond to different target correspondence, and the step of determining the skin score value of the target object according to the target correspondence and the measurement data of the target object corresponding to the target evaluation dimensions includes:
determining corresponding sub-scores according to the target corresponding relation corresponding to each target evaluation dimension and the measurement data, and obtaining more than one sub-score;
The skin score value is determined from more than one of the sub-scores.
Optionally, the step of determining the skin score value from more than one of the sub-scores comprises:
And carrying out weighted average calculation on the more than one sub-score according to the weight value corresponding to each target evaluation dimension respectively to obtain the skin score value.
Optionally, the more than one target evaluation dimension includes a first type target evaluation dimension and a second type target evaluation dimension, a weight value corresponding to the first type target evaluation dimension is smaller than a weight value corresponding to the second type target evaluation dimension, and a probability that a measured value corresponding to the first type target evaluation dimension changes along with an environmental factor is greater than a probability that the second type target evaluation dimension changes along with the environmental factor.
Optionally, more than one of the target evaluation dimensions includes anti-aging, moisture content, melanin, oil content, and sensitivity.
In order to achieve the above object, the present application also proposes a skin evaluation device comprising a memory, a processor, and a skin evaluation program stored on the memory and executable on the processor, the skin evaluation program implementing the steps of the skin evaluation method according to any one of the above when executed by the processor.
In addition, in order to achieve the above object, the present application also proposes a storage medium having stored thereon a skin evaluation program which, when executed by a processor, implements the steps of the skin evaluation method as set forth in any one of the above.
According to the skin evaluation method, the target corresponding relation between the measured value and the grading value is established based on the test sample data of the target evaluation dimension, the skin grading value of the target object is determined based on the target corresponding relation and the measured data of the target object corresponding to the target evaluation dimension, the target corresponding relation is the corresponding relation between the measured value and the grading value obtained through analysis according to the actual test sample data of the target evaluation dimension, the skin of the user is graded, the fit of the actual situation of the user is facilitated, the fact that the grading is carried out based on the corresponding relation obtained through theoretical calculation to enable the actual state of the user to be different is avoided, and the accuracy of the skin evaluation result is effectively improved.
Drawings
FIG. 1 is a schematic diagram of the hardware architecture involved in the operation of an embodiment of the skin evaluation device of the present invention;
FIG. 2 is a flow chart of an embodiment of a skin evaluation method according to the present invention;
FIG. 3 is a flow chart of another embodiment of the skin evaluation method of the present invention;
FIG. 4 is a flow chart of a skin evaluation method according to another embodiment of the present invention;
Fig. 5 is a flowchart of a skin evaluation method according to another embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the invention provides skin evaluation equipment. In the present embodiment, the skin evaluation device is a server of an application installed in the android system. In other embodiments, the skin evaluation device may also be a detection device with a separate test function.
In an embodiment of the present invention, referring to fig. 1, the skin evaluation device includes a processor 1001 (e.g., CPU), a memory 1002, a timer 1003, and the like. The components in the control device are connected through a communication bus. The memory 1002 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1002 may alternatively be a storage device separate from the processor 1001 described above.
Specifically, the skin evaluation device can be in communication connection with the skin tester or is internally provided with the skin tester, and can acquire detection data of different skin indexes tested by the skin tester.
It will be appreciated by those skilled in the art that the device structure shown in fig. 1 is not limiting of the device and may include more or fewer components than shown, or may be combined with certain components, or a different arrangement of components.
As shown in fig. 1, a skin evaluation program may be included in a memory 1002 as a storage medium. In the apparatus shown in fig. 1, a processor 1001 may be used to call a skin evaluation program stored in a memory 1002 and perform the relevant step operations of the skin evaluation method in the following embodiments.
The embodiment of the invention also provides a skin evaluation method which is applied to the skin evaluation equipment.
Referring to fig. 2, an embodiment of a skin evaluation method according to the present application is provided. In this embodiment, the skin evaluation method includes:
step S10, test sample data of a target evaluation dimension is obtained;
The test sample data specifically includes a plurality of test results of the user in the target evaluation dimension, which are collected before the current time, wherein the plurality of test results may include a plurality of test results of the target object before the current time and/or a plurality of test results of objects other than the target object at the current time.
The target evaluation dimension is specifically an evaluation item for evaluating the skin quality of the target object. The number of target evaluation dimensions may be one or more than one. The target evaluation dimension may be a fixed parameter set in advance, or may be a parameter determined according to a user-set parameter.
