JP6883943B2 - Evaluation method, evaluation device and program - Google Patents

Description

The present invention relates to an evaluation method, an evaluation device, and a program for how to spread wetness of cosmetics.

In the field of cosmetics, a method for objectively evaluating cosmetics and skin condition has been proposed.

In Patent Document 1, the volatile component of the cosmetic is volatilized, the change in mass of the evaluation sample with time is measured, and the ratio of the volatile component to the mass of the non-volatile component is a predetermined value. A method for evaluating the moisturizing property of a cosmetic product, which includes a step of determining the moisturizing property of the cosmetic product based on the drying speed and the magnitude thereof, is disclosed.

Patent Document 2 discloses a skin condition evaluation method for quantitatively evaluating a human skin condition. In the skin condition evaluation method, a plurality of liquids having different surface tensions are dropped on the skin of a subject. Then, the type of the limit liquid that wets the skin surface and spreads is specified from the shape of the dropped liquid on the skin, and the skin condition of the subject is determined from the type of the specified liquid.

Japanese Unexamined Patent Publication No. 2014-21930 Japanese Unexamined Patent Publication No. 2005-329008

On the other hand, consumers' demands for cosmetics have diversified in recent years, and in addition to the effects of cosmetics such as moisturizing properties, cosmetics having a better usability have been demanded. One of the feelings of use is the wet spread of cosmetics. However, a technique for quantitatively evaluating the wet spread of this cosmetic has not been established. The technique of the invention of Patent Document 1 is an invention relating to an evaluation method of moisturizing property, and the invention of Patent Document 2 is an invention relating to an evaluation method of skin condition and does not provide the technique. The present invention relates to a technique for quantifying how a cosmetic is wet and spread.

According to the present invention
An image data acquisition process for acquiring image data of a plurality of frames obtained by photographing the cosmetics dropped on the dropping object over a predetermined time, and
An analysis step of calculating data indicating the amount of change in the image between the two frames, and
Based on the calculation result in the analysis step, data showing the transition of the change amount of the image between two temporally continuous frames and / or the data showing the transition of the cumulative value of the change amount of the image are output. Output process and
A method for evaluating how to spread the wetness of a cosmetic having the above is provided.

Further, according to the present invention.
An image data acquisition unit that acquires image data of a plurality of frames of the cosmetics dropped on the dropping object over a predetermined time, and an image data acquisition unit.
An analysis unit that calculates data indicating the amount of change in the image between the two frames,
Based on the calculation result in the analysis unit, an output that outputs data showing the transition of the amount of change in the image between the frames that are continuous in time and / or data showing the transition of the cumulative value of the amount of change in the image. Department and
An evaluation device for evaluating how to spread the wetness of the cosmetic having the above is provided.

Further, according to the present invention.
Computer,
An image data acquisition means for acquiring image data of a plurality of frames in which cosmetics dropped on a drop target are photographed over a predetermined time.
An analysis means for calculating data indicating the amount of change in an image between two frames.
Output that outputs data showing the transition of the amount of change in the image between the frames that are continuous in time and / or data showing the transition of the cumulative value of the amount of change in the image based on the calculation result in the analysis means. means,
A program is provided to evaluate how the cosmetics that function as a wet spread spread.

According to the present invention, a technique for quantifying how a cosmetic is wet and spread is realized.

It is a flowchart which shows an example of the processing flow of this embodiment. This is an example of a functional block diagram of the evaluation device of the present embodiment. It is a figure which shows an example of the hardware composition of the evaluation apparatus of this embodiment. It is a figure which shows an example of the image data of this embodiment schematically. It is a figure for demonstrating the processing of the analysis part of this embodiment. This is an output example by the output unit of this embodiment. This is an output example by the output unit of this embodiment. This is an output example by the output unit of this embodiment. This is an output example by the output unit of this embodiment. It is a figure which shows an example of the image data of this embodiment schematically. It is a flowchart which shows an example of the process flow of the analysis process of this embodiment. It is a flowchart which shows an example of the process flow of the analysis process of this embodiment. This is an output example of the embodiment. This is an output example of the embodiment.

<First Embodiment>
First, the outline of the present embodiment will be described. In the present embodiment, the image data of a plurality of frames of the cosmetics dropped on the dropping object taken under predetermined conditions for a predetermined time is analyzed, and the transition of the amount of change in the image between two frames that are continuous in time is shown. Data and / or data showing the transition of the cumulative value of the amount of change in the image is output. Based on the output data, it is possible to evaluate how the cosmetics get wet and spread. Hereinafter, the configuration of the present embodiment will be described in detail.

FIG. 1 is a flowchart showing the flow of the evaluation method of the present embodiment. As shown in the figure, it has an image data acquisition step S10, an analysis step S20, and an output step S30. At least a part of these steps is performed by the evaluation device 10 shown in FIG. As shown in FIG. 2, the evaluation device 10 includes an image data acquisition unit 11, an analysis unit 12, and an output unit 13.

