System and method for applying a reflectance modifying agent to change a persons appearance based on a digital image

Abstract

A computer-controlled system determines attributes of a frexel, which is an area of human skin, and applies a reflectance modifying agent (RMA) at the pixel level to automatically change the appearance of human features based on one or more digital images. The change may be based on a digital image of the same frexel, for as seen in a prior digital photograph captured previously by the computer-controlled system. The system scans the frexel and uses feature recognition software to compare the person's current features in the frexel with that person's features in the digital image. It then calculates enhancements to the make the current features appear more like the features in the digital image, and it applies the RMA to the frexel to accomplish the enhancements. Or the change may be based on a digital image of another person, through the application of RMAs.

Description

FIELD OF THE INVENTION

The current invention relates to automated computer-controlled methods to selectively and precisely apply one or more reflectance modifying agent, such as a dye or pigment, to human skin as cosmetics to change the appearance of human features based on a model comprising at least one digital image.

BACKGROUND OF THE INVENTION

Prior Cosmetic Techniques and Their Disadvantages

Prior art techniques for modifying the appearance of skin include natural tanning, artificial tanning, and the deliberate application of cosmetics. Each of these prior art techniques has limitations.

Typically, the applications of cosmetic substances to skin are largely manual, for example through the used of brushes, application tubes, pencils, pads, and fingers. These application methods make prior art cosmetics imprecise, labor intensive, expensive, and sometimes harmful, when compared to the computerized techniques of the present invention.

Most prior art cosmetic approaches are based on the application of opaque substances. As explained in the cross-referenced application U.S. Ser. No. 11/503,806, there is a need for the precise computer-controlled application of reflectance modifying agents (RMAs), such as transparent dyes, to provide a more effective modification of appearance. In this specification, the terms “reflectance modifying agent” or “RMA” refer to any compound useful for altering the reflectance of another material, and are explained in further detail below. Some examples of RMA are inks, dyes, pigments, bleaching agents, chemically altering agents, and other substances that can alter the reflectance of human skin and other features. The terms “dye” and “transparent dyes” are used for brevity in this specification to represent any RMA.

Moreover, cosmetics are typically applied manually to make people look more like certain images. For example, cosmetics may be applied to reconstruct the former appearance of people whose features have been altered or damaged. For example, cosmetics may be applied to the skin of patients who have been burned, to make the burned skin appear to have the color and texture it had before the burns. Cosmetics may be used to create the appearance of eyebrows on cancer patients who have lost their hair as a result of chemotherapy or radiation treatment. And cosmetics are used generally to make older people look more like they were when young. In addition, cosmetics may be used to make people look more like any desired model of themselves that they might have.

Typically the models used as the basis for these cosmetic applications are

• • People's memories of the way they looked previously.
  • Prior images of people, such as photographs, videos, paintings, drawings, and digital images such as those stored on computers, cell phones, and digital cameras.
  • Images of people as they would like to be seen, for example in drawings, enhanced photographs, or computer-generated images.

Ideal models derived from certain people are also used as the basis for cosmetic applications on other people. For example, a makeup artist may create a “look,” consisting of a certain combination of colors, shading contrasts, and even feature shapes, such as eyebrow shapes, that is used as model for cosmetics applied to many different people. Such a look may be based on the appearance of a popular actress, for example a Nicole Kidman look or a Catherine Zeta-Jones look, because many women would like to look like those actresses. Makeup artists can apply cosmetics to make different people all have a similar look, or individuals may apply their own cosmetics to create such effects, for example based on magazine pictures or digital images of actresses.

However, manual techniques of applying cosmetics for such changes based on images, such as digital images, can be time consuming and require considerable skill to be done well, as anyone can attest who has tried to draw on eyebrows for a distressed cancer patient to match a digital image of her.

Therefore, there is a need for the precise application of reflectance modifying agents (RMAs) to provide a more effective, more automated, faster, less expensive, and less dangerous modification of the appearance of skin to cosmetically change people's features based on digital images.

