A method and system for detecting scalp moisture profile

Abstract

The present application relates to a kind of detection method and system of scalp moisture distribution, the method comprises: S1, head skin is zoned, and the region center position is moisture content measurement point position;S2, using skin moisture content measuring instrument acquisition head skin all area moisture content data;S3, using 3D figure head model, head is zoned, and region position corresponds with the head skin region position divided in S1 step;S4, according to the moisture content data of different region, match different color RGB value;S5, color rendering is done to all zoned of figure head model;S6, generate different angle human scalp 3D moisture distribution color image;The present application realizes all-around measurement to scalp moisture, and it provides a more comprehensive and objective evaluation method for the efficacy evaluation of scalp moisturizing product;Meanwhile, invisible skin moisture is converted into visual 3D facial color imaging, and result is more comprehensive and intuitive.

Description

Technical Field

[0001] This invention relates to the field of human skin analysis technology, specifically a method and system for detecting scalp moisture distribution. Background Technology

[0002] The scalp, as part of the skin, is an important protective barrier for the human head. However, unlike the skin on other parts of the body, the scalp is covered with dense hair, making it more difficult and complex to test its moisture content compared to other parts of the body.

[0003] Currently available instruments for measuring skin moisture content mainly fall into the following categories:

[0004] Non-invasive contact skin moisture measurement instruments can be categorized into capacitance, resistance, and conductivity methods based on their operating principles. While these instruments achieve quantitative measurement of skin moisture content, they have the following limitations in practical applications: 1. Limited by the probe's contact area, these instruments can only test the moisture content of a very small area of ​​skin, and the results cannot represent the overall skin moisture status; 2. For the scalp, due to the dense hair covering its surface, most contact probes cannot directly measure it, requiring the removal of some hair for measurement. Although this reduces the influence of hair on the test results, the shaving process may cause compression or damage to the test area, which will also affect the test results; 3. The test results of these instruments are presented numerically, and cannot visually represent the distribution of skin moisture. For scalp moisture content testing, although some non-invasive contact measurement instruments have been optimized in design (using needle-like probes) to eliminate the influence of hair on the test, the results only represent the moisture content of the probe contact area and cannot represent the overall scalp moisture status; furthermore, they cannot provide a visual representation of scalp moisture.

[0005] Skin capacitive imaging instruments, which use fingerprint sensing technology, can display a map of moisture distribution and microstructure on the skin surface. However, the images presented by this instrument are only of a localized area of ​​skin (18×12.8mm). 2 The moisture distribution results obtained from the scalp test still cannot represent the overall skin moisture distribution. Furthermore, due to the influence of hair and the unique three-dimensional curved structure of the head, it is difficult for the scalp to make contact with the probe, making it impossible to measure scalp moisture.

[0006] In vivo Raman confocal microscopy is an instrument that determines the percentage of water content in different depths of the skin by measuring Raman spectra in living organisms. However, the measurement process of this type of instrument is very time-consuming, cannot test scalp moisture, is easily affected by interference, and is very expensive, so it is not used for routine measurement.

[0007] In summary, current technologies for scalp moisture detection cannot simultaneously meet the following user needs: 1. Measurement without shaving; 2. Demonstration of complete scalp moisture distribution; 3. Visual presentation of moisture content. Therefore, this invention proposes a method and system for detecting scalp moisture distribution. Summary of the Invention

[0008] To address the problems existing in the prior art, this invention proposes a method and system for detecting scalp moisture distribution, which can present a continuous and complete 3D color image of human scalp moisture distribution.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] A method for detecting scalp moisture distribution, the method comprising the following steps:

[0011] S1. Divide the scalp into sections, with the center of each section being the measurement point for moisture content.

[0012] S2. Collect moisture content data for all areas of the scalp using a skin moisture content measuring instrument;

[0013] S3. Using a 3D character head model, divide the head into sections, with each section corresponding to the section of the head skin area divided in step S1.

[0014] S4. Match different color RGB values ​​based on the moisture content data of different regions;

[0015] S5. Apply color rendering to all sections of the character's head model;

[0016] S6. Generate 3D color images of human scalp moisture distribution from different angles.

[0017] As a further technical solution of the present invention, in step S1, the scalp skin is divided into 15-27 partitions, denoted as Hk, where k is 1-v and v is 15-27.

[0018] As a further technical solution of the present invention, in step S1, the scalp skin is divided into 20-27 sections, denoted as Hk, where k takes the value 1-v and v takes the value 20-27.

