JP6393063B2 - Aging pore identification method and cosmetic evaluation method - Google Patents
Aging pore identification method and cosmetic evaluation method Download PDFInfo
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- 239000011148 porous material Substances 0.000 title claims description 155
- 230000032683 aging Effects 0.000 title claims description 112
- 238000011156 evaluation Methods 0.000 title claims description 95
- 239000002537 cosmetic Substances 0.000 title claims description 56
- 238000000034 method Methods 0.000 title claims description 44
- 230000000007 visual effect Effects 0.000 claims description 27
- 230000000694 effects Effects 0.000 claims description 20
- 238000005286 illumination Methods 0.000 description 10
- 238000000611 regression analysis Methods 0.000 description 10
- 238000012360 testing method Methods 0.000 description 8
- 239000003795 chemical substances by application Substances 0.000 description 5
- 238000012850 discrimination method Methods 0.000 description 5
- 238000003384 imaging method Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 5
- 239000000843 powder Substances 0.000 description 5
- 238000004898 kneading Methods 0.000 description 4
- 239000002245 particle Substances 0.000 description 4
- 229920001296 polysiloxane Polymers 0.000 description 4
- 238000002360 preparation method Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 239000004570 mortar (masonry) Substances 0.000 description 3
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 2
- 230000003796 beauty Effects 0.000 description 2
- 239000011248 coating agent Substances 0.000 description 2
- 238000000576 coating method Methods 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000011049 filling Methods 0.000 description 2
- 238000012628 principal component regression Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000000550 effect on aging Effects 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 230000004313 glare Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 238000000491 multivariate analysis Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 239000000377 silicon dioxide Substances 0.000 description 1
- 238000003756 stirring Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000037303 wrinkles Effects 0.000 description 1
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Description
本発明は、加齢毛穴の鑑別方法及び化粧料の評価方法に関し、より詳しくは加齢毛穴の目立ちの目視評価値を目的変数とし、肌画像から得た色の照度等の変動係数を含む数値を説明変数として得られる回帰式を利用して加齢毛穴の目立ちを評価する鑑別方法及び該鑑別方法を利用した化粧料の評価方法に関する。 The present invention relates to a method for identifying aging pores and a method for evaluating cosmetics, and more specifically, a visual evaluation value for conspicuous aging pores as a target variable, and a numerical value including a coefficient of variation such as illuminance of a color obtained from a skin image The present invention relates to a discrimination method for evaluating the conspicuousness of aging pores using a regression equation obtained as an explanatory variable, and a cosmetic evaluation method using the discrimination method.
顔の毛穴は、当然ながら誰にでも存在するものであるが、毛穴の見え方、或いはその毛穴を気にするか否かについては個人差が大きいところがある。しかしながら、毛穴が目立つこと自体は、女性にとってはプラスの感覚ではなく、むしろマイナスに捉えられるものである。従って、いかに毛穴を見えにくくするかは、化粧方法や化粧料に求められることなのである。 Naturally, pores on the face exist for everyone, but there are differences among individuals regarding how the pores look or whether or not they care about the pores. However, the fact that pores are conspicuous is not a positive sense for women, but rather a negative one. Therefore, how to make pores difficult to see is required for makeup methods and cosmetics.
毛穴が目立つか否かは個人差が存するが、その要因の１つが「加齢」であることは周知である。一般に毛穴は、加齢に伴い、形態学的に毛穴の皮膚表面の開口部が広がる傾向にあり、これが毛穴が目立つ原因の１つになっている。若齢者の場合、毛穴の形態は比較的円筒形に近い凹部が独立して生じていると考えられるが、加齢に伴う開口部の開きは皮膚表面の凹凸構造の凸部の縁が減退し、結果として凹部が目立つこととなる。両者の毛穴を形態学的に比較すると、若齢期では肌表面が「きめが細かい」という言葉に代表されるように、毛穴自体が小さく目立たない、若しくは縦方向の円筒状に呈する傾向にあるのに対し、加齢に伴う毛穴の開きとは、皮膚表面の開口部自体が広くなり、そこからすり鉢の斜面の如く中央部底面に向かった斜面を呈しているものと考えられる。このように、年齢によって毛穴の形態は異なることから、単に毛穴を隠す方法と言っても、一様でないことは容易に想像され、そのための好適な化粧方法や化粧料は当然ながら異なる。 Whether or not pores are conspicuous varies from individual to individual, and it is well known that one of the factors is “aging”. Generally, pores tend to morphologically widen the pores on the skin surface with aging, and this is one of the causes that make pores conspicuous. In the case of young people, the pore shape is considered to be a relatively cylindrical recess, but the opening of the opening with aging is reduced at the edges of the protrusions of the uneven structure on the skin surface. As a result, the concave portion becomes conspicuous. Comparing both pores morphologically, the skin surface tends to be small, inconspicuous, or present in a cylindrical shape in the vertical direction, as represented by the word “fine texture” in the younger age. On the other hand, the opening of pores with aging is considered to be that the opening on the surface of the skin itself is widened, and that it exhibits a slope toward the bottom of the center, such as the slope of a mortar. Thus, since the form of the pores varies depending on the age, it is easily imagined that the method of simply concealing the pores is not uniform, and naturally suitable cosmetic methods and cosmetics are different.
これまで一般的に、粒子が小さい球状粉体などの素材が毛穴の内部に充填され易く、毛穴隠しに好適な素材として考えられてきており、実際にそのような素材が配合された化粧料の効果が発揮されていた。しかしながら、必ずしも粒子が小さい球状粉体を配合した化粧料であっても毛穴を隠すための効果が十分でないなどの問題が存した。これは、前述のように加齢に伴う毛穴の形態の変化が詳細に解明されていなかったことも要因の１つとして考えられ、実際に加齢に伴い、皮膚表面の開口部が広がった毛穴に対してどのような化粧品方法が好適であるかは解明されていなかったし、このような観点での毛穴隠しに好適な化粧料の提案もなされていなかったのが実情である。 In general, materials such as spherical powder with small particles are easily filled into pores and have been considered as materials suitable for concealing pores. The effect was demonstrated. However, there is a problem that the effect of hiding pores is not sufficient even in a cosmetic containing a spherical powder with small particles. This is considered to be due to the fact that the changes in pore shape accompanying aging were not elucidated in detail as described above, and pores in which the opening on the skin surface actually spreads with aging. On the other hand, what kind of cosmetic method is suitable has not been elucidated, and no cosmetics suitable for concealing pores from this point of view have been proposed.