BRIEF SUMMARY OF THE INVENTION

These and other needs are addressed by the present invention. The following explanation describes the present invention by way of example and not by way of limitation.

It is an aspect of the present invention to automatically change the appearance of human features based on a model digital image.

It is another aspect of the present invention to automatically reconstruct the appearance of human features based on digital images, through the application of RMAs. A useful technique is to employ feature recognition software to compare a person's current features with that person's features in one or more digital images. These images may be previously provided by the present invention's system and method. Or they may be provided by other compatible means. The present invention's enhancement software can then determine reconstructive enhancements based on those digital images and can apply those enhancements to the person precisely and automatically.

It is still another aspect of the present invention to automatically enhance the appearance of a person's features based on a digital image of another person, through the application of RMAs. A useful technique is to employ feature recognition software to compare the person's features with a model person's features in one or more digital images. These images may be previously provided by the present invention's system and method. Or they may be provided by other compatible means. The present invention's software can then determine enhancements based on those digital images and can apply those enhancements to the person precisely and automatically.

These and other aspects, features, and advantages are achieved according to the system and method of the present invention. In accordance with the present invention, a computer-controlled system determines attributes of a frexel, which is an area of human skin, and applies a reflectance modifying agent (RMA) at the pixel level to automatically change the appearance of human features based on one or more digital images.

One embodiment may change the appearance of human features based on one or more digital images of the same frexel, as seen in a prior digital photograph. In an embodiment, the digital images are captured previously by the computer-controlled system. The system scans the frexel and uses feature recognition software to compare the person's current features in the frexel with that person's features in the digital images. It then calculates enhancements to the make the current features appear more like the features in the digital images, and it applies the RMA to the frexel, typically with an inkjet printer, to accomplish the enhancements. The identified attributes in the frexel may relate to reflectance characteristics and to the surface topology of the skin.

Another embodiment may enhance the appearance of a person's features based on a digital image of another person, through the application of RMAs. A useful technique is to employ feature recognition software to compare the person's features with a model person's features in one or more digital images. These images may be previously provided by the present invention's system and method. Or they may be provided by other compatible means. The present invention's software can then determine enhancements based on those digital images and can apply those enhancements to the person precisely and automatically.

BRIEF DESCRIPTION OF THE DRAWINGS

The following embodiment of the present invention is described by way of example only, with reference to the accompanying drawings, in which:

FIG. 1 is a block diagram that illustrates an enhancement system for using a model digital image to change a person's appearance;

FIG. 2 is a block diagram that illustrates a reconstruction system comprising additional means of obtaining prior digital image;

FIG. 3 is a block diagram that illustrates a reconstruction system comprising additional means of obtaining prior digital images;

FIG. 4 is a block diagram that illustrates an enhancement system comprising additional means of obtaining a digital image of a second person;

FIG. 5 is a flow chart that illustrates a process for reconstructing the appearance of human features based on a digital image obtained through the present invention;

FIG. 6 is a flow chart that illustrates a process for reconstructing the appearance of human features based on a digital image obtained through another source than the present invention;

FIG. 7 is a flow chart that illustrates a process for automatically enhancing a person's appearance based on the appearance of a second person based on a digital image obtained through the present invention; and

FIG. 8 is a flow chart that illustrates a process for automatically enhancing a person's appearance based on the appearance of a second person based on a digital image obtained through another source than the present invention.

DETAILED DESCRIPTION OF EMBODIMENT

Reconstruction Process

The present invention comprises the application or one or more reflectance modifying agents (RMAs) through a computer-controlled system and method to change a person's appearance. For example, the invention may be used to automatically reconstruct the appearance of a person's damaged or altered features, based on the appearance of that person in one or more digital images. To cite another example, the invention may be used to automatically enhance a first person's appearance based on the appearance of second person in a digital image.