[0019] Determine the center point location of any region within these partitions, corresponding to different points; optionally, they correspond to the following points:

[0020] Point 1 (Head midline, upper forehead, near hairline), Point 2 (Head midline, between points 1 and 3), Point 3 (Head midline, center of the top of the head), Point 4 (Head midline, between points 3 and 5), Point 5 (Head midline, center of the back of the head), Point 6 (Head midline, between points 5 and 7), Point 7 (Head midline, lower end of the back of the head), Point 8 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 1 and 2), Point 9 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 2 and 3), Point 10 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4). Point 11 (a line parallel to the center of the left eye, intersecting the horizontal line at the midpoint of points 4 and 5), Point 12 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 5 and 6), Point 13 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 6 and 7), Point 14 (left side of the head, between points 8 and 17, forming a slightly curved diagonal line with points 1, 8, and 17), Point 15 (left side of the head, between points 11 and 17, forming a slightly curved diagonal line with points 14 and 16), Point 16 (left side of the head, between points 13 and 17, forming a line connecting points 3, 10, and 15), Point 17 (left side of the head, forming a line connecting points 3, 10, and 15).Point 18 (a slightly curved diagonal line forming with points 13 and 17), point 19 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 1 and 2), point 20 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 2 and 3), point 21 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 4 and 5), point 22 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 5 and 6). Point 6 (intersecting the horizontal line at the midpoint of point 6), Point 23 (right side of the head, a line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal lines at the midpoints of points 6 and 7), Point 24 (right side of the head, located between points 18 and 27, forming a slightly curved diagonal line with points 1, 18, and 27), Point 25 (right side of the head, located between points 21 and 27, forming a slightly curved diagonal line with points 24 and 26), Point 26 (right side of the head, located between points 23 and 27, forming a line connecting points 3, 20, and 25), Point 27 (right side of the head, forming a line connecting points 3, 10, and 15, forming a slightly curved diagonal line with points 23 and 27).

[0021] As a further technical solution of the present invention, in step S2, the skin moisture content measuring instrument is used to collect moisture content data of the entire area of ​​the scalp, wherein the skin moisture content measuring instrument is a contact-type non-invasive skin measuring instrument.

[0022] As a further technical solution of the present invention, the contact-type non-invasive skin measuring instrument is designed with a needle-shaped probe, including all instruments designed based on the correlation principle between the electrical properties of the skin and the water content of the stratum corneum, including capacitance testing instruments, resistance testing instruments and conductivity testing instruments.

[0023] As a further technical solution of the present invention, in step S3, a 3D human head model is used to divide the head into sections, and the positions of the sections correspond one-to-one with the positions of the head skin sections divided in step S1. The 3D human head model is created using 3D modeling software, including Autodesk Maya, Cinema 4D, 3ds Max, ZBrush, Blender, Houdini, Rhino, Modo, CAD, Vector, Meshmixer, and SculptGL.

[0024] As a further technical solution of the present invention, step S4, the step of matching different color RGB values ​​according to the moisture content data of different regions, includes:

[0025] S4-1. Calculate the measurement range L for scalp moisture content:

[0026] L = Lmax - Lmin;

[0027] Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0;

[0028] S4-2. Based on the measurement range L of scalp moisture content, divide the data into 10-100 equal intervals.

[0029] S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range for each interval:

[0030] Cn=((n-1)L / m,nL / m];

[0031] Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m;

[0032] S4-4. Different scalp moisture content data ranges correspond to different RGB color combinations, with R values ​​ranging from 0 to 255, G values ​​ranging from 0 to 255, and B values ​​ranging from 0 to 255.

[0033] As a further technical solution of the present invention, step S4, the step of matching different color RGB values ​​according to the moisture content data of different regions, includes:

[0034] S4-1. Calculate the measurement range L for scalp moisture content:

[0035] L = Lmax - Lmin;

[0036] Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0;

[0037] S4-2. Based on the measurement range L of scalp moisture content, divide the data into 30-60 equal intervals.

[0038] S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range for each interval:

[0039] Cn=((n-1)L / m,nL / m];

[0040] Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m;

[0041] S4-4. Different scalp moisture content data ranges correspond to different RGB color combinations, with R values ​​ranging from 0 to 255, G values ​​ranging from 0 to 255, and B values ​​ranging from 0 to 255.

[0042] As a further technical solution of the present invention, step S4, the step of matching different color RGB values ​​according to the moisture content data of different regions, includes:

[0043] S4-1. Calculate the measurement range L for scalp moisture content:

[0044] L = Lmax - Lmin;

[0045] Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0;

[0046] S4-2. Based on the measurement range L of scalp moisture content, divide the data into 60 equal intervals.