An example of the hardware configuration of the evaluation device 10 will be described with reference to FIG. As shown in FIG. 3, the evaluation device 10 includes a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. Peripheral circuits include various modules.

The bus 5A is a data transmission path for the processor 1A, the memory 2A, the peripheral circuits 4A, and the input / output interface 3A to transmit and receive data to and from each other. The processor 1A is, for example, an arithmetic processing unit such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The memory 2A is, for example, a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The input / output interface 3A includes an interface for transmitting / receiving information to / from another device. The processor 1A issues a command to each module and performs a calculation based on the calculation results thereof.

Hereinafter, each step shown in the flowchart of FIG. 1 will be described in detail.

In the image data acquisition step S10, image data of a plurality of frames obtained by photographing the cosmetics dropped on the dropping object over a predetermined time is acquired.

The image data acquisition step S10 includes at least one of an imaging step of capturing such image data and an input step of inputting the captured image data into the image data acquisition unit 11 of the evaluation device 10.

In the photographing process, the cosmetic is dropped onto the object to be dropped. Then, the cosmetic is photographed for a predetermined time, and image data of a plurality of frames is acquired. The dropping of the cosmetic may be performed using a predetermined device. In addition, the operator may perform the dropping using a tool such as a dropper or a micropipetta.

The type of object to be dropped is not particularly limited. For example, a living body, a substrate, or the like can be a dropping target. Examples of the substrate include, but are not limited to, a substrate made of glass, acrylic, silicone, urethane, or the like. The shape of the substrate is not particularly limited, but it may be, for example, a flat plate.

The cosmetics are objects for evaluating how to get wet and spread on the object to be dropped, and are liquid cosmetics such as solutions, gel cosmetics, cream cosmetics, wax cosmetics, aerosol cosmetics and the like. The type is not particularly limited. In addition, a dye such as a dye (a color different from the object to be dropped) may be appropriately added to the cosmetic to color the cosmetic. In this case, from the viewpoint of obtaining a more accurate evaluation result, it is preferable to add a pigment having a color located on the opposite side of the hue circle from the skin color. For example, the color of the pigment to be added to the cosmetic and the skin. It is also a preferable method to have a complementary color relationship with the color of.

The amount of the cosmetic to be dropped onto the object to be dropped is a design matter, but is, for example, 1 to 10 μL. By using a dropper, a micropipetta, or the like, an appropriate amount of cosmetics can be dropped onto the object to be dropped.

Shooting can be performed using a camera capable of shooting moving images. The frame rate can be determined according to the cosmetic and the object to be dropped. The frame rate can be increased when the wet spread is fast, and the frame rate can be decreased when the wet spread is slow. Instead of shooting moving images, continuous shooting of still images may be performed at predetermined time intervals.

In addition, the shooting time can be determined according to the cosmetics and the object to be dropped. When the wet spread is fast, it converges to a certain state (eg, a state in which the wet spread has stopped or almost stopped) in a relatively short time from the dropping timing. When the wet spreading is slow, it converges to a state in which the wet spreading is stopped (eg, a state in which the wet spreading is stopped or almost stopped) within a relatively long time from the dropping timing. For example, the shooting time can be set so as to include the time until convergence.

The relative positional relationship (distance, orientation, etc.) between the camera and the dropping object is fixed during shooting. For example, it can be realized by fixing each of the camera and the dropping object at a predetermined position and taking a picture while maintaining the fixed state. In this way, the position of the dropping object in the frame photographed by the camera can be fixed across a plurality of frames.

The lens magnification of the camera, the distance between the camera and the object to be dropped, and the like may be adjusted so that the frame does not show anything other than the cosmetic and the object to be dropped.

In one processing example in the analysis step S20 described below, the correlation coefficient of the image between the two frames F is calculated, and this is used as data indicating the amount of change in the image. Then, the wet spread of the cosmetic is evaluated based on the data showing the amount of change in the image.

When something other than cosmetics and objects to be dropped (hereinafter, may be referred to as "other things") is shown in the frame and its state (position, shape, color, etc.) changes between the two frames, The calculated correlation coefficient includes a change component in which the other is changed. It is not appropriate to evaluate how the cosmetics get wet and spread based on the data showing the amount of change in the image. The inconvenience can be avoided if adjustments are made so that objects other than the cosmetic and the object to be dropped are not reflected in the frame.

Further, in one processing example in the analysis step S20 described below, an area in which the cosmetics are reflected is extracted from the frame. If the frame is adjusted so that objects other than the cosmetic and the object to be dropped are not reflected in the frame, the process of extracting the area in which the cosmetic is reflected from the frame becomes easy.