皮膚形態、さらに詳細には毛穴の構造に着目した化粧料の選択方法は、これまでにいくつか報告されている。即ち、毛穴の面積と深さとから肌の特性に着目し、好適なベースアップ化粧料を選択する方法（特許文献１参照）などもあるが、毛穴補正効果を上げるあまり、見た目がマットな印象になることもしばしばあった。さらに、このような背景もあり、毛穴補正効果についての要望はさらに高まり、加えて自然な見栄えが好まれることから、ベースメークアップ化粧品だけでは補正しがたい毛穴隠しに効果がある化粧料として、近年では下地化粧料に毛穴補正効果を付与することが多い。例えば、シリカなどの半透明な球状粉体を化粧料に配合することにより、毛穴を埋める技術が開発されている（特許文献２参照）。加齢による毛穴の皮膚表面における開口部の広がりを考慮しない場合、粒径３〜２０μｍの球状粉体が、簡便性という面で、毛穴の充填に著しい効果を有することが示されている（特許文献３参照）。さらに、より毛穴の形態に着目したとき、粒子径が４〜１５μｍであるときより効果を示すことが明らかにされており（特許文献４参照）、広く一般的に用いられる化粧料については、好適な毛穴補正用の化粧料素材と言える。 Several methods for selecting cosmetics that focus on skin morphology, more specifically, pore structure, have been reported so far. That is, there is a method of selecting a suitable base-up cosmetic by paying attention to the characteristics of the skin from the area and depth of the pores (see Patent Document 1). Often it was. In addition, there is such a background, the demand for pore correction effect is further increased, and since natural appearance is preferred, as a cosmetic that is effective in concealing pores that is difficult to correct with base makeup cosmetics alone, In recent years, pore correction effects are often imparted to base cosmetics. For example, a technique for filling pores by blending a translucent spherical powder such as silica into cosmetics has been developed (see Patent Document 2). It is shown that spherical powder having a particle size of 3 to 20 μm has a remarkable effect on filling pores in terms of simplicity when the opening of the pores on the skin surface due to aging is not considered (patent) Reference 3). Furthermore, when paying attention to the form of pores, it has been clarified that the effect is more effective when the particle diameter is 4 to 15 μm (see Patent Document 4). It can be said that it is a cosmetic material for correcting pores.
前述のように、加齢によって皮膚表面の開口部が広がってしまった毛穴（以下、「加齢毛穴」と略す場合がある。）は、通常の化粧料や化粧方法では十分に隠すことが困難であった。このような加齢毛穴を隠すために有効な化粧料を開発するためには、まず加齢毛穴の目立ちを正確に評価できる方法を確立することが重要である。
即ち、本発明は、加齢によって皮膚表面の開口部が広がった加齢毛穴の目立ちを評価する方法を提供することを目的とする。
As described above, pores whose skin surface opening has spread due to aging (hereinafter may be abbreviated as “aged pores”) are difficult to hide sufficiently with normal cosmetics and makeup methods. Met. In order to develop an effective cosmetic for hiding such aging pores, it is important to first establish a method that can accurately evaluate the conspicuousness of aging pores.
That is, an object of the present invention is to provide a method for evaluating the conspicuousness of an aging pore in which an opening on the skin surface has spread due to aging.
本発明者らは、上記課題を解決すべく鋭意検討を重ねた結果、肌画像から得られる色の照度等の変動係数が、目視評価によって決定した加齢毛穴の目立ちの評価値と高い相関性を示し、加齢毛穴の目立ちを評価する上での有効な指標となることを見出し、本発明を完成させた。 As a result of intensive studies to solve the above-mentioned problems, the present inventors have found that the coefficient of variation such as the illuminance of the color obtained from the skin image is highly correlated with the evaluation value of conspicuous aging pores determined by visual evaluation. And was found to be an effective index for evaluating the conspicuousness of aging pores, thereby completing the present invention.
即ち、本発明は以下の通りである。
＜１＞ 加齢毛穴の目立ちを評価する加齢毛穴の鑑別方法であって、（１）被験者又は前記被験者の肌画像から得た加齢毛穴の目立ちの目視評価値を目的変数とし、前記被験者の肌画像から得た色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を説明変数として得られる回帰式を準備する第１工程、（２）鑑別対象者の肌画像から色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を得る第２工程、及び（３）前記第２工程で得た前記数値を、前記第１工程で準備した前記回帰式に代入し、算出された数値を前記鑑別対象者の加齢毛穴の目立ちの評価値として決定する第３工程を含むことを特徴とする、加齢毛穴の鑑別方法。
＜２＞ 化粧料の加齢毛穴の隠し効果を評価する化粧料の評価方法であって、（１’）＜１＞に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布する前の被験者の加齢毛穴の目立ちの評価値を得る第１’工程、（２’）＜１＞に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布した後の被験者の加齢毛穴の目立ちの評価値を得る第２’工程、及び（３’）前記第１’工程で得た前記評価値と前記第２’工程で得た前記評価値を比較して、加齢毛穴の目立ちが抑制されていた場合に、前記化粧料には加齢毛穴の隠し効果がある決定する第３’工程を含むことを特徴とする、化粧料の評価方法。
That is, the present invention is as follows.
<1> A method for differentiating aging pores by evaluating the conspicuousness of aging pores, wherein (1) a visual evaluation value of conspicuous aging pores obtained from a subject or a skin image of the subject is an objective variable, and the subject A first step of preparing a regression equation obtained by using numerical values including variation coefficient, geometric mean, or harmonic mean of color illuminance group, luminance group, or lightness group obtained from the skin image of (2), and (2) discrimination target A second step of obtaining a numerical value including a variation coefficient, geometric average, or harmonic average of color illuminance group, luminance group, or lightness group from a person's skin image, and (3) the numerical value obtained in the second step, Substituting into the regression equation prepared in the first step, and including a third step of determining the calculated numerical value as a conspicuous evaluation value of the age-related pores of the identification subject, Identification method.
<2> A cosmetic evaluation method for evaluating the effect of concealing aging pores of cosmetics, wherein the cosmetic is applied by the method for distinguishing aging pores according to (1 ′) <1>. Step 1 ′ for obtaining evaluation value of conspicuousness of aging pores of test subject, (2 ′) Conspicuity of aging pores of test subject after applying cosmetic by the method for distinguishing aging pores according to <1> 2 ′ step for obtaining an evaluation value of (3 ′), and (3 ′) comparing the evaluation value obtained in the first ′ step with the evaluation value obtained in the second ′ step, thereby suppressing conspicuous aging pores. In the case where it has been done, the cosmetic material includes a third step of determining that the cosmetic material has a concealing effect on aging pores.
本発明によれば、加齢毛穴の目立ち及び化粧料の加齢毛穴の隠し効果を評価することができる。 According to the present invention, the conspicuousness of aging pores and the concealing effect of aging pores of cosmetics can be evaluated.
以下、本発明について説明するが、本発明の技術的範囲は、以下の具体的な実施形態にのみ限定されるものではない。 The present invention will be described below, but the technical scope of the present invention is not limited to the following specific embodiments.