[0047] S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range for each interval:

[0048] Cn=((n-1)L / m,nL / m];

[0049] Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m;

[0050] S4-4. Different scalp moisture content data ranges are mapped to different RGB color combinations, as follows:

[0051] C1(R=5, G=1, B=0),

[0052] C2(R=83, G=2, B=0),

[0053] C3(R=140, G=9, B=1),

[0054] C4(R=179, G=53, B=2),

[0055] C5(R=199, G=91, B=3),

[0056] C6(R=222, G=126, B=5),

[0057] C7(R=233, G=155, B=8),

[0058] C8(R=238, G=193, B=50),

[0059] C9 (R=237, G=209, B=109),

[0060] C10(R=233,G=220,B=168),

[0061] C11(R=222,G=227,B=205),

[0062] C12(R=207,G=228,B=211),

[0063] C13(R=199,G=233,B=216),

[0064] C14(R=194,G=232,B=221),

[0065] C15(R=187,G=233,B=222),

[0066] C16(R=178,G=230,B=226),

[0067] C17(R=164,G=230,B=229),

[0068] C18(R=159,G=227,B=236),

[0069] C19(R=147,G=223,B=239),

[0070] C20(R=136,G=218,B=239),

[0071] C21(R=131,G=216,B=236),

[0072] C22(R=117,G=214,B=231),

[0073] C23(R=110,G=211,B=229),

[0074] C24(R=99,G=205,B=227),

[0075] C25(R=86,G=195,B=224),

[0076] C26(R=82,G=192,B=225),

[0077] C27(R=78,G=188,B=223),

[0078] C28(R=71,G=183,B=220),

[0079] C29(R=64,G=176,B=216),

[0080] C30(R=57,G=170,B=212),

[0081] C31(R=51,G=160,B=203),

[0082] C32(R=47,G=155,B=201),

[0083] C33(R=50,G=150,B=200),

[0084] C34(R=47,G=144,B=199),

[0085] C35(R=42,G=136,B=198),

[0086] C36(R=37,G=129,B=192),

[0087] C37(R=35,G=127,B=190),

[0088] C38(R=31,G=119,B=182),

[0089] C39(R=25,G=108,B=174),

[0090] C40(R=20,G=103,B=171),

[0091] C41(R=15,G=98,B=168),

[0092] C42(R=12,G=90,B=164),

[0093] C43(R=6,G=83,B=161),

[0094] C44(R=3,G=80,B=157),

[0095] C45(R=0,G=77,B=159),

[0096] C46(R=1,G=73,B=157),

[0097] C47(R=1,G=67,B=151),

[0098] C48(R=0,G=65,B=147),

[0099] C49(R=2,G=63,B=143),

[0100] C50(R=0,G=58,B=132),

[0101] C51 (R=0, G=55, B=130),

[0102] C52 (R=2, G=51, B=120),

[0103] C53 (R=1, G=47, B=109),

[0104] C54(R=2, G=42, B=101),

[0105] C55(R=1, G=36, B=94),

[0106] C56 (R=3, G=34, B=88),

[0107] C57 (R=1, G=32, B=86),

[0108] C58(R=2, G=33, B=87),

[0109] C59 (R=1, G=30, B=86),

[0110] C60 (R=5, G=32, B=75).

[0111] As a further technical solution of the present invention, in step S5, the color rendering of all sections of the character head model is specifically performed by using drawing software or 3D modeling software to perform color rendering of all sections of the character head model.

[0112] As a further technical solution of the present invention, in step S6, generating color images of human scalp 3D moisture distribution from different angles refers to establishing a spatial XYZ coordinate axis with the center point of the back of the head as the zero point, using degrees as the coordinate axis unit, with the X-axis as (-360, 360), the Y-axis as (-360, 360), and the Z-axis as (-360, 360), to generate color images of human scalp 3D moisture distribution from different angles.

[0113] Another objective of this invention is to provide a scalp moisture distribution detection system, the system comprising:

[0114] The measurement point determination module is used to divide the scalp into sections, with the center of each section designated as the moisture content measurement point.

[0115] The data acquisition module is used to collect moisture content data of all areas of the scalp using a skin moisture content measuring instrument;

[0116] The model region division module is used to divide the head into regions using a 3D human head model. The region positions correspond one-to-one with the head skin region positions divided in the measurement point determination module.

[0117] The RGB value matching module is used to match different color RGB values ​​based on the moisture content data of different regions.

[0118] The model color rendering module is used to render the colors of all sections of the character's head model.

[0119] The color image generation module is used to generate 3D color images of human scalp moisture distribution from different angles.

[0120] Compared with the prior art, the beneficial effects of the present invention are:

[0121] 1. This invention provides a whole-head partitioning method and test point distribution method, which can realize comprehensive measurement of scalp moisture. The results are more representative of the scalp moisture status and provide a more comprehensive and objective evaluation method for the efficacy evaluation of scalp moisturizing products.

[0122] 2. This invention provides a complete and continuous 3D color map of scalp moisture distribution, which transforms invisible skin moisture into a visualized 3D facial color image. Compared with traditional skin moisture measurement methods, the results are more comprehensive, intuitive, and easier for consumers to understand, and have a strong visual impact on consumers.

[0123] 3. The present invention also provides 60 preferred RGB combinations, each corresponding to a different moisture content range, which can quickly match the corresponding color based on the measurement results. The unique RGB combinations are like the characteristic code of the color, which can ensure the consistency of the presented results. Attached Figure Description

[0124] Figure 1 This is a localization map of 27 sites in the whole head provided in an embodiment of the present invention.