It should be noted that, instead of the technique of adjusting the camera or the like so that objects other than cosmetics and dripping objects are not captured in the frame, a technique of processing only a part of the frame in the analysis step S20 may be adopted. Good. The same effect can be obtained by selecting the area to be treated so that the area other than the cosmetic and the object to be dropped does not appear in the area to be treated.

As the illumination light at the time of shooting, it is preferable to use a light that does not cause flicker. For example, halogen lamps, xenon lamps, LEDs and the like can be mentioned. Further, by installing polarizing plates on both the illumination light side and the camera side and crossing these polarization directions, it is possible to cut the specularly reflected light.

Here, FIG. 4 schematically shows an example of image data. Images of each of the plurality of frames F are shown. In association with each frame, imaging timing _{t i (1 ≦ i ≦ m} ; i is a positive integer indicating the i-th imaging frame, m is a positive integer indicating the shooting last captured frame) is shown There is. The value of i increases with the passage of time.

Only the object D to be dropped and the cosmetic C are shown in each frame F. Cosmetic C is simply represented by a circle both before and after it gets wet and spreads. The size of the circle shows that it is getting wet and spreading.

In the input step, the image data obtained in the photographing step is input to the image data acquisition unit 11 of the evaluation device 10. As a result, the image data acquisition unit 11 of the evaluation device 10 shown in FIG. 1 can acquire the image data.

Returning to FIG. 1, in the analysis step S20, the analysis unit 12 of the evaluation device 10 calculates data indicating the amount of change in the image between the two frames.

For example, the analysis unit 12 may create a plurality of pairs in two temporally continuous frames, and calculate data indicating the amount of change in the image between the two frames for each pair.

If to be processed of m frame F shown in FIG. 4, analyzer 12 includes a frame F of the imaging timing t _a, create multiple pairs between frame F of the imaging timing _{t a + 1 (1 ≦ a} ≦ m-1; a is a positive integer indicating the a-th shooting frame), and data indicating the amount of change in the image between the two frames F is calculated for each pair.

In the case of this example, the analysis unit 12 can generate time-series data of the amount of change in the image between two frames that are continuous in time. The time-series data is data showing the transition of the amount of change in the image between two frames that are continuous in time.

The analysis unit 12 first accumulates the "time-series data of the amount of change in the image between two temporally continuous frames" obtained as described above in chronological order. (in the case of FIG. 4, the frame F of the imaging timing t ₁₎ of the frame can be generated time-series data of the image variation amount of the cumulative value relative to the of. The time-series data is data showing the transition of the cumulative value of the amount of change in the image.

As another example, the analysis unit 12 creates a plurality of pairs in the first frame in time and each of the other frames, and calculates data indicating the amount of change in the image between the two frames for each pair. You may.

When the m frames F shown in FIG. 4 are to be processed, the analysis unit 12 has a plurality of pairs of the frame F at _{the shooting timing t 1} (the first frame in time) and _{the frame F at the shooting timing t b.} (2 ≦ b ≦ m; b is a positive integer indicating the b-th shooting frame), and data indicating the amount of change in the image between the two frames F is calculated for each pair.

In this example, the analysis unit 12 may generate time-series data of temporally (in the case of FIG. 4, the frame F of the imaging timing t ₁₎ the first frame image variation amount of the cumulative value relative to the in it can. The time-series data is data showing the transition of the cumulative value of the amount of change in the image.

Next, a process of calculating data indicating the amount of change in the image will be described. The analysis unit 12 can calculate the amount of change in the image between the two frames by using any conventional technique. Here, as data indicating the amount of change in the image, "the first calculation method for calculating the correlation coefficient between two frames" and "the amount of change in the area of the area where the makeup is reflected in each of the two frames are calculated. The second calculation method to be performed ”will be described.

"First calculation method for calculating the correlation coefficient between two frames"
As described above, when the relative positional relationship between the dripping object and the camera is fixed and only the dripping object and the cosmetic are shown in the processed image, the component whose appearance changes within the shooting time is Only cosmetics. Therefore, by calculating the amount of change in the image between the two frames, the amount of change in the cosmetics between the two frames can be calculated.

For example, the correlation coefficient between the images of the two frames can be used as data (index) indicating the amount of change in the image. If there is no change between the images in the two frames, the correlation coefficient is 1, and the larger the change, the smaller the correlation coefficient. Any technique can be adopted as the method for calculating the correlation coefficient, and an example will be described below.

First, the analysis unit 12 obtains a one-dimensional vector by arranging the pixel values of each of the plurality of pixels in a predetermined order for each frame. The order of arrangement may be the same among all frames, and the details are a matter of design. As a result, the data shown in FIG. 5 can be obtained. F _t1 is obtained by arranging the pixel values of a plurality of pixels of the frame F of the imaging timing t ₁ to a predetermined order.