＜加齢毛穴の鑑別方法＞
本発明の一態様である加齢毛穴の鑑別方法（以下、「本発明の鑑別方法」と略す場合がある。）は、加齢毛穴の目立ちを評価する方法であり、下記（１）〜（３）の工程を含むことを特徴とする。
（１）被験者又は前記被験者の肌画像から得た加齢毛穴の目立ちの目視評価値を目的変数とし、前記被験者の肌画像から得た色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を説明変数として得られる回帰式を準備する第１工程。（２）鑑別対象者の肌画像から色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を得る第２工程。
（３）前記第２工程で得た前記数値を、前記第１工程で準備した前記回帰式に代入し、算出された数値を前記鑑別対象者の加齢毛穴の目立ちの評価値として決定する第３工程。
本発明者らは、加齢毛穴の目立ちを評価するために、まず目視評価によって、目立つ毛穴を加齢毛穴に基づくものとそれ以外の毛穴に基づくものに分類し、さらにその目立ちを段階（レベル）分けして、それぞれの毛穴の特徴を検証した。なお、「加齢毛穴」は、「皮膚表面の開口部が広がり、形状がすり鉢状になっている毛穴」と定義して、判断を行った。このような目視評価は、肌のシワ、キメ等を評価するために化粧品業界等で使用されている方法である。目視評価は、官能評価ではあるが、元来、肌の美しさは人の視覚によって認識されるものであり、さらに正確かつ客観的に評価できることが化粧品業界等で認められているため、必要とする情報を効率的に取得できる実用的な方法なのである。なお、図４に示す基準写真を参考に、熟練した評価者１０名によって加齢毛穴の目視評価を行った結果、１０名／１０名が正当となり、再現良く正確な分類（評価）が行えることを確認した。
加齢毛穴が目立つ被験者と目立たない被験者の肌画像及び加齢毛穴以外の毛穴（以下、「普通毛穴」と略す場合がある。）が目立つ被験者（若齢者）と目立たない被験者（若齢者）の肌画像（ＲＧＢ表色系画像）から、それぞれ図１に示す領域の緑（Ｇ）、青（Ｂ）、及びＲＧＢ混色の照度データを取得して、それをヒストグラムにまとめると図２に示すような分布になる。普通毛穴が目立つ被験者の肌画像は低照度側（ブラック側）の比率が増加するのに対して、加齢毛穴が目立つ被験者の肌画像は高照度側（ホワイト側）と低照度側（ブラック側）の両方の比率が増加して、分布が広がる傾向にあることが確認できる。これは毛穴の断面構造が加齢によって図３に示すように進行し、毛穴周辺の表面のギラツキによって高照度側（ホワイト側）の比率が増加するとともに、暗部となる毛穴の面積が増えることによって低照度側（ブラック側）の比率も増加するためであると思われる（なお、色の照度のみならず、「明るさ」に関係する「輝度」や「明度」等の値についても、分布が広がる傾向にある。）。そして、本発明者らは、このような加齢毛穴の「明るさ」の分布の特徴が現れる変動係数、幾何平均、調和平均等の処理数値を説明変数の１つとし、加齢毛穴の目立ちの目視評価値を目的変数として回帰分析を行うことにより、得られた回帰式が加齢毛穴の目立ちを評価する有効な予測式になることを見出したのである。
なお、「加齢毛穴」とは、前述のように「皮膚表面の開口部が広がり、形状がすり鉢状になっている毛穴」を意味するものとする。
また、「加齢毛穴の目立ちの目視評価値」と「加齢毛穴の目立ちの評価値」の「評価値」とは、加齢毛穴の目立ちの程度を任意の数の段階に分類して、それぞれの段階に応じて付与された数値を意味するものとする。従って、例えば加齢毛穴の目立ちを３段階に分類する場合、加齢毛穴が目立つ群を評価値３と、加齢毛穴が目立たない群を評価値１と、残
りの群を評価値２と設定することが挙げられる。
また、「肌画像から得た色の照度群、輝度群、若しくは明度群」と「肌画像から色の照度群、輝度群、若しくは明度群」の「色の照度群」とは、ＲＧＢ表色系における赤（Ｒ）、緑（Ｇ）、青（Ｂ）等の照度（強度）の数値（例えば、０（ブラック）〜２５５（ホワイト））群や、ＣＭＹＫ表色系におけるシアン（Ｃ）、マゼンタ（Ｍ）、イエロー（Ｙ）、ブラック（Ｂ）等の照度（強度）の数値群を意味する。また、「輝度群」とは、ＹＵＶ表色系等における輝度（Ｙ）の数値群や、ＨＬＳ表色系における輝度（Ｌ）の数値群を意味し、「明度群」とは、マンセル表色系等における明度（Ｖ）の数値群を意味する。
さらに「色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値」の「数値」とは、肌画像から得られる「彩度」等の直接的な数値、又はこれらの数値を統計的に処理して得られる「平均値」、「最大値」等の数値を意味し、「色の照度群の変動係数」、「色の照度群の幾何平均」、「色の照度群の調和平均」、「輝度群の変動係数」、「輝度群の幾何平均」、「輝度群の調和平均」、「明度群の変動係数」、「明度群の幾何平均」、又は「明度群の調和平均」を含むものであれば、その他の数値は特に限定されないことを意味する。
<Method for distinguishing aging pores>
The method for distinguishing aging pores (hereinafter sometimes abbreviated as “the distinguishing method of the present invention”), which is an embodiment of the present invention, is a method for evaluating the conspicuousness of aging pores, and includes the following (1) to ( 3) is included.
(1) A visual evaluation value of conspicuous aging pores obtained from the subject or the subject's skin image is used as a target variable, and the illuminance group, luminance group, or lightness group variation coefficient of the color obtained from the subject's skin image, A first step of preparing a regression equation obtained by using a numerical value including a geometric average or a harmonic average as an explanatory variable. (2) A second step of obtaining a numerical value including a variation coefficient, a geometric average, or a harmonic average of a color illuminance group, a luminance group, or a lightness group from a skin image of a discrimination target person.
(3) Substituting the numerical value obtained in the second step into the regression equation prepared in the first step, and determining the calculated numerical value as an evaluation value for conspicuous aging pores of the identification subject 3 steps.
In order to evaluate the conspicuousness of the aging pores, the present inventors first classify the conspicuous pores into those based on the aging pores and those based on other pores by visual evaluation, and further classify the conspicuous stages (levels). ) Divided and verified the characteristics of each pore. “Aging pores” were defined as “pores with widened openings on the skin surface and shaped like a mortar”, and were judged. Such visual evaluation is a method used in the cosmetics industry and the like for evaluating skin wrinkles, texture, and the like. Although visual evaluation is a sensory evaluation, it is originally necessary that the beauty of skin is recognized by human vision, and it is recognized by the cosmetics industry etc. that it can be evaluated more accurately and objectively. It is a practical method that can efficiently acquire information. In addition, as a result of visual evaluation of aging pores by 10 skilled evaluators with reference to the reference photograph shown in FIG. 4, 10/10 people are valid, and accurate classification (evaluation) can be performed with good reproducibility. It was confirmed.