[0125] Figure 2 The colors and RGB combinations corresponding to the 60 moisture content ranges provided in the embodiments of the present invention.

[0126] Figure 3 This is the final output of the full-scalp 3D color image of moisture distribution in Embodiment 1 of the present invention.

[0127] Figure 4 This is the final output of the full-scalp 3D color image of moisture distribution in Embodiment 2 of the present invention.

[0128] Figure 5 This is the final output of the full-scalp 3D color image of moisture distribution in Embodiment 3 of the present invention. Detailed Implementation

[0129] The technical solution of this patent will be further described in detail below with reference to specific embodiments.

[0130] Example 1.

[0131] Please see Figures 1 to 3 The scalp is divided into sections, with the center of each section designated as the moisture content measurement point. The specific steps include:

[0132] S1-1. Divide the scalp into 27 sections, denoted as Hk, where k is 1-v and v is 27.

[0133] S1-2. Determine the location of the center point of any region in these partitions, corresponding to the following points:

[0134] Point 1 (Head midline, upper forehead, near hairline), Point 2 (Head midline, between points 1 and 3), Point 3 (Head midline, center of the top of the head), Point 4 (Head midline, between points 3 and 5), Point 5 (Head midline, center of the back of the head), Point 6 (Head midline, between points 5 and 7), Point 7 (Head midline, lower end of the back of the head), Point 8 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 1 and 2), Point 9 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 2 and 3), Point 10 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4). Point 11 (a line parallel to the center of the left eye, intersecting the horizontal line at the midpoint of points 4 and 5), Point 12 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 5 and 6), Point 13 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 6 and 7), Point 14 (left side of the head, between points 8 and 17, forming a slightly curved diagonal line with points 1, 8, and 17), Point 15 (left side of the head, between points 11 and 17, forming a slightly curved diagonal line with points 14 and 16), Point 16 (left side of the head, between points 13 and 17, forming a line connecting points 3, 10, and 15), Point 17 (left side of the head, forming a line connecting points 3, 10, and 15).Point 18 (a slightly curved diagonal line forming with points 13 and 17), point 19 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 1 and 2), point 20 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 2 and 3), point 21 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 4 and 5), point 22 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 5 and 6). Point 6 (intersecting the horizontal line at the midpoint of point 6), Point 23 (right side of the head, a line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal lines at the midpoints of points 6 and 7), Point 24 (right side of the head, located between points 18 and 27, forming a slightly curved diagonal line with points 1, 18, and 27), Point 25 (right side of the head, located between points 21 and 27, forming a slightly curved diagonal line with points 24 and 26), Point 26 (right side of the head, located between points 23 and 27, forming a line connecting points 3, 20, and 25), Point 27 (right side of the head, forming a line connecting points 3, 10, and 15, forming a slightly curved diagonal line with points 23 and 27).

[0135] S2. Use a skin moisture content measuring instrument to collect moisture content data for all areas of the scalp. Specifically, use a Moisture with Pin Probe needle-shaped skin moisture tester to collect moisture content data for 27 zones of the scalp.

[0136] S3. Using a 3D character head model, divide the head into sections, with each section corresponding to the head skin area described in step S1. Specifically, use Cinema 4D modeling software to create a 3D character head model, dividing the head into 27 sections, with each section corresponding to the head skin area described in step S1.

[0137] S4. Match different color RGB values ​​based on the moisture content data of different regions, specifically including the following steps:

[0138] S4-1. Calculate the measurement range L for scalp moisture content:

[0139] L = Lmax - Lmin;

[0140] In the above formula, Lmax is the maximum skin moisture content that can be measured by the instrument selected in step S2, and Lmin is 0;

[0141] The instrument used in this embodiment, the Moisture with Pin Probe, has a maximum measurable skin moisture content Lmax of 300, i.e., L = Lmax - Lmin = 300.

[0142] S4-2. Based on the measurement range L of scalp moisture content, divide the data into 60 equal intervals.

[0143] S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range for each interval:

[0144] Cn=((n-1)L / m,nL / m]

[0145] In the above formula, L = 300, m = 60, and n ranges from 1 to 60; the specific numerical range of C1 to C60 is as follows:

[0146] C1=(0,5], C2=(5,10], C3=(10,15], C4=(15,20], C5=(20,25], C6=(25,30], C7=(30,35], C8=(35,40], C9=(40,45], C1 0=(45,50], C11=(50,55], C12=(55,60], C13=(60,65], C14=(65,70], C15=(70,75], C16=(75,80], C17=(80,85], C18=( 85,90], C19=(90,95], C20=(95,100], C21=(100,105], C22=(105,110], C23=(110,115], C24=(115,120], C25=(120,1 25], C26=(125,130], C27=(130,135], C28=(135,140], C29=(140,145], C30=(145,150], C31=(150,155], C32=(155,16 0], C33=(160,165], C34=(165,170], C35=(170,175], C36=(175,180], C37=(180,185], C38=(185,190], C39=(190,19 5], C40=(195,200], C41=(200,205], C42=(205,210], C43=(210,215], C44=(215,220], C45=(220,225], C46=(225,230 ], C47=(230,235], C48=(235,240], C49=(240,245], C50=(245,250], C51=(250,255], C52=(255,260], C53=(260,265] , C54=(265,270], C55=(270,275], C56=(275,280], C57=(280,285], C58=(285,290], C59=(290,295], C60=(295,300];