U.S. application Ser. No. 11/503,806 filed Aug. 14, 2006 by the present applicants claims the computer-controlled system and method that scans an area of human skin, identifies unattractive attributes, and applies the RMA, typically with an inkjet printer, to improve the appearance of that area of skin. The present invention comprises new innovations to that system and method to accomplish the changes mentioned above.

Enhancement System

FIG. 1 illustrates an embodiment of a system for changing the appearance of features using the cosmetic system explained with reference to FIG. 1 in the cross-referenced application U.S. Ser. No. 11/503,806. FIG. 1 in the present application shows the incorporation of the new element of at least one previously stored digital image 702 that is used as a model for changing a person's appearance.

Frexels

In this patent specification, the term “frexel” is defined as a small pixel-like region of the skin. A frexel might correspond to a small portion of a freckle or other skin feature, or it may correspond to an area of the skin that does not have special features. A frexel thus refers to skin rather than to an independent coordinate system. The term frexel is used to suggest that what is being measured is on a 3-D surface rather than a flat surface.

Reconstruction System

FIG. 2 illustrates an embodiment of a system for changing the appearance of features using the cosmetic system explained with reference to FIG. 48 in the cross-referenced application U.S. 60/889,297. In FIG. 2, the stored digital image 702 may be a previous digital image of a person whose feature or features are to be reconstructed. In an embodiment, this digital image 702 may be one obtained through the system and method of the present invention, so that it provides the appropriate data needed for reconstruction. As a result, compatible data may be obtained for the same frexel or frexels on a person at a current time and at a previous time and may be compared efficiently for reconstruction. This data may comprise reflectance and topographical data mapped for the same frexel and the same set of features contained in the frexel. Moreover it may be represented in the same data format, so that it may be easily used for reconstruction. This digital image 702 may represent a prior appearance of the person, for example from when the person was younger, healthier or otherwise more attractive.

If a patient's left eyebrow needs to be reconstructed, for example, a digital image 702 may be used that has been previously captured about that patient and stored in storage 250, and that shows the patient's left eyebrow. A woman who has stored a model digital image 702 of her face at age 20 may use that digital image 702 years later, for example when she is 50, as the basis for enhancements with RMAs throughout her face. The same woman could also choose to use as a basis for reconstruction a previous image of herself when she received a special makeup look from a professional makeup artist.

Topographic aspects of features can also be reconstructed to degrees. For example, dark hollows under eyes and below cheekbones can be lightened to make a face appear younger and healthier.

In another embodiment, multiple previous digital images of the person may be used to derive a digital image 702, useful for reconstruction, for example by averaging the relevant values of the multiple digital images. In addition, a current frexel may be reconstructed by using data from different but relevant frexels. For example, a frexel representing a point on a cheek may be reconstructed on the basis of previous images 702 showing adjacent frexels or frexels on different points of the body.

In still another embodiment, a computer display 102 (not shown) and interface 104 (not shown), for example a keyboard, may be used to allow a consumer to select a stored digital image 702, or elements from that image 702 or from multiple stored images, to derive a basis for one or more reconstructions, as will be evident to those skilled in the art.

In other embodiments, the digital image 702 may be created remotely and transferred to computing environment 100 by any method known to those skilled in the art or not yet known. For example, it may be sent over the Internet from a remote computer to computing environment 100. It may be loaded onto computing environment 100 by means of a diskette. It may also be transferred through wireless technology, as well as by many other means.

Alternate Embodiments of Reconstruction System

FIG. 3 illustrates other embodiments in which the system comprises means for incorporating images not created by the system and method of the present invention and not previously explained above, which can be used as bases for reconstruction.

In one embodiment, image receiving means 712 enable the application system 200, shown in FIG. 2, to receive at least one digital image 702 of the person whose appearance is to be reconstructed so that digital image 702 can be stored in storage 250. For example, the digital image 702 may be a scanned image made from a photograph, painting, drawing, or other form of image. Or it may a digitally created image, such as an image captured by a digital camera, cell phone, or video camera, or an image generated on a computer.