The target evaluation dimension may be anti-aging, moisture content, melanin, oil content, sensitivity, or the like. In this embodiment, the number of target evaluation dimensions is more than one, more than one of which includes anti-aging, moisture content, melanin, oil content, and sensitivity. Or more than one of the target evaluation dimensions may include a portion of anti-aging, moisture content, melanin, oil content, and sensitivity.
Step S20, determining a target corresponding relation between the measured value and the grading value according to the test sample data;
The target correspondence may include a mapping relationship, a calculation formula, and the like. Specifically, a calculation formula between the measured value and the score value may be determined according to the test sample data, for example, a mathematical relationship model with unknown model parameters between the measured value and the score value may be established in advance, the model parameters may be determined according to the data analysis result of the test sample data, and a number relationship model with known model parameters may be used as the calculation formula between the measured value and the score value to obtain the target corresponding relationship. For another example, a plurality of preset measurement value intervals and score intervals corresponding to each preset measurement value interval may be preset, according to distribution characteristics of the test sample data in the plurality of preset measurement value intervals (for example, the number or the average value of the test samples in different preset measurement value intervals, etc.), the corresponding score intervals are adjusted according to the distribution characteristics, and the adjusted plurality of preset measurement value intervals and the corresponding score intervals are used as the target corresponding relationship.
When the number of the target evaluation dimensions is more than one, the corresponding target corresponding relation can be determined according to the test sample data corresponding to each target evaluation dimension, and each target price dimension corresponds to at least one target corresponding relation.
And step S30, determining the skin grading value of the target object according to the target corresponding relation and the measurement data of the target object corresponding to the target evaluation dimension.
The measurement data is a test value of a target evaluation dimension obtained by testing the skin of the target object at present.
The target object is an object that is currently in need of skin testing. In this embodiment, the target object is a user. In other embodiments, the target subject may be any subject that is tested by the skin tester according to a preset skin test rule, such as an animal.
And determining the corresponding grading value of the measurement data in the target corresponding relation as a reference grading value, and directly taking the reference grading value as a skin grading value.
When the target evaluation dimension is more than one, the score value of the measurement data of each target evaluation dimension in the corresponding target corresponding relation can be respectively determined as the reference score value, more than one reference score value is obtained, and the skin score value can be calculated according to the more than one reference score value.
According to the skin evaluation method provided by the embodiment of the invention, the target corresponding relation between the measured value and the grading value is established based on the test sample data of the target evaluation dimension, the skin grading value of the target object is determined based on the target corresponding relation and the measured data of the target object corresponding to the target evaluation dimension, the target corresponding relation is the corresponding relation between the measured value and the grading value obtained by analyzing the actual test sample data of the target evaluation dimension, the skin of the user is graded, the fit of the actual situation of the user is facilitated, the fact that the grading is carried out based on the corresponding relation obtained by theoretical calculation so as to be inconsistent with the actual state of the user can be avoided, and the accuracy of the skin evaluation result is effectively improved.
Further, based on the above embodiment, another embodiment of the skin evaluation method of the present application is proposed. In this embodiment, the test sample data includes a plurality of test sample values, where each test sample value is a test result value of a corresponding user in the target evaluation dimension before the current time. Referring to fig. 3, the step S20 includes:
step S21, determining a reference measurement value corresponding to a preset scoring value according to the distribution characteristics of the plurality of test sample values;
Specifically, the collected plurality of test sample values may be imported into a hash map, distribution characteristics (such as sample density, mean value or standard deviation in different data intervals) of the plurality of test sample values may be determined by analyzing distribution of values in the hash map and a point cluster of data points, and a measurement value corresponding to a preset grading value may be determined as a reference measurement value based on the distribution characteristics.
The preset score value may be a score value determined according to the skin test needs of the user. And if the preset grading values are different, the corresponding reference measured values are different. Specifically, the target condition of the distribution characteristics of the corresponding plurality of test samples may be determined according to the preset score value, and the reference measurement value may be determined according to the set of test sample values satisfying the target condition.
The predetermined scoring value may be one or more, and the corresponding reference measurement value may be one or more.
In this embodiment, the preset score value is one, the reference measurement value is a value in a value interval with the largest distribution density in the plurality of test samples, and the preset score value is a preset pass score (for example, 60 score).
In other embodiments, the number of the preset score values may be more than one, the number of the reference measurement values may be more than one, specifically, different preset score values may correspond to different preset distribution densities, the distribution densities of the plurality of test samples in different numerical intervals are determined, and the numerical value in the numerical interval in which the deviation between the distribution density and the preset distribution density corresponding to the preset score value is the smallest is taken as the reference measurement value corresponding to the preset score value, based on which more than one reference measurement value may be obtained.