[0147] S4-4. Different scalp moisture content data ranges are assigned to different RGB color combinations, specifically:

[0148] C1(R=5,G=1,B=0),C2(R=83,G=2,B=0),C3(R=140,G=9,B=1),C4(R=179,G=53,B=2),C5(R=199,G=91,B=3),C6(R=222,G=126,B=5),C7(R=233,G=155,B=8),C8(R=238,G=193,B=50),C9(R=237,G=209,B=109),C10(R=233,G=220,B=168),C11(R=222,G=227,B=205),C12(R=207,G=228,B=211),C13(R=199,G=233,B=216),C14(R=194,G=232,B=221),C15(R=187,G=233,B=222),C16(R=178,G=230,B=226),C17(R=164,G=230,B=229),C18(R=159,G=227,B=236),C19(R=147,G=223,B=239),C20(R=136,G=218,B=239),C21(R=131,G=216,B=236),C22(R=117,G=214,B=231),C23(R=110,G=211,B=229),C24(R=99,G=205,B=227),C25(R=86,G=195,B=224),C26(R=82,G=192,B=225),C27(R=78,G=188,B=223),C28(R=71,G=183,B=220),C29(R=64,G=176,B=216),C30(R=57,G=170,B=212),C31(R=51,G=160,B=203),C32(R=47,G=155,B=201),C33(R=50,G=150,B=200),C34(R=47,G=144,B=199),C35(R=42,G=136,B=198),C36(R=37,G=129,B=192),C37(R=35,G=127,B=190),C38(R=31,G=119,B=182),

[0149] C39(R=25,G=108,B=174),C40(R=20,G=103,B=171),C41(R=15,G=98,B=168),C42(R=12,G=90,B=164),C43(R=6,G=83,B=161),C44( R=3,G=80,B=157),C45(R=0,G=77,B=159),C46(R=1,G=73,B=157),C47(R=1,G=67,B=151),C48(R=0,G=65,B=147),C49(R=2,G=63,B =143),C50(R=0,G=58,B=132),C51(R=0,G=55,B=130),C52(R=2,G=51,B=120),C53(R=1,G=47,B=109),C54(R=2,G=42,B=101),C55( R=1,G=36,B=94),C56(R=3,G=34,B=88),C57(R=1,G=32,B=86),C58(R=2,G=33,B=87),C59(R=1,G=30,B=86),C60(R=5,G=32,B=75);

[0150] S4-5. Determine the range of moisture values ​​for different scalp skin zones and their corresponding RGB color combinations.

[0151] Based on the moisture content test data of 27 zones of the scalp, different intervals were mapped and matched with the corresponding RGB combinations to obtain the characteristic colors of different zones, as shown in Table 1:

[0152] Table 1: Moisture content test results of 27 zones of scalp and corresponding RGB combinations

[0153]

[0154]

[0155] S5. Use Cinema 4D modeling software to perform color rendering on all sections of the character's head model.

[0156] S6. Establish a spatial XYZ coordinate axis with the center point of the back of the head as the zero point, using degrees as the coordinate unit. The X-axis is (-360, 360), the Y-axis is (-360, 360), and the Z-axis is (-360, 360). Generate 3D color images of human scalp moisture distribution at different angles. See... Figure 3 .

[0157] Example 2.

[0158] After the subject in Example 1 used the scalp moisturizing product, steps S2, S4-4, S4-5, S5, and S6 were performed again:

[0159] The results of this embodiment are shown in Table 2. The final output 3D color image of the entire scalp's moisture distribution is shown in Table 2. Figure 4 As shown:

[0160] Table 2: Test results of moisture content in 27 areas of the scalp after product use and corresponding RGB combinations

[0161]

[0162]

[0163] Example 3.

[0164] In this embodiment, the subject applied a scalp moisturizing essence to the left half of their head, while leaving the right half of their head untouched. The technical solution of this invention was then implemented.

[0165] S1 divides the subject's head into sections, with the center of each section designated as the moisture content measurement point. The specific steps include:

[0166] S1-1. Divide the scalp into 20 sections, denoted as Hk, where k is 1-v and v is 20.