Skin images of subjects with conspicuous aging pores and subjects with inconspicuous subjects, and subjects with prominent pores other than aging pores (hereinafter sometimes abbreviated as “normal pores”) and subjects with inconspicuous (young people) 2), the illuminance data of the green (G), blue (B), and RGB mixed colors in the region shown in FIG. 1 is obtained from the skin image (RGB color system image), respectively, and is collected into a histogram as shown in FIG. The distribution is as shown. The skin image of subjects with normal pores on the low illuminance side (black side) increases, while the skin images of subjects with aging pores on the high illumination side (white side) and low illuminance side (black side) ) Increase in both ratios, and the distribution tends to expand. This is because the cross-sectional structure of the pores progresses as shown in FIG. 3 by aging, and the ratio of the high illuminance side (white side) increases due to the glare of the surface around the pores, and the area of pores that become dark parts increases. This seems to be due to an increase in the ratio of the low illuminance side (black side) (in addition to the illuminance of the color, the “brightness” and “brightness” values related to “brightness” are also distributed. It tends to spread.) Then, the present inventors set the processing coefficient such as the coefficient of variation, the geometric mean, the harmonic mean, etc. in which the characteristics of the “brightness” distribution of the aging pores appear as one of the explanatory variables, and the conspicuousness of the aging pores. It was found that by performing regression analysis using the visual evaluation value of as a target variable, the obtained regression equation becomes an effective prediction equation for evaluating the conspicuousness of aging pores.
Note that “aged pores” mean “pores having an opening on the skin surface and a mortar shape” as described above.
In addition, the “evaluation value” of “visual evaluation value of conspicuous aging pores” and “evaluation value of conspicuous aging pores” classifies the degree of conspicuous aging pores into an arbitrary number of stages, It shall mean the numerical value given according to each stage. Therefore, for example, when classifying the conspicuousness of aging pores into three levels, a group in which aging pores are conspicuous is set as evaluation value 3, a group in which aging pores are not conspicuous is set as evaluation value 1, and the remaining groups are set as evaluation value 2. To do.
The “color illuminance group” of the “color illuminance group, luminance group, or lightness group obtained from the skin image” and “color illuminance group, luminance group, or lightness group from the skin image” are RGB color specifications. Numeric values of illuminance (intensity) such as red (R), green (G), blue (B) in the system (for example, 0 (black) to 255 (white)) group, cyan (C) in the CMYK color system, It means a group of numerical values of illuminance (intensity) such as magenta (M), yellow (Y), black (B). The “luminance group” means a numerical value group of luminance (Y) in the YUV color system and the like, and a numerical value group of luminance (L) in the HLS color system, and the “lightness group” means the Munsell color specification. It means a numerical value group of brightness (V) in a system or the like.
Furthermore, the “numerical value” of “a numerical value including a variation coefficient, geometric average, or harmonic average of color illuminance group, luminance group, or lightness group” is a direct numerical value such as “saturation” obtained from a skin image, Or it means numerical values such as “average value” and “maximum value” obtained by statistically processing these numerical values, and “coefficient of variation of color illuminance group”, “geometric average of color illuminance group”, “ "Harmonic average of color illuminance group", "Coefficient of variation of luminance group", "Geometric average of luminance group", "Harmonic average of luminance group", "Coefficient of variation of lightness group", "Geometric average of lightness group", or As long as it includes “harmonic average of brightness group”, it means that other numerical values are not particularly limited.
（第１工程）
本発明の鑑別方法は、「被験者又は前記被験者の肌画像から得た加齢毛穴の目立ちの目視評価値を目的変数とし、前記被験者の肌画像から得た色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を説明変数として得られる回帰式を準備する第１工程」を含むことを特徴とするが、回帰式を準備する具体的な方法は特に限定されない。
例えば、加齢毛穴の目立ちの目視評価値等を取得し、回帰分析を行って回帰式を得るほか、他者から回帰式を入手すること、或いは従前に使用した回帰式をそのまま又は改変して再利用しようとすること等も「回帰式を準備する」ことに含まれる。
(First step)
The discrimination method of the present invention is as follows: “A visual evaluation value of conspicuous aging pores obtained from a subject or a skin image of the subject is an objective variable, and an illuminance group, a luminance group, or a lightness of a color obtained from the subject skin image. Including a first step of preparing a regression equation obtained by using numerical values including a group variation coefficient, a geometric mean, or a harmonic mean as explanatory variables, but the specific method for preparing the regression equation is particularly limited. Not.
For example, obtain a visual evaluation value of conspicuous aging pores, etc., and perform regression analysis to obtain a regression equation, obtain a regression equation from another person, or modify or modify a previously used regression equation Trying to reuse is also included in “preparing a regression equation”.