This digital image 702 may represent not only a prior appearance of the person but the way the person would like to be seen. For example, the person might want to look like his or her appearance in an idealized drawing, an enhanced photograph, or a computer-generated image. These idealized images may be created by the person or someone working on the person's behalf, such as an artist or a makeup designer.

The digital image 702 may be received by the application system 200 by any of multiple image receiving means 712, shown in FIG. 3, known and not yet known. For example, it may be sent to the application system 200, shown in FIG. 2, by e-mail and read automatically by an application program. It may be loaded from a diskette or other storage device and read by an appropriate storage device reader. Moreover, it may be created by a device or software application attached to the application system 200, such as a digital camera or computer graphics program, and automatically stored by software in storage 250.

Moreover, multiple digital images 702 may be received by the application system 200 to derive a single model for reconstruction. For example, the application algorithm 230 can average multiple digital images 702 to derive more representative values for features in the captured digital data, their locations, and their reflectance patterns, to improve the quality of the printable reconstruction image 708.

Another embodiment comprises scanner 2222, shown in FIG. 3, so that a non-digital image 714 may be scanned and digitized to create a digital image 702 that can be stored in storage 250, for use as a model for reconstruction.

To use images created through other methods, the present invention employs digital image feature recognition software 710 that identifies features in one or more received digital images 702. In an embodiment, this digital image feature recognition software 710 employs the techniques for the analysis of reflectance patterns explained in detail above, but applied to digital images. In other embodiments, it may use other techniques for feature recognition, for example Optasia™, the model-based feature-recognition platform developed by Image Metrics, Plc. The “Technical White Paper” on the Image Metrics website states that, “The Optasia engine can perform rapid model-to-image matching regardless of the model type, including those with high-frequency elements such as texture.” These other techniques may be used in combination with the techniques for the analysis of reflectance patterns explained above or independently of them.

The digital image feature recognition software 710 is used to create a digital image feature map 704 that identifies features in the digital image 702, their locations, and their reflectance patterns.

The application algorithm 230 in turn creates a frexel feature map 706 from data captured for the person scanned, as explained above. The frexel feature map 706 identifies features in that captured data, their locations, and their reflectance patterns.

The application algorithm 230 then compares the analogous information in the digital image feature map 704 and the frexel feature map 706 and uses the data in the digital image feature map 704 as a model to reconstruct the data in the frexel feature map 706. In an embodiment, this reconstruction can be accomplished by subtracting the frexel values from the analogous digital image values to derive the values of a reconstruction image.

For example, an eyebrow that has become fainter in the frexel feature map 706 may be reconstructed, with pixel-level precision, from a darker eyebrow present in the digital image feature map 704. Skin discolored from burns can be altered to more of its previous color.

The application algorithm 230 uses this reconstruction to define a printable reconstruction image 708 that is used as a basis to apply an RMA to an area of skin 302, typically by inkjet printing, as explained above.

Enhancement System for Changing a First Person's Appearance Based on a Digital Image of a Second Person

In an embodiment, the digital image 702 shown in FIG. 1 may be that of another person obtained through the system and method of the present invention, so that it provides the appropriate data needed for the enhancements to be made to the first person.

FIG. 1 also illustrates an embodiment of a system for changing the appearance of features using the cosmetic system explained with reference to FIG. 48 in the cross-referenced application U.S. 60/889,298. In this embodiment, the digital image 702 generally represents a second person whose appearance is more desirable for some purpose than the appearance of the first person. It may, for example, represent a second person who is younger, healthier or otherwise more attractive than the first person. If a first person's eyebrows are too light and lack an attractive shape, for example, a model digital image 702 of an actress with dark and well arched eyebrows may be used, when that model digital image 702 has been previously captured and stored in storage 250. Thus, a printable enhancement image 234 may be calculated and applied to the first person to morph the first person's eyebrows so that they look more like the second person's eyebrows.