A vector may be generated from the pixel values of all the pixels of each frame, or a vector may be generated from the pixel values of some pixels. For example, a vector may be generated by arranging the pixel values of pixels every other row or every other column. Considering the accuracy, it is preferable to use the pixel values of all the pixels. However, by reducing the number of pixels used, the processing load on the computer can be reduced, and effects such as shortening the processing time can be obtained. It can be appropriately designed according to the required accuracy, the desired processing time, and the like.

Further, in the case of the image data shown in FIG. 4, the wet and spread cosmetic C does not reach along the outer periphery of the frame F. When there is such a tendency, a vector may be generated by excluding the pixel values of the pixels along the outer circumference of each frame F.

After that, the analysis unit 12 creates a pair in two frames. The method of creating a pair is as described above.

After that, the analysis unit 12 calculates the correlation coefficient for each pair. The correlation coefficient can be calculated, for example, by dividing the inner product of two vectors by the product of the magnitudes of each of the two vectors.

"A second calculation method for calculating the amount of change in the area of the area where the cosmetics are reflected in each of the two frames"
From the image of each frame, the area where the cosmetics are reflected is extracted, and the area of the extracted area is calculated. The difference in the area between the two frames can be used as data (index) indicating the amount of change in the image. The data showing the amount of change in the image directly represents how the cosmetic is wet and spread. The area may be expressed by, for example, the number of pixels.

Any technique can be adopted as a method for extracting the area where the cosmetics are reflected. For example, when the image of each frame is a color image, the cosmetic on the dropping object may be extracted by utilizing the difference in color between the cosmetic and the dropping object. As an example, a color range of cosmetics can be set, and an area including pixels included in the color range can be extracted as an area in which the cosmetics are reflected.

In addition, when the image of each frame is a grayscale image, the cosmetic on the dropping object may be extracted by utilizing the difference in brightness between the cosmetic and the dropping object. As an example, the lightness range of the cosmetics can be set, and the area including the pixels included in the lightness range can be extracted as the area in which the cosmetics are reflected.

Returning to FIG. 1, in the output step S30, the output unit 13 of the evaluation device 10 shows the transition of the amount of change in the image between two temporally continuous frames based on the analysis / calculation result in the analysis step S20. And / or output data showing the transition of the cumulative value of the amount of change in the image.

FIG. 6 shows an example of the data output by the output unit 13. The data shown in FIG. 6 is a graph obtained by plotting "time-series data of the amount of change (correlation coefficient) of an image between two temporally continuous frames" calculated by the analysis unit 12 on a graph. The transition of the amount of change in the image between two frames of ti _{and ti + 1} that are continuous with each other is shown. _{Of ti i} and ti _{+ 1} that are continuous in time on the horizontal axis, _{the time t 1} corresponding to the first frame in time is taken, and the correlation coefficient of the timings of _{t 1} and t ₂ is taken on the vertical axis. The graph shows the transition of the correlation coefficient of each of sample S1 and sample S2. The correlation coefficient between the timings t ₁ and t ₂ (timing t _1-2 ) is the correlation coefficient between _{the frame at the shooting timing t 1 and} the frame at the shooting timing t ₂ . The correlation coefficient photographed and calculated under the above conditions represents the speed at which the cosmetics get wet and spread. The closer it is to 1, the slower the speed, and the farther it is from 1, the faster the speed.

From the data shown in FIG. 6, it can be seen that there is a difference in how the cosmetics of sample S1 and sample S2 are touched and spread.

In sample S1, the value of the correlation coefficient hardly fluctuates over all time zones and changes around 1. In the case of such sample 1, it can be seen that the dropped cosmetic is hardly wet and spread after being dropped.

On the other hand, in sample S2, _{the value of the correlation coefficient at the beginning of dropping (t 1-2} , t _2-3, etc.) is relatively small, but gradually approaches 1 with the passage of time, and then 1 at a certain timing. It can be seen that it converges in the vicinity. In the case of such sample 2, the dropped cosmetics initially wet and spread at a relatively high speed, but the speed of wet and spread gradually slows down with the passage of time, and the wet spread is converging. I understand.

FIG. 7 shows another example of the data output by the output unit 13. The data shown in FIG. 7 is a graph of time-series data obtained by correcting "time-series data of the amount of change (correlation coefficient) of an image between two temporally continuous frames" calculated by the analysis unit 12. It shows the transition of the amount of change in the image between two frames that are continuous in time. The correction changes the value of each timing to a value obtained by subtracting the correlation coefficient of each timing from 1. As a result, when the amount of change in the image is small, the value is close to 0, and as the amount of change in the image is large, the value is large.

The data shown in FIG. 7 is a graph in which time is taken on the horizontal axis and the correction value (change amount) is taken on the vertical axis, and the transition of the change amount of each of the sample S1 and the sample S2 is shown. The amount of change on the vertical axis is the value obtained by subtracting the correlation coefficient from 1. The amount of change represents the speed at which wetting and spreading. The closer it is to 0, the slower the speed, and the farther it is from 0, the faster the speed.