第１工程において、回帰式を準備するための被験者の数、加齢毛穴の目立ちの目視評価値を得る方法、評価値の段階数、肌画像を得る手段、肌画像の撮像箇所、肌画像の種類、肌画像の倍率、肌画像の画素数、数値の種類、回帰式の種類等は、特に限定されず、目的に応じて適宜選択することができる。
被験者の数は、多い方が好ましいが、通常１０以上、好ましくは２０以上である。
加齢毛穴の目立ちの目視評価値を得る方法としては、図４に示すような加齢毛穴の目立ちについて段階分けされた基準写真を参考にして、評価者が評価値を付与していく方法が挙げられる。評価者は、美容、エステティック、又は肌評価等の研究に１年以上携わった経験を有し、さらに継続的に肌評価の訓練を行っている者であることが好ましい。また、評価値は、複数回評価を行う及び／又は複数の評価者によって行い、得られた評価値の平均を評価値としてもよい。この場合、評価の回数や評価者の数は、２以上であることが好ましく、３以上であることがより好ましい。
評価値の段階数は、通常３段階以上であり、通常１０段階以下、好ましくは５段階以下である。なお、評価値となる数値は、正の整数を用いることが好ましく、例えば３段階とする場合は（１、２、３）が、５段階とする場合は（１、２、３、４、５）、１０段階とする場合は（１、２、３、４、５、６、７、８、９、１０）を用いることが挙げられる。
肌画像を得る手段は、カラーデジタルカメラ、カラービデオカメラ等の公知の撮像機器が挙げられる。また、肌画像は、撮像機器から得られたそのままの肌画像を使用するほか、コンピューターに肌画像のデータを取り込み、画像解析ソフト等を使用して、ノイズの除去や平滑化等の処理を行った画像であってもよい。画像解析ソフトとしては、三谷商事株式会社のＷｉｎＲＯＯＦ（登録商標）、アドビシステムズ社のＡｄｏｂｅ Ｐｈｏｔｏｓｈｏｐ（登録商標）、ナノシステム株式会社のＮａｎｏＨｕｎｔｅｒ ＮＳ２Ｋ−Ｐｒｏ（登録商標）等が挙げられる。
肌画像の撮像箇所は、毛穴が確認することができる箇所であれば特に限定されないが、
図１に示すような頬部を含む肌画像であることが好ましい。
肌画像の種類は、「色の照度」、「輝度」、又は「明度」の何れかの数値を取得できる表色系であれば、ＲＧＢ、ＹＵＶ、Ｙｘｙ、マンセル（ＨＶＣ）、Ｌ＊ａ＊ｂ＊、Ｌ＊Ｃ＊ｈ＊、Ｌａｂ等の何れの表色系であってもよい。
肌画像の倍率は、通常０．１倍以上、好ましくは０．３倍以上、より好ましくは０．５倍以上であり、通常５０倍以下、好ましくは３０倍以下、より好ましくは２０倍以下である。
肌画像の画素数は、通常５０×５０画素（ドット、ピクセル）以上、好ましくは８０×８０画素（ドット、ピクセル）以上、より好ましくは１００×１００画素（ドット、ピクセル）以上である。
数値は、色の照度群の変動係数、色の照度群の幾何平均、色の照度群の調和平均、輝度群の変動係数、輝度群の幾何平均、輝度群の調和平均、明度群の変動係数、明度群の幾何平均、又は明度群の調和平均のほかに、色の照度群の最大値、色の照度群の最小値、色の照度群の中央値、色の照度群の最頻値、色の照度群の平均値、色の照度群の標準偏差、輝度群の最大値、輝度群の最小値、輝度群の中央値、輝度群の最頻値、輝度群の平均値、輝度群の標準偏差、明度群の最大値、明度群の最小値、明度群の中央値、明度群の最頻値、明度群の平均値、明度群の標準偏差等の色の照度群、輝度群、又は明度群を統計的に処理して得られる数値が挙げられる。また、肌画像の表色系に応じて、彩度等の数値を含むものであってもよく、さらにこれらの数値を統計的に処理して得られる数値（最大値、最小値、中央値、最頻値、平均値、標準偏差、変動係数、幾何平均（相乗平均）、調和平均等）を含むものであってもよい。
回帰式の種類は、説明変数として色の照度群の変動係数、色の照度群の幾何平均、色の照度群の調和平均、輝度群の変動係数、輝度群の幾何平均、輝度群の調和平均、明度群の変動係数、明度群の幾何平均、又は明度群の調和平均の何れか１つを使用する単回帰分析によって得られる回帰式であっても、説明変数として色の照度群の変動係数等やそれ以外の複数の数値も使用する重回帰分析によって得られる回帰式であっても、或いは主成分回帰分析（ＰＣＲ）、ＰＬＳ等の公知の回帰分析を使用して得られる回帰式であってもよい。
In the first step, the number of subjects for preparing a regression equation, a method for obtaining a visual evaluation value of conspicuous aging pores, the number of stages of evaluation values, a means for obtaining a skin image, an imaging location of a skin image, a skin image The type, the magnification of the skin image, the number of pixels of the skin image, the type of numerical values, the type of regression equation, and the like are not particularly limited and can be appropriately selected according to the purpose.
The number of subjects is preferably large, but is usually 10 or more, preferably 20 or more.
As a method of obtaining the visual evaluation value of the conspicuousness of the aging pores, there is a method in which the evaluator assigns the evaluation value with reference to the reference photographs classified in stages for the conspicuousness of the aging pores as shown in FIG. Can be mentioned. The evaluator is preferably a person who has more than one year of experience in research such as beauty, aesthetics, or skin evaluation, and that is continuously training in skin evaluation. The evaluation value may be evaluated a plurality of times and / or by a plurality of evaluators, and an average of the obtained evaluation values may be used as the evaluation value. In this case, the number of evaluations and the number of evaluators are preferably 2 or more, and more preferably 3 or more.
The number of stages of evaluation values is usually 3 or more, usually 10 or less, preferably 5 or less. In addition, it is preferable to use a positive integer as a numerical value as an evaluation value. For example, (1, 2, 3) is set to 3 levels, and (1, 2, 3, 4, 5) is set to 5 levels. ) In the case of 10 steps, (1, 2, 3, 4, 5, 6, 7, 8, 9, 10) may be used.
Examples of means for obtaining a skin image include known imaging devices such as a color digital camera and a color video camera. In addition to using the skin image obtained from the imaging device as it is, the skin image is imported into the computer and processed with noise removal and smoothing using image analysis software. It may be an image. Examples of the image analysis software include WinROOF (registered trademark) of Mitani Corporation, Adobe Photoshop (registered trademark) of Adobe Systems, NanoHunter NS2K-Pro (registered trademark) of Nanosystem Corporation, and the like.
The imaging location of the skin image is not particularly limited as long as the pore can be confirmed,
A skin image including a cheek as shown in FIG. 1 is preferable.
The skin image type is RGB, YUV, Yxy, Munsell (HVC), L * a * as long as the color system can acquire any value of “color illuminance”, “luminance”, or “lightness” . Any color system such as b * , L * C * h * , or Lab may be used.
The magnification of the skin image is usually 0.1 times or more, preferably 0.3 times or more, more preferably 0.5 times or more, usually 50 times or less, preferably 30 times or less, more preferably 20 times or less. is there.
The number of pixels of the skin image is usually 50 × 50 pixels (dots, pixels) or more, preferably 80 × 80 pixels (dots, pixels) or more, more preferably 100 × 100 pixels (dots, pixels) or more.
The numerical values are the variation coefficient of color illuminance group, geometric mean of color illuminance group, harmonic mean of color illuminance group, variation coefficient of luminance group, geometric mean of luminance group, harmonic mean of luminance group, variation coefficient of lightness group In addition to the geometric mean of the lightness group, or the harmonic mean of the lightness group, the maximum value of the color illumination group, the minimum value of the color illumination group, the median value of the color illumination group, the mode value of the color illumination group, Average value of color illuminance group, standard deviation of color illuminance group, maximum value of luminance group, minimum value of luminance group, median value of luminance group, mode value of luminance group, average value of luminance group, luminance group Standard deviation, brightness group maximum, brightness group minimum, brightness group median, brightness group mode, brightness group average, brightness group standard deviation, etc. Examples include numerical values obtained by statistically processing the brightness group. Further, depending on the color system of the skin image, it may include numerical values such as saturation, and further numerical values obtained by statistically processing these numerical values (maximum value, minimum value, median value, Mode value, average value, standard deviation, coefficient of variation, geometric mean (geometric mean), harmonic mean, etc.).