For example, the distinctive arch of Nicole Kidman's eyebrow can be used as a model to enhance millions of girls next door by making their eyebrows of more arched. Or Catherine Zeta Jones's olive complexion, individual beauty marks, and full crimson lips can lend those girls a degree of her special charm.

On the other hand, model digital image 702 may represent a second person whose appearance is older and more responsible looking that the first person's, for example for the purpose of a job interview when the first person is very young and wants to look more mature.

The model digital image 702 may further represent a particular kind of appearance of any second person desired to serve as a model for the enhancements to the first person. For example, the model digital image 702 may be one of Nicole Kidman made up to have a special look for a formal event.

Filtering techniques may be used to determine the degree of similarity to be achieved. With no filtering, a very close resemblance between the second and first person may be achieved, depending on the original similarity between the two people. A higher degree of filtering may achieve a softer suggestion of similarity.

Topographic aspects of features can also be enhanced to degrees. On the first person's face, for example, cheekbones can be darkened to make them appear more like those of a second person with prominent, attractive cheekbones.

In another embodiment, multiple digital images of the second person may be used to derive a model digital image 702, useful for enhancements, for example by averaging the relevant values of those images. In addition, a frexel on the first person may be enhanced by using data from different but relevant frexels on the second person. For example, a frexel representing a point on a cheek on a first person may be enhanced on the basis of one or more model digital images 702 showing frexels or frexels on different points of the body of the second person.

In still another embodiment, a computer display 102 (not shown) and an interface 104 (not shown), for example a keyboard, may be used to allow a first person to select a stored model digital image 702 of a second person, or elements from that model digital image 702 or from multiple stored images, to derive a basis for one or more enhancements, as will be evident to those skilled in the art.

In other embodiments, the digital image 702 may be created remotely on a first instance of the present invention and transferred by any method, known to those skilled in the art or not yet known, to computing environment 100, which represents a second instance of the present invention. For example, it may be sent over the Internet from a remote computer to computing environment 100. It may be loaded onto computing environment 100 by means of a diskette. It may also be transferred through wireless technology, as well as by many other means.

FIG. 4 illustrates other embodiments in which the system comprises means for incorporating images not created by the system and method of the present invention to create a printable enhancement image 234. The elements shown in FIG. 4 are explained above in connection with FIG. 3.

DESCRIPTION OF EMBODIMENT

Reconstruction Example

FIG. 5 illustrates an embodiment of a process for reconstruction using the system shown in FIG. 2.

Step 730 in FIG. 5—Derive a digital image 702 showing a person's desired appearance. As explained above, the digital image 702 may have been stored previously by application system 200, shown in FIG. 2. In addition, it can be derived from elements of one or multiple digital images stored previously, for example through averaging them.

Step 732 in FIG. 5—Scan a frexel of the person.

The application system 200, shown in FIG. 2 and explained in detail above, scans a frexel of the person.

Step 734 in FIG. 5—Use the data in the digital image 702 as a model to reconstruct the data in the frexel.

The application algorithm 230, shown in FIG. 2, compares the analogous information in the digital image 702 and in the frexel and uses the data in the digital image 702 as a model to reconstruct the data in the frexel. For example, this can be done by subtracting the frexel values from the analogous digital image values.

Step 736 in FIG. 5—Define a printable reconstruction image 708 from the reconstructed data.

The reconstructed values derived in Step 734 are treated as a printable reconstruction image 708.

Step 738 in FIG. 5—Apply the RMA to the frexel to create the reconstruction.

The application system 200, shown in FIG. 2, applies the RMA to the frexel, typically by inkjet printing, to accomplish the desired reconstruction.

DESCRIPTION OF EMBODIMENT

Using Images Created by Other Methods

FIG. 6 illustrates an embodiment of a process for reconstruction using images not obtained by the general system and method of the present invention described above.