And S22, determining the target corresponding relation according to the preset grading value and the reference measured value.
Specifically, a corresponding score value and a second quantitative relation (such as a difference value or a ratio value, etc.) between the preset score value and the corresponding score value are determined according to a first quantitative relation (such as a difference value or a ratio value, etc.) between a plurality of target measured values and the reference measured value, a target score value corresponding to each target measured value is determined according to each second quantitative relation and the preset score value, a target correspondence is determined according to a plurality of correspondence between the target measured values and the target score values, specifically, at least two measured value intervals can be divided by a plurality of target measured values, and a score value interval corresponding to each measured value interval is determined according to a plurality of correspondence between the target measured values and the target score values as a target correspondence. And a calculation formula between the measured value and the grading value can be obtained by fitting a plurality of corresponding relations between the target measured value and the target grading value as a target corresponding relation.
In this embodiment, the distribution features of the plurality of test sample values are used to determine the reference measurement value corresponding to the preset score value, and then the corresponding relationship between the score value and the measurement value is established based on the preset score value and the corresponding reference measurement value, where the preset score value can be used as the skin evaluation requirement characterization, the distribution features of the plurality of test sample values can accurately analyze the measurement value whose evaluation meets the preset score value as the reference measurement value, and the corresponding relationship between the reference measurement value and the preset score value is established based on the corresponding relationship between the reference measurement value and the preset score value, so as to ensure that the evaluation score of the target evaluation dimension output based on the corresponding relationship can be accurately matched with the output test requirement, and further improve the user experience of the skin evaluation process.
Further, in this embodiment, step S21 includes determining a value interval in which each of the test samples is located in a plurality of preset value intervals, counting the number of the test samples distributed in each of the preset value intervals, determining the preset value interval with the largest number as a target value interval, and determining the reference measurement value according to the values in the target value interval.
Specifically, the collected plurality of test sample values may be imported into a hash map, a plurality of preset value intervals may be identified on the hash map, and the preset value interval in which the plurality of test sample values are most dense may be determined as the target value interval by analyzing the distribution of the values in the hash map and the point clusters of the data points. In the present embodiment, the median value of the target numerical value section is taken as the reference measurement value. In other embodiments, the threshold value of the target value interval or any value within the interval may be used as the reference measurement value.
In this embodiment, the reference measurement value is determined in the numerical interval with the most densely distributed samples, which is favorable for ensuring that the evaluation score obtained by most of the user measurements can be controlled near the preset score value, and avoiding that the obtained score value cannot accurately reflect the actual skin quality due to the excessively large deviation between the actual measurement value of the target object and the average condition of most of the groups, thereby being favorable for improving the accuracy of the determined skin evaluation result and improving the user experience.
Further, in this embodiment, the preset score value is greater than or equal to 50% of the preset highest score, which is favorable for most users to have skin evaluation results not too low, and further improves user skin evaluation experience.
Further, in this embodiment, step S22 includes dividing at least two measurement value intervals according to the reference measurement value, determining a score value interval corresponding to each measurement value interval according to a correspondence between the reference measurement value and the preset score value, and determining a correspondence between the measurement value interval and the score value interval as the target correspondence.
Specifically, at least two measurement value intervals can be divided by taking a reference measurement value as an interval critical value, or the reference measurement value can be taken as the median value of one of the measurement value intervals and divided into a plurality of measurement value intervals according to preset interval amplitude (the deviation between the maximum value and the minimum value of the preset interval), wherein the interval amplitude of each measurement value interval is the preset interval amplitude, and the median value of one of the measurement value intervals is the reference measurement value.
When the number of the reference measurement values is one, the set of test values greater than or equal to the reference measurement values may be divided into a first measurement value interval, and the set of test values less than the reference measurement values may be divided into a second measurement value interval. Or one or more than one reference measurement value can be determined according to the reference measurement value and the preset interval, the more than one reference measurement value can be all greater than the reference measurement value, can be all less than the reference measurement value, can be all greater than the reference measurement value and be all less than the reference measurement value, the reference measurement value and all the reference measurement value are orderly sequenced to obtain a target sequence, and a numerical value set between any two adjacent measurement values in the target sequence is divided into a measurement value interval to obtain at least two measurement value intervals.
When the number of the reference measured values is more than one, the more than one measured values can be sequentially sequenced to obtain a target sequence, and a numerical value set between any two adjacent measured values in the target sequence is divided into a measured value interval to obtain at least two measured value intervals.