The types of regression equations are as follows: variation coefficient of color illuminance group, geometric mean of color illuminance group, harmonic mean of color illuminance group, variation coefficient of luminance group, geometric mean of luminance group, harmonic mean of luminance group Even if it is a regression equation obtained by a single regression analysis using any one of the coefficient of variation of the lightness group, the geometric mean of the lightness group, or the harmonic mean of the lightness group, the coefficient of variation of the color illuminance group as an explanatory variable Or a regression equation obtained by multiple regression analysis using a plurality of other numerical values, or a regression equation obtained by using a known regression analysis such as principal component regression analysis (PCR) or PLS. May be.
（第２工程）
本発明の鑑別方法は、「鑑別対象者の肌画像から色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を得る第２工程」を含むことを特徴とするが、肌画像を得る手段、肌画像の撮像箇所、肌画像の種類、肌画像の倍率、肌画像の画素数等は、第１工程と同様のものが挙げられる。また、数値の種類は、準備した回帰式に合わせて取得することが好ましい。
(Second step)
The discrimination method of the present invention includes a “second step of obtaining a numerical value including a variation coefficient, a geometric average, or a harmonic average of a color illuminance group, a luminance group, or a lightness group from a skin image of a discrimination target person”. However, the means for obtaining the skin image, the imaging location of the skin image, the type of the skin image, the magnification of the skin image, the number of pixels of the skin image, and the like are the same as those in the first step. Moreover, it is preferable to acquire the kind of numerical value according to the prepared regression equation.
（第３工程）
本発明の鑑別方法は、「前記第２工程で得た前記数値を、前記第１工程で準備した前記回帰式に代入し、算出された数値を前記鑑別対象者の加齢毛穴の目立ちの評価値として決定する第３工程」を含むことを特徴とするが、数値を回帰式に代入して評価値を算出する具体的手順は特に限定されない。
例えば、準備した回帰式が説明変数として色の照度群の変動係数、色の照度群の幾何平均、色の照度群の調和平均、輝度群の変動係数、輝度群の幾何平均、輝度群の調和平均、明度群の変動係数、明度群の幾何平均、又は明度群の調和平均の何れか１つを使用する単回帰分析によって得られた回帰式である場合、回帰式は下記式（１）のように表すことができる（式（１）中のａとｂは、回帰分析によって具体的な数値が得られている。）。
ｙ＝ａｘ＋ｂ （１）
ｘに鑑別対象者の肌画像から得た色の照度群の変動係数等を代入して、ｙとして鑑別対象者の加齢毛穴の目立ちの評価値が得られるのである。
また、準備した回帰式が説明変数として色の照度群の変動係数等やそれ以外の複数の数
値も使用する重回帰分析によって得られる回帰式である場合、回帰式は下記式（２）のように表すことができる（式（２）中のａ１、ａ２、ａ３、ａｉ等は、回帰分析によって具体的な数値が得られている。）。
ｙ＝ａ１ｘ１＋ａ２ｘ２＋ａ３ｘ３＋・・・ａｉｘｉ （２）
ｘ１、ｘ２、ｘ３、ｘｉ等に肌の鑑別対象者の肌画像から得た色の照度群の変動係数等をそれぞれ代入して、ｙとして鑑別対象者の毛穴の目立ちの評価値が得られるのである。
なお、数値を回帰式に代入して評価値を算出する方法は、手計算であっても、コンピューター等を利用したものであってもよい。
(Third step)
The identification method of the present invention is as follows: “Substituting the numerical value obtained in the second step into the regression equation prepared in the first step, and evaluating the conspicuousness of the age-related pores of the identification subject. The third step of determining as a value ”is included, but a specific procedure for calculating an evaluation value by substituting a numerical value into a regression equation is not particularly limited.
For example, the prepared regression equation is the variation coefficient of the color illuminance group, the geometric mean of the color illuminance group, the harmonic mean of the color illuminance group, the coefficient of variation of the luminance group, the geometric mean of the luminance group, the harmony of the luminance group When the regression equation is obtained by a single regression analysis using any one of the average, the coefficient of variation of the lightness group, the geometric mean of the lightness group, or the harmonic mean of the lightness group, the regression equation is represented by the following equation (1): (A and b in the formula (1) have specific numerical values obtained by regression analysis).
y = ax + b (1)
By substituting the variation coefficient of the illuminance group of the color obtained from the skin image of the discrimination target person into x, the evaluation value of the conspicuousness of the age-related pores of the discrimination target person is obtained as y.
In addition, when the prepared regression equation is a regression equation obtained by multiple regression analysis that uses the variation coefficient of the color illuminance group as an explanatory variable and other numerical values, the regression equation is as shown in the following equation (2). (A 1 , a 2 , a 3 , a i, etc. in the formula (2) have specific numerical values obtained by regression analysis).
y = a 1 x 1 + a 2 x 2 + a 3 x 3 +... a i x i (2)
x 1, x 2, x 3 , x i , etc. on the skin of the discrimination subject's obtained from the skin image colors of illumination groups coefficient of variation or the like are substituted, respectively, evaluation value of the appearance of discrimination subject pores as y Is obtained.
The method for calculating the evaluation value by substituting the numerical value into the regression equation may be manual calculation or using a computer or the like.
本発明の鑑別方法は、加齢毛穴の目立ちを評価する方法であるが、その用途は特に限定されず、得られる加齢毛穴の目立ちの評価値を応用して、加齢毛穴の進行状況や化粧料の加齢毛穴の隠し効果を評価するために利用してもよい。
例えば、加齢毛穴の目立ちの評価値を年齢毎に分類して、年齢毎の標準値を設定し、対象者の加齢毛穴の目立ちの評価値とその標準値とを比較して、対象者の加齢毛穴の進行状況を評価する評価方法が挙げられる。
また、化粧料を塗布する前の加齢毛穴の目立ちの評価値と化粧料を塗布した後の加齢毛穴の目立ちの評価値とを比較して、化粧料の加齢毛穴の隠し効果を評価する評価方法が挙げられる。なお、本発明の鑑別方法を利用した上記の化粧料の評価方法も本発明に一態様である。以下、化粧料の評価方法について、詳細に説明する。
The differentiation method of the present invention is a method for evaluating the conspicuousness of aging pores, but its use is not particularly limited, and by applying the evaluation value of conspicuous aging pores obtained, the progress of aging pores and You may utilize in order to evaluate the concealment effect of the aging pore of cosmetics.
For example, the evaluation value of conspicuousness of aging pores is classified for each age, a standard value for each age is set, the evaluation value of conspicuousness of aging pores of the subject is compared with the standard value, and the subject An evaluation method for evaluating the progress of the aging pores is mentioned.
Also, compare the evaluation value of conspicuous aging pores before applying cosmetics with the evaluation value of conspicuous aging pores after applying cosmetics, and evaluate the concealing effect of aging pores of cosmetics The evaluation method to do is mentioned. The cosmetic evaluation method using the identification method of the present invention is also an aspect of the present invention. Hereinafter, the cosmetic evaluation method will be described in detail.