Step 740 in FIG. 6—Derive a digital image 702 showing a person's desired appearance.

As explained above, the digital image 702 can be received by the application system 200 shown in FIG. 2, or created by scanning a non-digital image 714, shown in FIG. 3. It can also be derived from multiple digital images, for example through averaging them. It may represent a prior image of the person or an image of how the person would like to be seen, for example one designed by a makeup artist.

Step 742 in FIG. 6—Create a digital image feature map 704.

The digital image feature recognition software 710, shown in FIG. 3, creates a digital image feature map 704 that identifies features in the digital image 702, their locations, and their reflectance patterns.

Step 744 in FIG. 6—Scan a frexel of the person.

The application system 200, shown in FIG. 2 and explained above, scans a frexel of the person.

Step 746 in FIG. 6—Create a frexel feature map 706.

The application algorithm 230, shown in FIG. 3, creates a frexel feature map 706 from data captured for the person scanned. The frexel feature map 706 identifies features in that captured data, their locations, and their reflectance patterns.

Step 748 in FIG. 6—Use the data in the digital image feature map 704 as a model to reconstruct the data in the frexel feature map 706.

The application algorithm 230, shown in FIG. 3, compares the analogous information in the digital image feature map 704 and in the frexel feature map 706 and uses the data in the digital image feature map 704 as a model to reconstruct the data in the frexel feature map 706. For example, this can be done by subtracting the frexel values from the analogous digital image values.

Step 750 in FIG. 6—Define a printable reconstruction image 708 from the reconstructed data.

The reconstructed values derived in Step 748 are treated as a printable reconstruction image 708.

Step 752 in FIG. 6—Apply the RMA to the frexel to create the reconstruction.

The application system 200, shown in FIG. 2, applies the RMA to the frexel, typically by inkjet printing, to accomplish the desired reconstruction.

Advantages of Reconstruction

The advantages of the reconstruction system and method described above are that it enables RMAs to be applied more automatically and more precisely, at the pixel level, to reconstruct the appearance of people's features, based on the appearance of those features in digital images.

Alternate Reconstruction Embodiments

In addition, this process may be usefully applied to other substances besides RMAs. For example human skin and artificial reconstruction materials may be applied.

DESCRIPTION OF EMBODIMENT

Process for Enhancing a First Person's Feature Based on a Digital Image of a Second Person

FIG. 7 illustrates an embodiment of a process for enhancement of a first person's features based on a digital image of a second person.

Step 830 in FIG. 7—Derive a model digital image 702.

As explained above, the model digital image 702 may be created by the application system 200 shown in FIG. 1. For example, it may represent a digital image of an actress with a special look designed by a makeup artist, captured by the system and method of the present invention. It may also received by the application system 200 from any of multiple sources, and it may be derived from multiple images, for example through averaging them.

Step 832 in FIG. 7—Scan a frexel of the first person.

The application system 200, shown in FIG. 1 and explained in detail above, scans a frexel of the first person.

Step 834 in FIG. 7—Use the data in the model digital image 702 as a model to calculate an enhancement in the frexel of the first person.

The application algorithm 230, shown in FIG. 1, compares the analogous information in the model digital image 702 and in the frexel of the first person and uses the data in the model digital image 702 as a model to enhance the data in the frexel of the first person. For example, this can be done by subtracting the frexel values from the analogous model digital image values. As explained above, the values of the enhancement image may be filtered by a percentage to prevent exact copying of the model digital image 702.

Step 836 in FIG. 7—Define a printable enhancement image 234 from the enhancement data.

The enhancement values derived in Step 734 are treated as a printable enhancement image 234.

Step 838 in FIG. 7—Apply the RMA to the frexel to make the enhancement.

The application system 200, shown in FIG. 1, applies the RMA to the frexel on the first person, typically by inkjet printing, to accomplish the desired enhancement.