Specifically, one or all values of each measurement value interval may be determined as a target measurement value, a first quantitative relation (e.g., a difference value or a ratio value, etc.) between the internal target measurement value and the reference measurement value may be determined, a second quantitative relation (e.g., a difference value or a ratio value, etc.) between a target score value corresponding to each target measurement value and a preset score value may be determined according to the first quantitative relation, and a target score value corresponding to each target measurement value may be determined according to the second quantitative relation and the preset score value. And determining the target corresponding relation according to the corresponding relation between the target measured value and the target grading value.
And the values in all the measurement intervals can be used as target measurement values, and the corresponding relation between the target measurement values and the target grading values can be directly used as target corresponding relation.
The target measurement value may be a critical value of the measurement value interval, and the multiple target score value may be divided into multiple score value intervals based on the multiple target score values, and the corresponding relationship between the measurement value interval and the score value interval may be determined as the target corresponding relationship based on the corresponding relationship between the target measurement value and the target score value
In this embodiment, the measured value intervals are divided and the corresponding score value intervals are determined in the above manner, and different score value intervals can represent different score levels, so that when a subsequent skin test is performed based on the target corresponding relationship, it is beneficial to determine that the measured value interval where the measured data is located can know the score level of the user, to reduce the influence of the detection error on the deviation of the skin output result, and to improve the user experience.
Further, based on any one of the above embodiments, a further embodiment of the skin evaluation method of the present application is provided. In this embodiment, referring to fig. 4, the step S22 includes:
step S221, determining a target change trend of the grading value along with the change of the measured value according to a target correlation corresponding to the target evaluation dimension, wherein the target correlation comprises correlation between the size of the measured value and the represented skin quality degree;
the target correlation relations corresponding to different target evaluation dimensions are different, and specifically, the target correlation relations can be set according to characterization definitions of measurement values of the different target evaluation dimensions. For example, the higher the moisture content, the better the skin, the lower the moisture content, and the worse the skin, and, for example, the higher the melanin value, the worse the skin, the lower the melanin value, and so on, the more negative the melanin size is in negative correlation with the skin quality.
Wherein, the skin quality degree and the grading value are positively correlated, the better the skin quality is, the higher the grading value is, and the worse the skin quality is, the lower the grading value is.
Specifically, when the target correlation is a positive correlation, the target variation tendency includes an increase in the score value with an increase in the measured value and a decrease in the score value with a decrease in the measured value, and when the target correlation is a negative correlation, the target variation tendency includes a decrease in the score value with an increase in the measured value and an increase in the score value with a decrease in the measured value.
For example, the correlation of the measured values corresponding to different target evaluation dimensions with the skin quality level is shown in the following table:
| Dimension(s) | Value range | Numerical definition |
| Attenuation resistance | 0~100 | Weak (0-40) normal (41-70) strong (71-100) |
| Moisture content | 0~100 | Lack (0-50) moderate (51-80) full (81-100) |
| Melanin pigment | 0~100 | Less (0-20) normal (21-80) weight (81-100) |
| Oil component | 0~5 | Lack (0 to 2) moderate (3) excess (4 to 5) |
| Sensitivity to | 0~100 | Health (0 to 30) is slight (31 to 75) and serious (76 to 100) |
Step S222, determining the target correspondence according to the target variation trend, the preset score value and the reference measurement value.
Specifically, the second quantitative relationship may be determined according to the target variation trend and the first quantitative relationship.
And matching the change trend of the scoring value along with the measured value in the determined target corresponding relation with the target change trend.
When the target change trend is that the score value increases with the increase of the measured value and the score value decreases with the decrease of the measured value, the score value corresponding to the measured value is smaller than the preset score value when the measured value is smaller than the reference measured value and the score value corresponding to the measured value is larger than the preset score value when the measured value is larger than the reference measured value, and when the target change trend is that the target change trend comprises that the score value decreases with the increase of the measured value and the score value increases with the decrease of the measured value, the score value corresponding to the measured value is larger than the preset score value when the measured value is smaller than the reference measured value and the score value corresponding to the measured value is smaller than the preset score value when the measured value is larger than the reference measured value.
In this embodiment, by the above manner, accuracy of the skin evaluation result of the target object with respect to the target evaluation dimension is facilitated to be improved.