[0167] S1-2. Determine the center point location of any region in these partitions, corresponding to the following points (select 20 points from the following 27 points):

[0168] Point 1 (Head midline, upper forehead, near hairline), Point 2 (Head midline, between points 1 and 3), Point 3 (Head midline, center of the top of the head), Point 4 (Head midline, between points 3 and 5), Point 5 (Head midline, center of the back of the head), Point 6 (Head midline, between points 5 and 7), Point 7 (Head midline, lower end of the back of the head), Point 8 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 1 and 2), Point 9 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 2 and 3), Point 10 (Left side of the head, a line parallel to the head midline and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4), Point 11 (Left side of the head, a line parallel to the head midline, passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 3 and 4). Point 11 (a line parallel to the center of the left eye, intersecting the horizontal line at the midpoint of points 4 and 5), Point 12 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 5 and 6), Point 13 (left side of the head, a line parallel to the midline of the head and passing through the center of the left eye, intersecting the horizontal line at the midpoint of points 6 and 7), Point 14 (left side of the head, between points 8 and 17, forming a slightly curved diagonal line with points 1, 8, and 17), Point 15 (left side of the head, between points 11 and 17, forming a slightly curved diagonal line with points 14 and 16), Point 16 (left side of the head, between points 13 and 17, forming a line connecting points 3, 10, and 15), Point 17 (left side of the head, forming a line connecting points 3, 10, and 15).Point 18 (a slightly curved diagonal line forming with points 13 and 17), point 19 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 1 and 2), point 20 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 2 and 3), point 21 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 4 and 5), point 22 (a parallel line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal line at the midpoint of points 5 and 6). Point 6 (intersecting the horizontal line at the midpoint of point 6), Point 23 (right side of the head, a line parallel to the midline of the head and passing through the center of the right eye, intersecting the horizontal lines at the midpoints of points 6 and 7), Point 24 (right side of the head, located between points 18 and 27, forming a slightly curved diagonal line with points 1, 18, and 27), Point 25 (right side of the head, located between points 21 and 27, forming a slightly curved diagonal line with points 24 and 26), Point 26 (right side of the head, located between points 23 and 27, forming a line connecting points 3, 20, and 25), Point 27 (right side of the head, forming a line connecting points 3, 10, and 15, forming a slightly curved diagonal line with points 23 and 27).

[0169] S2. Use a skin moisture content measuring instrument to collect moisture content data for all areas of the scalp. Specifically, use a Moisture with Pin Probe needle-shaped skin moisture tester to collect moisture content data for 20 zones of the scalp.

[0170] S3. Using a 3D character head model, divide the head into sections, with each section corresponding to the head skin area described in step S1. Specifically, use Cinema 4D modeling software to create a 3D character head model, dividing the head into 20 sections, with each section corresponding to the head skin area described in step S1.

[0171] S4. Match different color RGB values ​​based on the moisture content data of different regions, specifically including the following steps:

[0172] S4-1. Calculate the measurement range L for scalp moisture content:

[0173] L = Lmax - Lmin;

[0174] In the above formula, Lmax is the maximum skin moisture content that can be measured by the instrument selected in step S2, and Lmin is 0;

[0175] The instrument used in this embodiment, the Moisture with Pin Probe, has a maximum measurable skin moisture content Lmax of 300, i.e., L = Lmax - Lmin = 300.

[0176] S4-2. Based on the measurement range L of scalp moisture content, divide the data into 60 equal intervals.

[0177] S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range for each interval:

[0178] Cn=((n-1)L / 60,nL / 60]

[0179] In the above formula, L = 300, m = 60, and n ranges from 1 to 60; the specific numerical range of C1 to C60 is as follows:

[0180] C1=(0,5], C2=(5,10], C3=(10,15], C4=(15,20], C5=(20,25], C6=(25,30], C7=(30,35], C8=(35,40], C9=(40,45], C1 0=(45,50], C11=(50,55], C12=(55,60], C13=(60,65], C14=(65,70], C15=(70,75], C16=(75,80], C17=(80,85], C18=( 85,90], C19=(90,95], C20=(95,100], C21=(100,105], C22=(105,110], C23=(110,115], C24=(115,120], C25=(120,1 25], C26=(125,130], C27=(130,135], C28=(135,140], C29=(140,145], C30=(145,150], C31=(150,155], C32=(155,16 0], C33=(160,165], C34=(165,170], C35=(170,175], C36=(175,180], C37=(180,185], C38=(185,190], C39=(190,19 5], C40=(195,200], C41=(200,205], C42=(205,210], C43=(210,215], C44=(215,220], C45=(220,225], C46=(225,230 ], C47=(230,235], C48=(235,240], C49=(240,245], C50=(245,250], C51=(250,255], C52=(255,260], C53=(260,265] , C54=(265,270], C55=(270,275], C56=(275,280], C57=(280,285], C58=(285,290], C59=(290,295], C60=(295,300];

[0181] S4-4. Different scalp moisture content data ranges are assigned to different RGB color combinations, specifically:

[0182] C1(R=5,G=1,B=0),C2(R=83,G=2,B=0),C3(R=140,G=9,B=1),C4(R=179,G=53,B=2),C5(R=199,G=91,B=3),C6(R=222,G=126,B=5),C7(R=233,G=155,B=8),C8(R=238,G=193,B=50),C9(R=237,G=209,B=109),C10(R=233,G=220,B=168),C11(R=222,G=227,B=205),C12(R=207,G=228,B=211),C13(R=199,G=233,B=216),C14(R=194,G=232,B=221),C15(R=187,G=233,B=222),C16(R=178,G=230,B=226),C17(R=164,G=230,B=229),C18(R=159,G=227,B=236),C19(R=147,G=223,B=239),C20(R=136,G=218,B=239),C21(R=131,G=216,B=236),C22(R=117,G=214,B=231),C23(R=110,G=211,B=229),C24(R=99,G=205,B=227),C25(R=86,G=195,B=224),C26(R=82,G=192,B=225),C27(R=78,G=188,B=223),C28(R=71,G=183,B=220),C29(R=64,G=176,B=216),C30(R=57,G=170,B=212),C31(R=51,G=160,B=203),C32(R=47,G=155,B=201),C33(R=50,G=150,B=200),C34(R=47,G=144,B=199),C35(R=42,G=136,B=198),C36(R=37,G=129,B=192),C37(R=35,G=127,B=190),C38(R=31,G=119,B=182),

[0183] C39(R=25,G=108,B=174),C40(R=20,G=103,B=171),C41(R=15,G=98,B=168),C42(R=12,G=90,B=164),C43(R=6,G=83,B=161),C44( R=3,G=80,B=157),C45(R=0,G=77,B=159),C46(R=1,G=73,B=157),C47(R=1,G=67,B=151),C48(R=0,G=65,B=147),C49(R=2,G=63,B =143),C50(R=0,G=58,B=132),C51(R=0,G=55,B=130),C52(R=2,G=51,B=120),C53(R=1,G=47,B=109),C54(R=2,G=42,B=101),C55( R=1,G=36,B=94),C56(R=3,G=34,B=88),C57(R=1,G=32,B=86),C58(R=2,G=33,B=87),C59(R=1,G=30,B=86),C60(R=5,G=32,B=75);

[0184] Based on the moisture content test data of 20 zones of the scalp, different intervals were mapped and matched with the corresponding RGB combinations to obtain the characteristic colors of different zones, as shown in Table 3:

[0185] Table 3: Moisture content test results of 20 zones of scalp and corresponding RGB combinations

[0186]

[0187]

[0188] S5. Use Cinema 4D modeling software to perform color rendering on all sections of the character's head model.

[0189] S6. Establish a spatial XYZ coordinate axis with the center point of the back of the head as the zero point, using degrees as the coordinate unit. The X-axis is (-360, 360), the Y-axis is (-360, 360), and the Z-axis is (-360, 360). Generate 3D color images of human scalp moisture distribution at different angles. See... Figure 5 .

[0190] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0191] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for detecting scalp moisture distribution, characterized in that, The method includes the following steps: S1. Divide the scalp into sections, with the center of each section being the measurement point for moisture content. S2. Collect moisture content data of all areas of the scalp using a skin moisture content measuring instrument; the skin moisture content measuring instrument is a contact-type non-invasive skin measuring instrument; the contact-type non-invasive skin measuring instrument is designed with a needle probe, including all instruments designed based on the correlation principle between the electrical properties of the skin and the water content of the stratum corneum, including capacitance testing instruments, resistance testing instruments and conductivity testing instruments; S3. Using a 3D character head model, divide the head into sections, with each section corresponding to the section of the head skin area divided in step S1. S4. Match different color RGB values ​​based on the moisture content data of different regions; S5. Apply color rendering to all sections of the character's head model; S6. Generate 3D color images of human scalp moisture distribution from different angles.

2. The method for detecting scalp moisture distribution according to claim 1, characterized in that, In step S1, the scalp skin is divided into 15-27 sections, denoted as Hk, where k is 1-v and v is 15-27.

3. The method for detecting scalp moisture distribution according to claim 2, characterized in that, In step S1, the scalp skin is divided into 20-27 sections, denoted as Hk, where k is 1-v and v is 20-27.

4. The method for detecting scalp moisture distribution according to claim 1, characterized in that, In step S4, the step of matching different color RGB values ​​based on the moisture content data of different regions includes: S4-1. Calculate the measurement range L for scalp moisture content: L = Lmax - Lmin; Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0; S4-2. Based on the measurement range L of scalp moisture content, divide the data into 10-100 equal intervals. S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range of each interval: Cn = ((n-1)L / m, nL / m]; Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m; S4-4. Different scalp moisture content data ranges correspond to different RGB color combinations, with R values ​​ranging from 0 to 255, G values ​​ranging from 0 to 255, and B values ​​ranging from 0 to 255.