＜化粧料の評価方法＞
本発明の一態様である化粧料の評価方法は、化粧料の加齢毛穴の隠し効果を評価する方法であり、下記（１’）〜（３’）の工程を含むことを特徴とする。
（１’）請求項１に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布する前の被験者の加齢毛穴の目立ちの評価値を得る第１’工程。
（２’）請求項１に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布した後の被験者の加齢毛穴の目立ちの評価値を得る第２’工程。
（３’）前記第１’工程で得た前記評価値と前記第２’工程で得た前記評価値を比較して、加齢毛穴の目立ちが抑制されていた場合、前記化粧料には加齢毛穴の隠し効果がある決定する第３’工程。
なお、「加齢毛穴の目立ちが抑制されていた」とは、例えば加齢毛穴の目立ちの評価値が大きいほど加齢毛穴が目立ちにくいとする回帰式を使用する場合、第２’工程で得た評価値が第１’工程で得た評価値よりも大きいと、加齢毛穴の目立ちが抑制されていたと判断することであり、逆に加齢毛穴の目立ちの評価値が小さいほど加齢毛穴が目立ちにくいとする回帰式を使用する場合、第２’工程で得た評価値が第１’工程で得た評価値よりも小さいと、加齢毛穴の目立ちが抑制されていたと判断することを意味するものとする。
<Cosmetics evaluation method>
The cosmetic evaluation method according to one embodiment of the present invention is a method for evaluating the effect of concealing aging pores of cosmetics, and includes the following steps (1 ′) to (3 ′).
(1 ') The 1' process which obtains the evaluation value of the conspicuousness of the test subject's aging pore before apply | coating the said cosmetics by the identification method of the aging pore of Claim 1.
(2 ') The 2' process which obtains the evaluation value of the conspicuousness of the test subject's aging pore after apply | coating the said cosmetics by the identification method of the aging pore of Claim 1.
(3 ′) When the evaluation value obtained in the first ′ step and the evaluation value obtained in the second ′ step are compared, and the conspicuousness of aging pores is suppressed, The third step for determining the effect of concealing the pores of age.
“Aging pores were not conspicuous” means that, for example, when using a regression equation that indicates that the aging pores are less noticeable as the evaluation value of the aging pores is larger, it is obtained in the 2 ′ step. If the evaluation value is larger than the evaluation value obtained in the first step, it is determined that the conspicuousness of the aging pores has been suppressed. Conversely, the smaller the evaluation value of the conspicuous aging pores, the aging pores. When using a regression equation that makes it difficult to stand out, if the evaluation value obtained in the 2 ′ step is smaller than the evaluation value obtained in the 1 ′ step, it is determined that the conspicuousness of the aging pores has been suppressed Shall mean.
本発明の化粧料の評価方法は、化粧料には加齢毛穴の隠し効果があるとする定性的な評価のみならず、化粧料の加齢毛穴の隠し効果を定量的に評価するものであってもよい。例えば、第２’工程で得た評価値と第１’工程で得た評価値の差がより大きいほど、化粧料の加齢毛穴の隠し効果が大きいと判断することが挙げられる。 The cosmetic evaluation method of the present invention quantitatively evaluates not only the qualitative evaluation that cosmetics have the effect of concealing aging pores but also the concealment effect of aging pores of cosmetics. May be. For example, it may be determined that the greater the difference between the evaluation value obtained in the 2 ′ step and the evaluation value obtained in the 1 ′ step, the greater the effect of concealing the aging pores of the cosmetic.
以下に実施例及び比較例を挙げて本発明をさらに具体的に説明するが、本発明の趣旨を逸脱しない限り適宜変更することができる。従って、本発明の範囲は以下に示す具体例により限定的に解釈されるべきものではない。 Hereinafter, the present invention will be described more specifically with reference to examples and comparative examples, but can be appropriately changed without departing from the gist of the present invention. Accordingly, the scope of the present invention should not be construed as being limited by the specific examples shown below.
＜実施例１：加齢毛穴の鑑別＞
（回帰式の準備（第１工程））
１０代〜５０代の女性パネラー（被験者）６２人の素肌の状態の肌画像（図１に示すよ
うな頬部を含む肌画像）を使用し、それぞれのパネラーの加齢毛穴の目立ちを５段階に分類して、それぞれの目視評価値とした。なお、肌画像を得るための撮影は、光源としてＤ６５を用い、測定部位からカメラまでの距離を一定とし、さらに撮影条件を全て統一して行った。また、目視評価は図４に示す基準写真と下記の表１の評価基準を参考に分類した。
(Preparation of regression equation (first step))
Using skin images of the skin of 62 female panelists (subjects) in their teens to 50s (skin images including the cheeks as shown in FIG. 1), each paneler has five stages of conspicuous aging pores. The visual evaluation values were obtained. The photographing for obtaining the skin image was performed using D65 as the light source, keeping the distance from the measurement site to the camera constant, and further unifying all photographing conditions. Moreover, visual evaluation classified according to the reference | standard photograph shown in FIG. 4, and the evaluation criteria of following Table 1. FIG.
次に、これらの肌画像（Ｐｈｏｔｏｓｈｏｐ ＣＳ６４ ＲＧＢ、画素数：１００×１００ピクセル）から図１に示す領域（一定の面積）の青（Ｂ）の照度データを取得して、青（Ｂ）の照度群の変動係数を算出した（変動係数＝標準偏差／平均値）。
そして、加齢毛穴の目立ちの目視評価値と青（Ｂ）の照度群の変動係数を解析ソフトＪＭＰ１０を使用して多変量解析（回帰分析）を行った結果、下記式（３）が得られ、決定係数Ｒ２は０．５６０５となった。なお、加齢毛穴の目立ちの目視評価値を横軸とし、青（Ｂ）の照度群の変動係数を縦軸としてプロットしたグラフを図５に示す。
ｙ＝４０．１ｘ−０．６７ （３）
これらの結果から、加齢毛穴の目立ちの目視評価値と照度群の変動係数とは、相関性が高いこと明らかである。
Next, the blue (B) illuminance data of the region (constant area) shown in FIG. 1 is acquired from these skin images (Photoshop CS64 RGB, number of pixels: 100 × 100 pixels), and the illuminance of blue (B) is obtained. The group coefficient of variation was calculated (variation coefficient = standard deviation / average value).
And as a result of performing multivariate analysis (regression analysis) using the analysis software JMP10, the visual evaluation value of the conspicuous aging pores and the variation coefficient of the illuminance group of blue (B), the following formula (3) is obtained. , the coefficient of determination R 2 was 0.5605. In addition, the graph which plotted with the horizontal axis | shaft the visual evaluation value of conspicuous aging pores and making the vertical axis | shaft the variation coefficient of the illumination intensity group of blue (B) is shown in FIG.
y = 40.1x-0.67 (3)
From these results, it is clear that the visual evaluation value of conspicuous aging pores and the variation coefficient of the illuminance group have a high correlation.