From the data shown in FIG. 7, it can be seen that there is a difference in how the cosmetics of sample S1 and sample S2 are touched and spread. From the data shown in FIG. 7, a tendency similar to that of the data shown in FIG. 6 can be read.

FIG. 8 shows another example of the data output by the output unit 13. The data shown in FIG. 8, (in the case of FIG. 4, the frame F of the imaging timing t ₁₎ analyzer 12 "temporally first frame is calculated by the time-series data of the cumulative value of the amount of change that image relative to the the Is plotted on a graph, and shows the transition of the cumulative value of the amount of change in the image. Specifically, it is a plot of time-series data obtained by integrating the time-series data of the amount of change shown in FIG. 7 in chronological order. A graph in which time is taken on the horizontal axis and the cumulative value of the change amount is taken on the vertical axis shows the transition of the cumulative value of the change amount of each of the sample S1 and the sample S2. The slope of the line in the graph represents the speed at which wetting and spreading.

From the data shown in FIG. 8, it can be seen that there is a difference in how the cosmetics of sample S1 and sample S2 are touched and spread. By reading the transition of the slope of each of the lines of the sample S1 and the sample S2, the same tendency as the data shown in FIGS. 6 and 7 can be read.

Further, from the data shown in FIG. 8, it is possible to easily grasp the transition of the amount (cumulative value) of the cosmetics wet and spread. In addition, at each timing, it is possible to easily grasp the difference in the amount of wet and spread cosmetics of each of sample S1 and sample S2.

FIG. 9 shows another example of the data output by the output unit 13. Data shown in Figure 9, is calculated by the analyzer 12 "temporally first frame (the case of FIG. 4, the frame F of the imaging timing t ₁₎ the variation relative to the image of (the area in which the cosmetic objects appear Time-series data of the cumulative value of the amount of change in the area) ”is plotted on a graph, and the transition of the cumulative value of the amount of change in the image is shown. The horizontal axis is the time, and the vertical axis is the cumulative value of the change in the area where the cosmetics are reflected. The graph shows the transition of the cumulative change in each of the samples S1 and S2. The slope of the line in the graph represents the speed at which wetting and spreading.

From the data shown in FIG. 9, it can be seen that there is a difference in how the cosmetics of sample S1 and sample S2 are touched and spread. By reading the transition of the slope of each of the lines of the sample S1 and the sample S2, the same tendency as the data shown in FIGS. 6 to 8 can be read.

Further, from the data shown in FIG. 9, it is possible to easily grasp the transition of the size of the area where the cosmetics are wet and spread. Further, at each timing, it is possible to easily grasp the difference in the size of the area where the cosmetics of the sample S1 and the sample S2 are wet and spread.

In the present embodiment described above, the image data of a plurality of frames obtained by photographing the cosmetics dropped on the dropping object over a predetermined time is analyzed, and the transition of the amount of change in the image between two frames that are continuous in time is shown. Data and / or data showing the transition of the cumulative value of the amount of change in the image is output. As described with reference to FIGS. 6 to 9, it is possible to analyze how the cosmetics are touched and spread based on the data.

As described above, according to the present embodiment, it is possible to quantify how the cosmetics get wet and spread by a relatively simple method.

<Second embodiment>
First, the outline of the present embodiment will be described. The present inventors have referred to a dripping object having a large number of fine grooves (eg, skin grooves) and a portion surrounded by the grooves, such as human skin (hereinafter, "grooved dripping object"). ), The cosmetic was dropped over a large number of grooves and the portion surrounded by the grooves, and the state of getting wet and spreading was observed. As a result, it was found that in such a case, there is a portion that wets and spreads first through the groove in a part near the outer periphery of the droplet.

This will be described in detail with reference to FIG. FIG. 10 shows the time change when the cosmetic C is dropped on the grooved dropping object E. The description of the groove and the portion surrounded by the groove on the grooved dropping object E is omitted. With reference to the frame F at the shooting timings t ₂ and t _m in FIG. 10, the wet and spread cosmetic C is formed on the main body portion C1 and the preceding portion C2 that wets and spreads first from the vicinity of the outer periphery of the main body portion C1 through the groove. Divide. The main body portion C1 and the preceding portion C2 get wet and spread at different speeds.

In this embodiment, the main body portion C1 and the preceding portion C2 can be separated to evaluate how to spread wet. Hereinafter, a detailed description will be given.

Similar to the first embodiment, the flowchart of FIG. 1 shows the flow of the evaluation method of the present embodiment. As shown in the figure, it has an image data acquisition step S10, an analysis step S20, and an output step S30. At least a part of these steps is performed by the evaluation device 10 shown in FIG. As shown in FIG. 2, the evaluation device 10 includes an image data acquisition unit 11, an analysis unit 12, and an output unit 13. Hereinafter, each step will be described.