In order to better understand the process of establishing the target correspondence in the skin evaluation method according to the embodiment of the present invention, the following description is given by way of a specific example:
Specifically, taking the water content as an example, the water content value is positively correlated with the skin quality, the water content value of most people in the hash chart is in the interval of [20,70], wherein the water content value is most dense near 40 points, so that 40 (namely the reference measured value) is basically the most average value of 60 minutes (namely the preset grading value), the grading value corresponding to the boundary measured value interval [0,40] is increased from 0 to 60 minutes according to the equal ratio, the measured value interval [41,80] also belongs to the dense area above the average value, the corresponding grading value is increased from 60 to 80 minutes according to the equal ratio, the occurrence probability of the measured value interval [81,100] is smaller, the corresponding grading value is increased from 80 to 100 minutes according to the equal ratio, and the grading value ranges corresponding to different measured value intervals can be obtained as the target corresponding relation based on the grading value ranges.
Further, based on any one of the above embodiments, another embodiment of the skin evaluation method of the present application is provided. In this embodiment, referring to fig. 5, the number of the target evaluation dimensions is more than one, different target evaluation dimensions correspond to different target correspondence, and the step of determining the skin score value of the target object according to the target correspondence and the measurement data of the target object corresponding to the target evaluation dimensions includes:
Step S31, corresponding sub-scores are determined according to the target corresponding relation corresponding to each target evaluation dimension and the measurement data, and more than one sub-score is obtained;
And step S32, determining the skin scoring value according to more than one sub-score.
In particular, the skin score value may be calculated from more than one sub-score.
In this embodiment, by the above manner, the target correspondence of different target evaluation dimensions is determined based on the corresponding actual test sample data, and the corresponding measurement data is subjected to skin evaluation based on the different target correspondence, which is favorable for improving the accuracy of the skin test results of different target evaluation dimensions, and the skin evaluation values of the target objects are determined by integrating more than one evaluation dimension, so that the overall skin condition of the target objects can be accurately reflected by the skin evaluation values, and the accuracy of the skin test results is further improved.
Further, in this embodiment, after the step S32, a skin score value may be output, and after the skin score value is output, if a demand instruction of a skin improvement suggestion is received, a target dimension to be improved in more than one target evaluation dimension may be determined according to more than one sub-score, and prompt information corresponding to the target dimension is output, so that a user is facilitated to locate and improve a skin problem of the user.
Further, in this embodiment, step S32 includes performing weighted average calculation on the more than one sub-score according to the weight value corresponding to each of the target evaluation dimensions, to obtain the skin score value.
In this embodiment, the weight values corresponding to different target evaluation dimensions are different. And the sum of all weight values corresponding to all target evaluation dimensions is 1.
For example, the sub-scores corresponding to the 5 dimensions of anti-aging, moisture content, melanin, oil content, and sensitivity are A, B, C, D, E in sequence, and the corresponding weight values are i, j, k, m, n in sequence, wherein (i+j+k+m+n=1) the skin score Q can be calculated according to the following formula that q=a+i+b+j+c+k+d+m+e.
In this embodiment, by the above manner, the skin evaluation value can more accurately reflect the overall skin condition of the user, which is beneficial to improving the accuracy of the skin evaluation result.
Further, in this embodiment, the more than one target evaluation dimension includes a first type target evaluation dimension and a second type target evaluation dimension, a weight value corresponding to the first type target evaluation dimension is smaller than a weight value corresponding to the second type target evaluation dimension, and a probability that a measured value corresponding to the first type target evaluation dimension changes with an environmental factor is greater than a probability that the second type target evaluation dimension changes with the environmental factor.
In the first target class evaluation dimension, the weight value corresponding to the target evaluation dimension with high probability of changing along with the environmental factors can be smaller than the weight value corresponding to the target evaluation dimension with low probability of changing along with the environmental factors.
For example, in the embodiment, measurement data is obtained through RGB and UV spectral imaging technology test, and among 5 evaluation dimensions of the anti-aging, the water content, the melanin, the oil content and the sensitivity, the anti-aging, the water content and the oil content are easily influenced by environmental factors and changed, the measurement data can be divided into a first class of target evaluation dimensions, the melanin and the sensitivity are not easily influenced by environmental factors and changed, the measurement data can be divided into a second class of target evaluation dimensions, and weight values corresponding to the anti-aging, the water content, the melanin, the oil content and the sensitivity are sequentially 15%, 30%, 10% and 30%.
In this embodiment, the weight values of different target evaluation dimensions are not fixed to the same weight, and some of the weight ratios of the dimensions of the external environment change result are easily reduced, so that the influence of environmental factors on the detection result is avoided, and the accuracy of the skin test result is further improved.
In other embodiments, priorities of different target evaluation dimensions set by the user may be obtained, and weight values corresponding to the target evaluation dimensions are determined successively according to the priorities.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium is stored with a skin evaluation program, and the skin evaluation program realizes the relevant steps of any embodiment of the skin evaluation method when being executed by a processor.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a skin evaluation device, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
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