（鑑別対象者の色の照度群の変動係数の取得（第２工程））
４人の女性パネラー（パネラーＡ〜Ｄ）の色の照度の変動係数を、前述の「回帰式の準備（第１工程）」と同様の方法により取得した。
(Acquisition of coefficient of variation of illuminance group of identification target person's color (second step))
The variation coefficient of the illuminance of the color of the four female panelists (panelists A to D) was obtained by the same method as the above-mentioned “Preparation of regression equation (first step)”.
（鑑別対象者の加齢毛穴の目立ちの評価値の決定（第３工程））
得られた青（Ｂ）の照度群の変動係数を式（３）に代入して、女性パネラーＡ〜Ｄの加齢毛穴の目立ちの評価値をそれぞれ決定した。結果を表２に示す。
なお、女性パネラーＡ〜Ｄの加齢毛穴の目立ちを、前述の「回帰式の準備（第１工程）」と同様に５段階の目視評価値で別途評価した（目視評価は３回行った平均値である。）。同じく結果を表２に示す。
The obtained coefficient of variation of the blue (B) illuminance group was substituted into Equation (3) to determine the evaluation values of the conspicuous aging pores of female panelists A to D, respectively. The results are shown in Table 2.
In addition, the conspicuousness of the aging pores of female panelists A to D was separately evaluated with the five-stage visual evaluation values in the same manner as the above-mentioned “Preparation of regression equation (first step)” (visual evaluation was an average of three times. Value.) Similarly, the results are shown in Table 2.
表２より、式（３）を使用して決定された加齢毛穴の目立ちの評価値が、目視評価値を
精度良く再現していることが明らかである。
From Table 2, it is clear that the conspicuous evaluation value of the aging pores determined using the formula (3) accurately reproduces the visual evaluation value.
＜実施例２：化粧料の加齢毛穴の隠し効果を評価＞
以下に示す工程に従って、オイルゲル化粧料（シリコーン練りこみ剤型）を調製した。油剤、粉体を表３に示す割合にて手攪拌にて混合した後、自転・公転ミキサーを使用し、２０００ｒｐｍの回転数で一定時間混合した。
Oil gel cosmetics (silicone kneading agent type) were prepared according to the following steps. The oil agent and powder were mixed by hand stirring at the ratio shown in Table 3, and then mixed for a certain time at a rotation speed of 2000 rpm using a rotation / revolution mixer.
次に調製したオイルゲル化粧料（シリコーン練りこみ剤型）を、前述の女性パネラーＡ〜Ｄにそれぞれ塗布し、肌画像を撮像して、前述の「鑑別対象者の色の照度群の変動係数の取得（第２工程）」と同様の方法により、色の照度群の変動係数を取得した。得られた色の照度群の変動係数を式（３）に代入して、女性パネラーＡ〜Ｄの化粧料の塗布後の加齢毛穴の目立ちの評価値をそれぞれ決定した。結果を表４に示す。なお、女性パネラーＡ〜Ｄの化粧料の塗布後の加齢毛穴の目立ちを、前述の「回帰式の準備（第１工程）」と同様に５段階の目視評価値で別途評価した（目視評価は３回行った平均値である。）。同じく結果を表４に示す。
表４より、オイルゲル化粧料（シリコーン練りこみ剤型）を塗布したことによって、加齢毛穴の目立ちが抑制されており、オイルゲル化粧料（シリコーン練りこみ剤型）に加齢毛穴の隠し効果があることが明らかである。 From Table 4, by applying the oil gel cosmetic (silicone kneading agent type), the conspicuousness of the aging pores is suppressed, and the oil gel cosmetic (silicone kneading agent type) has the effect of concealing the aging pores. It is clear.
本発明の鑑別方法は、加齢毛穴の進行状況や化粧料の加齢毛穴の隠し効果を評価するために利用することができる。 The discrimination method of the present invention can be used to evaluate the progress of aging pores and the effect of concealing aging pores in cosmetics.
Claims (2)
（１）被験者又は前記被験者の肌画像から得た、加齢毛穴の目立ちの目視評価値を目的変数とし、前記被験者の肌画像から得た色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を説明変数として得られる回帰式を準備する第１工程、
（２）鑑別対象者の肌画像から色の照度群、輝度群、若しくは明度群の変動係数、幾何平均、又は調和平均を含む数値を得る第２工程、及び
（３）前記第２工程で得た前記数値を、前記第１工程で準備した前記回帰式に代入し、算出された数値を前記鑑別対象者の加齢毛穴の目立ちの評価値として決定する第３工程
を含むことを特徴とする、加齢毛穴の鑑別方法。 A method for differentiating aging pores to evaluate the conspicuousness of aging pores,
(1) was obtained from the skin image of the subject or the subject, the objective variable visual evaluation value of noticeable aging pores, illuminance group color obtained from the skin image of the subject, the brightness group, or the coefficient of variation of brightness groups A first step of preparing a regression equation obtained with numerical values including geometric mean or harmonic mean as explanatory variables;
(2) a second step of obtaining a numerical value including a variation coefficient, a geometric average, or a harmonic average of a color illuminance group, a luminance group, or a lightness group from the skin image of the person to be identified; and (3) obtained in the second step. The numerical value is substituted into the regression equation prepared in the first step, and the calculated numerical value is included as an evaluation value of the conspicuousness of the age-related pores of the discrimination target person, and includes a third step. , How to differentiate aging pores.
（１’）請求項１に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布する前の被験者の加齢毛穴の目立ちの評価値を得る第１’工程、
（２’）請求項１に記載の加齢毛穴の鑑別方法によって、前記化粧料を塗布した後の被験者の加齢毛穴の目立ちの評価値を得る第２’工程、及び
（３’）前記第１’工程で得た前記評価値と前記第２’工程で得た前記評価値を比較して、加齢毛穴の目立ちが抑制されていた場合に、前記化粧料には加齢毛穴の隠し効果がある決定する第３’工程
を含むことを特徴とする、化粧料の評価方法。 A cosmetic evaluation method for evaluating the concealment effect of cosmetic aging pores,
(1 ′) a first ′ step of obtaining an evaluation value of the conspicuousness of the subject's aging pores before applying the cosmetic by the method for distinguishing aging pores according to claim 1;
(2 ′) a second step of obtaining an evaluation value of conspicuous aging pores of the subject after applying the cosmetic by the method for distinguishing aging pores according to claim 1, and (3 ′) When the evaluation value obtained in the 1 ′ step and the evaluation value obtained in the 2 ′ step are compared and the conspicuousness of the aging pores is suppressed, the cosmetics have a concealing effect on the aging pores. A method for evaluating cosmetics, comprising the step of determining 3 ′.
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