The details of the image data acquisition step S10 are the same as those in the first embodiment. In the present embodiment, the lens magnification of the camera, the distance between the camera and the object to be dropped, and the like are adjusted so that the cosmetic that spreads wet through the groove is captured. The object to be dropped may be the skin of a living body such as a human being, or a substrate or the like having a groove or the like imitating the texture (skin groove) of the human skin.

As shown in FIG. 11, the analysis step S20 includes a smoothing step S21 and a first calculation step S22.

In the smoothing step S21, the analysis unit 12 performs a smoothing process on the image data. The analysis unit 12 can adopt any smoothing technique. For example, a smoothing process using a smoothing filter (averaging filter, Gaussian filter, etc.), a smoothing process using a Fourier transform, and the like can be mentioned, but the present invention is not limited thereto.

When 1 to 10 μL or more of the cosmetic is dropped on the skin of a living body such as a human being or on a substrate having a groove that imitates the texture (skin groove) of the human skin, as shown in FIG. The area of the main body portion C1 is sufficiently larger than the area of the preceding portion C2. Further, the main body portion C1 is a cohesive mass, while the leading portion C2 is an aggregate of a plurality of thin linear objects.

Since such a difference exists between the main body portion C1 and the preceding portion C2, when the image data is appropriately smoothed, the difference in pixel values between the preceding portion C2 and the grooved dropping object E becomes large. On the other hand, the difference in pixel value between the main body portion C1 and the grooved dropping object E remains sufficient. That is, only the preceding portion C2 tends to be selectively assimilated with the grooved dropping object E.

Returning to FIG. 11, in the first calculation step S22, the analysis unit 12 calculates data indicating the amount of change in the image based on the image data after the smoothing process. Since the process of calculating the data indicating the amount of change in the image is the same as that described in the first embodiment, the description here will be omitted.

When data indicating the amount of change in the image is calculated based on the image data that has not been smoothed, the calculated amount of change includes "change amount component due to change (wet spread) of main body portion C1" and "change amount component". "Change amount component due to change (wet spread) of the preceding portion C2" is included. On the other hand, when the smoothing process as described above is performed and the data indicating the amount of change in the image is calculated based on the image data in which only the preceding portion C2 is selectively assimilated with the grooved dropping object E, the data indicating the amount of change in the image is calculated. In the calculated change amount, the "change amount component due to the change (wet spread) of the preceding portion C2" is reduced, and the change amount that well represents the "change amount due to the change (wet spread) of the main body portion C1" is calculated. can do.

Returning to FIG. 1, in the output step S30, the output unit 13 shows the transition of the data showing the transition of the change amount of the image and / or the cumulative value of the change amount of the image based on the calculation result in the first calculation step S22. Output data. The details of these data are the same as in the first embodiment.

The output data as described above based on the calculation result in the first calculation step S22 is the transition of the "change (wetting spread) of the main body portion C1" and the cumulative value of the "change (wetting spread) of the main body portion C1". It is the data that shows the transition.

As described above, according to the present embodiment, the same effects as those of the first embodiment can be realized. Further, when the cosmetic is dropped on the grooved drip object and a state in which the wet spread is photographed, the main body portion C1 and the preceding portion C2 can be separated to evaluate how the wet spread spreads.

Specifically, according to the present embodiment, it is possible to evaluate how the main body portion C1 gets wet and spreads. By adopting the same treatment as in the first embodiment, it is possible to evaluate how the cosmetics are wet and spread by grouping the main body portion C1 and the preceding portion C2. As described above, according to the present embodiment, it is possible to evaluate how the cosmetics get wet and spread from various viewpoints.

<Third embodiment>
Similar to the second embodiment, the present embodiment relates to a technique of separating the main body portion C1 and the preceding portion C2 and evaluating how to spread wet. Hereinafter, a detailed description will be given.

Similar to the first and second embodiments, the flowchart of FIG. 1 shows the flow of the evaluation method of the present embodiment. As shown in the figure, it has an image data acquisition step S10, an analysis step S20, and an output step S30. At least a part of these steps is performed by the evaluation device 10 shown in FIG. As shown in FIG. 2, the evaluation device 10 includes an image data acquisition unit 11, an analysis unit 12, and an output unit 13. Hereinafter, each step will be described.

The image data acquisition step S10 is the same as that of the first and second embodiments. In the present embodiment, the lens magnification of the camera, the distance between the camera and the object to be dropped, and the like are adjusted so that the cosmetic that wets and spreads through the groove is captured. The object to be dropped may be the skin of a living body such as a human being, or a substrate or the like having a groove or the like imitating the texture (skin groove) of the human skin.

As shown in FIG. 12, the analysis step S20 includes a smoothing step S21, a first calculation step S22, a second calculation step S23, and a difference calculation step S24.

The smoothing step S21 and the first calculation step S22 are the same as those in the second embodiment.