5. The method for detecting scalp moisture distribution according to claim 4, characterized in that, In step S4, the step of matching different color RGB values ​​based on the moisture content data of different regions includes: S4-1. Calculate the measurement range L for scalp moisture content: L = Lmax - Lmin; Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0; S4-2. Based on the measurement range L of scalp moisture content, divide the data into 30-60 equal intervals. S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range of each interval: Cn = ((n-1)L / m, nL / m]; Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m; S4-4. Different scalp moisture content data ranges correspond to different RGB color combinations, with R values ​​ranging from 0 to 255, G values ​​ranging from 0 to 255, and B values ​​ranging from 0 to 255.

6. The method for detecting scalp moisture distribution according to claim 5, characterized in that, In step S4, the step of matching different color RGB values ​​based on the moisture content data of different regions includes: S4-1. Calculate the measurement range L for scalp moisture content: L = Lmax - Lmin; Where Lmax is the maximum skin moisture content that the skin moisture content measuring instrument can measure, and Lmin is 0; S4-2. Based on the measurement range L of scalp moisture content, divide the data into 60 equal intervals. S4-3. Determine the data range of these equally divided intervals, denoted as Cn for each interval, and calculate the value range of each interval: Cn = ((n-1)L / m, nL / m]; Where L is the measurement range, m is the number of equal intervals, and n ranges from 1 to m; S4-4. Different scalp moisture content data ranges are mapped to different RGB color combinations, as follows: C1(R=5, G=1, B=0), C2(R=83, G=2, B=0), C3(R=140, G=9, B=1), C4(R=179, G=53, B=2), C5(R=199, G=91, B=3), C6(R=222, G=126, B=5), C7(R=233, G=155, B=8), C8(R=238, G=193, B=50), C9 (R=237, G=209, B=109), C10 (R=233, G=220, B=168), C11(R=222, G=227, B=205), C12 (R=207, G=228, B=211), C13 (R=199, G=233, B=216), C14 (R=194, G=232, B=221), C15(R=187, G=233, B=222), C16 (R=178, G=230, B=226), C17(R=164, G=230, B=229), C18(R=159, G=227, B=236), C19 (R=147, G=223, B=239), C20 (R=136, G=218, B=239), C21 (R=131, G=216, B=236), C22 (R=117, G=214, B=231), C23 (R=110, G=211, B=229), C24 (R=99, G=205, B=227), C25(R=86, G=195, B=224), C26 (R=82, G=192, B=225), C27 (R=78, G=188, B=223), C28(R=71, G=183, B=220), C29 (R=64, G=176, B=216), C30 (R=57, G=170, B=212), C31 (R=51, G=160, B=203), C32 (R=47, G=155, B=201), C33(R=50, G=150, B=200), C34 (R=47, G=144, B=199), C35(R=42, G=136, B=198), C36 (R=37, G=129, B=192), C37 (R=35, G=127, B=190), C38(R=31, G=119, B=182), C39 (R=25, G=108, B=174), C40 (R=20, G=103, B=171), C41 (R=15, G=98, B=168), C42 (R=12, G=90, B=164), C43 (R=6, G=83, B=161), C44(R=3, G=80, B=157), C45(R=0, G=77, B=159), C46 (R=1, G=73, B=157), C47 (R=1, G=67, B=151), C48(R=0, G=65, B=147), C49 (R=2, G=63, B=143), C50 (R=0, G=58, B=132), C51 (R=0, G=55, B=130), C52 (R=2, G=51, B=120), C53 (R=1, G=47, B=109), C54(R=2, G=42, B=101), C55(R=1, G=36, B=94), C56 (R=3, G=34, B=88), C57 (R=1, G=32, B=86), C58(R=2, G=33, B=87), C59 (R=1, G=30, B=86), C60 (R=5, G=32, B=75).

7. The method for detecting scalp moisture distribution according to claim 1, characterized in that, In step S6, generating 3D color images of human scalp moisture distribution from different angles refers to establishing a spatial XYZ coordinate axis with the center point of the back of the head as the zero point, using degrees as the coordinate axis unit, with the X-axis at (-360, 360), the Y-axis at (-360, 360), and the Z-axis at (-360, 360), to generate 3D color images of human scalp moisture distribution from different angles.

8. A scalp moisture distribution detection system, characterized in that, The system includes: The measurement point determination module is used to divide the scalp into sections, with the center of each section designated as the moisture content measurement point. The data acquisition module is used to collect moisture content data of all areas of the scalp using a skin moisture content measuring instrument; the skin moisture content measuring instrument is a contact-type non-invasive skin measuring instrument; the contact-type non-invasive skin measuring instrument has a needle probe design, including all instruments designed based on the correlation principle between the electrical properties of the skin and the water content of the stratum corneum, including capacitance testing instruments, resistance testing instruments and conductivity testing instruments; The model region division module is used to divide the head into regions using a 3D human head model. The region positions correspond one-to-one with the head skin region positions divided in the measurement point determination module. The RGB value matching module is used to match different color RGB values ​​based on the moisture content data of different regions. The model color rendering module is used to render the colors of all sections of the character's head model. The color image generation module is used to generate 3D color images of human scalp moisture distribution from different angles.

Images