In the second calculation step S23, the analysis unit 12 calculates data indicating the amount of change in the image based on the image data that has not been smoothed. Since the process of calculating the data indicating the amount of change in the image is the same as that described in the first embodiment, the description here will be omitted.

The second calculation step S23 may be performed after the smoothing step S21 and the first calculation step S22, may be performed before these, or may be performed in parallel with these. ..

As described in the second embodiment, when data indicating the amount of change in the image is calculated based on the image data that has not been smoothed, the calculated amount of change includes "change in the main body portion C1 (wet spread). ) And "change amount component due to change (wet spread) of the preceding portion C2" are included. That is, it is possible to calculate the amount of change by adding the "amount of change caused by the change (wetting spread) of the main body portion C1" and the "amount of change caused by the change (wetting spread) of the preceding portion C2".

In the difference calculation step S24, the data indicating the amount of change in the image calculated by the analysis unit 12 in the first calculation step S22 from the data (time series data) indicating the amount of change in the image calculated in the second calculation step S23. Calculate the difference by subtracting (time series data). The analysis unit 12 performs the difference processing by matching the measurement timings of the time-series data obtained in the second calculation step S23 and the time-series data obtained in the first calculation step S22.

As described above, the data indicating the amount of change in the image calculated in the second calculation step S23 is "the amount of change due to the change in the main body portion C1 (wetting spread)" and "the change in the preceding portion C2 (wetting spread)". It represents the amount of change obtained by adding up the amount of change caused by.

On the other hand, as described in the second embodiment, data indicating the amount of change in the image calculated in the first calculation step S22 (data indicating the amount of change in the image calculated based on the image data after the smoothing process). Well represents "the amount of change due to the change (wet spread) of the main body portion C1".

Therefore, the difference data obtained by subtracting the data indicating the amount of change in the image calculated in the first calculation step S22 from the data indicating the amount of change in the image calculated in the second calculation step S23 is "preceding". The amount of change due to the change (wet spread) of the partial C2 is well represented.

Returning to FIG. 1, in the output step S30, the output unit 13 is calculated in the difference calculation step S24 instead of the data showing the transition of the change amount of the image and / or the data showing the transition of the cumulative value of the change amount of the image. The data showing the transition of the difference and / or the data showing the transition of the cumulative value of the difference are output. The output unit 13 outputs the difference data by the same display method (see FIGS. 6 to 9) as the data showing the transition of the change amount of the image and / or the data showing the transition of the cumulative value of the change amount of the image. can do.

The output unit 13 may further output data indicating a transition of the amount of change in the image and / or data indicating a transition of the cumulative value of the amount of change in the image. For example, the output unit 13 may output predetermined data according to the user's selection.

As described above, according to the present embodiment, the same effects as those of the first and second embodiments can be realized. Further, when the cosmetic is dropped on the grooved drip object and a state in which the wet spread is photographed, the main body portion C1 and the preceding portion C2 can be separated to evaluate how the wet spread spreads.

Specifically, in the present embodiment, it is possible to evaluate how the preceding portion C2 gets wet and spreads. By adopting the same treatment as in the first embodiment, it is possible to evaluate how the cosmetics are wet and spread by grouping the main body portion C1 and the preceding portion C2. Further, by adopting the same treatment as in the second embodiment, it is possible to evaluate how the main body portion C1 gets wet and spreads. As described above, according to the present embodiment, it is possible to evaluate how the cosmetics get wet and spread from various viewpoints.

<< Example >>
As cosmetics, cosmetics having the ingredients shown in Table 1 below were prepared. 2.0 μL of a solution prepared by adding 0.10% by mass of a colorant (Blue No. 1) to the cosmetic was added dropwise onto human skin.

Then, under the shooting conditions of a frame rate of 30 fps, a distance between the human skin and the camera: 10 cm, an image size of 1280 × 960 pxl, and a camera lens magnification of 40 times, the appearance of the cosmetics getting wet and spreading was photographed. Only cosmetics and human skin were shown in the frame.

Then, the analysis step S20 was performed on the obtained image data. Specifically, the analysis unit 12 obtained a one-dimensional vector by arranging the pixel values of all the pixels in a predetermined order for each frame. Thereafter, analyzer 12 includes a frame F of the imaging timing _{t a,} create multiple pairs between frame F of the imaging timing _{t a + 1 (1 ≦ a} ≦ m-1), for each pair, between two frames F By calculating the correlation coefficient of, time-series data of the correlation coefficient was obtained.

In addition, the analysis unit 12 performed a smoothing process using a smoothing filter on each of the plurality of frames. After that, the analysis unit 12 obtained a one-dimensional vector by arranging the pixel values of all the pixels in a predetermined order for each frame. Then, the analysis unit 12 includes a frame F of the imaging timing _{t a,} create multiple pairs between frame F of the imaging timing _{t a + 1 (1 ≦ a} ≦ m-1), for each pair, between two frames F By calculating the correlation coefficient of, time-series data of the correlation coefficient was obtained.

FIG. 13 shows the data output by the output unit 13 based on the above calculation result. FIG. 13 shows the same information in the same graph as in FIG.

“Original” is time series data of the correlation coefficient calculated without performing the smoothing process. “Blurred” is time series data of the correlation coefficient calculated after the smoothing process.

From FIG. 13, it can be seen that the wet spreading method of the cosmetic can be evaluated as described in the first embodiment.

Further, from FIG. 13, it can be seen that the transition of the correlation coefficient changes depending on the presence or absence of the smoothing process. “Original” represents the transition of the change obtained by adding the “change due to the change (wetting spread) of the main body portion C1” and the “change (wetting spread) of the preceding portion C2”. “Blurred” represents the transition of “change (wetting spread) of main body portion C1”.

Next, FIG. 14 shows the difference data between “original” and “blurred” in FIG. The difference data represents the transition of "change (wet spread) of preceding portion C2".

As described above, it has been shown that the present embodiment can evaluate how the cosmetics get wet and spread as described in the first to third embodiments.

1A processor 2A memory 3A I / O I / F
4A Peripheral circuit 5A Bus 10 Evaluation device 11 Image data acquisition unit 12 Analysis unit 13 Output unit C Cosmetics C1 Main body part C2 Preceding part D Dropping object E Grooved dropping object F frame

Claims (6)

An image data acquisition step of acquiring image data of a plurality of frames obtained by photographing a cosmetic material dropped over a groove and other portions on a dropping object having a groove over a predetermined time.
Based on the image data after the smoothing process, there are two analysis steps, one is a first analysis step of calculating data indicating the amount of change in the image between the two frames, and the other is based on the image data not subjected to the smoothing process. The data showing the amount of change in the image between the frames is calculated, and the data showing the amount of change in the image calculated based on the image data not subjected to the smoothing process is used to obtain the image data after the smoothing process. An analysis step of executing a second analysis step of calculating a difference obtained by subtracting data indicating the amount of change in the image calculated based on
Data showing at least one of the transition of the change amount of the image and the transition of the cumulative value of the change amount calculated based on the image data after the smoothing process, the transition of the difference, and the transition of the cumulative value of the difference. An output process that outputs data indicating at least one of
How to evaluate how to spread the wetness of cosmetics with. In the evaluation method according to claim 1,
In the analysis step, an evaluation method for calculating a correlation coefficient between two frames as data indicating the amount of change in the image. In the evaluation method according to claim 1,
In the analysis step, an evaluation method for calculating the amount of change in the area of the area in which the cosmetic is reflected in each of the two frames as data indicating the amount of change in the image. In the evaluation method according to any one of claims 1 to 3,
In the output step, an evaluation method for further outputting data indicating at least one of a transition of a change amount of the image and a transition of a cumulative value of the change amount calculated based on the image data that has not been smoothed. An image data acquisition unit that acquires image data of a plurality of frames obtained by photographing a cosmetic material dropped over a groove and other portions on a dropping object having a groove over a predetermined time.
Based on the image data after the smoothing process, there are two, a first analysis process for calculating data indicating the amount of change in the image between the two frames, and two based on the image data not subjected to the smoothing process. The data showing the amount of change in the image between the frames is calculated, and the data showing the amount of change in the image calculated based on the image data not subjected to the smoothing process is used to obtain the image data after the smoothing process. An analysis unit that executes a second analysis process that calculates a difference obtained by subtracting data indicating the amount of change in the image calculated based on
Data showing at least one of the transition of the change amount of the image and the transition of the cumulative value of the change amount calculated based on the image data after the smoothing process, the transition of the difference, and the transition of the cumulative value of the difference. An output unit that outputs data indicating at least one of
An evaluation device for evaluating how a cosmetic having a wet spread spreads. Computer,
An image data acquisition means for acquiring image data of a plurality of frames obtained by photographing a cosmetic material dropped over a groove and other portions on a dropping object having a groove for a predetermined time.
Based on the image data after the smoothing process, there are two, a first analysis process for calculating data indicating the amount of change in the image between the two frames, and two based on the image data not subjected to the smoothing process. The data showing the amount of change in the image between the frames is calculated, and the data showing the amount of change in the image calculated based on the image data not subjected to the smoothing process is used to obtain the image data after the smoothing process. An analysis means for executing a second analysis process for calculating a difference obtained by subtracting data indicating the amount of change in the image calculated based on the above.
Data showing at least one of the transition of the change amount of the image and the transition of the cumulative value of the change amount calculated based on the image data after the smoothing process, the transition of the difference, and the transition of the cumulative value of the difference. An output means that outputs data indicating at least one of
A program to evaluate how the cosmetics that function as wet and spread.

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