DESCRIPTION OF EMBODIMENT

Enhancement Process with Images Created by Other Methods

FIG. 8 illustrates an embodiment of a process for enhancement of a first person using images of a second person that are not created by the general system and method of the present invention described above.

Step 840 in FIG. 8—Derive a model digital image 702 of a second person.

As explained above, the model digital image 702 can be received by the application system 200 shown in FIG. 1 or created by scanning a non-digital image 714, shown in FIG. 4. It can also be derived from multiple digital images, for example through averaging them.

Step 842 in FIG. 8—Create a digital image feature map 704.

The digital image feature recognition software 710, shown in FIG. 4, creates a digital image feature map 704 that identifies features in the model digital image 702, their locations, and their reflectance patterns.

Step 844 in FIG. 8—Scan a frexel of the first person.

The application system 200, shown in FIG. 1 and explained in detail above, scans a frexel of the first person.

Step 846 in FIG. 8—Create a frexel feature map 706.

The application algorithm 230, shown in FIG. 4, creates a frexel feature map 706 from data captured for the first person. The frexel feature map 706 identifies features in that captured data, their locations, and their reflectance patterns.

Step 848 in FIG. 8—Use the data in the digital image feature map 704 as a model to enhance the data in the frexel feature map 706.

The application algorithm 230, shown in FIG. 4, compares the analogous information in the digital image feature map 704 and in the frexel feature map 706 and uses the data in the digital image feature map 704 as a model to make an enhancement in the frexel feature map 706. For example, this can be done by subtracting the frexel values from the analogous digital image values. As explained above, the values of the enhancement image may be filtered by a percentage to prevent exact copying of the model digital image 702.

Step 850 in FIG. 8—Define a printable enhancement image 234 from the enhancement data.

The enhancement values derived in Step 848 are treated as a printable enhancement image 234.

Step 852 in FIG. 8—Apply the RMA to the frexel to make the enhancement.

The application system 200, shown in FIG. 1, applies the RMA to the frexel, typically by inkjet printing, to accomplish the desired enhancement.

It will be apparent to those skilled in the art that different embodiments of the present invention may employ a wide range of possible hardware and of software techniques. The scope of the current invention is not limited by the specific examples described above.

Claims

1. A system to change an appearance of a region of skin of a first person, the system comprising: a camera configured to generate one or more images of the region of human skin, the region of human skin being allocated into a plurality of frexels;a computing device executing enhancement software to determine a difference between the plurality of frexels within the region of skin of the first person and a desired image based on a first image of skin, the first image of skin depicting one or more features to be cosmetically enhanced in the region of skin and the desired image comprising a model for visual enhancements of the first image of skin; andan apparatus comprising at least one reflectance modifying agent application element, the reflectance modifying agent application element selectively applying a reflectance modifying agent to one or more of the plurality of frexels in accordance with the difference between the plurality of frexels within the region of skin and the first image of skin to emulate the one or more features of the desired image within the region of skin of the first person.

2. The system of claim 1, further comprising providing a digital image feature map based on the first image.

3. The system of claim 1, wherein the first image comprises a digital image of the first person.

4. The system of claim 1, wherein the first image comprises a digital image of a region of human skin of a second person.

5. The system of claim 1, wherein the first image comprises reflectance and topographical data.

6. The system of claim 1, further comprising comparing a digital feature map, which is provided based on the first image of skin, and a frexel feature map to generate a reconstruction image by: using the digital feature map as a model to derive enhancement values; andgenerating the reconstruction image as an enhancement image based on the derived enhancement values.

7. The system of claim 1, wherein the computing device is further operable to perform operations comprising: recognizing features in digital images;creating a digital image feature map from a digital image;creating a frexel feature map; andgenerating a reconstruction image as an enhancement image based on a difference between values in the digital image feature map and values in the frexel feature map.

8. The system of claim 7, wherein generating the reconstruction image comprises applying a filtering ratio to the digital image feature map.

9. The system of claim 1, wherein a digital image feature map is provided and is based on a plurality of digital images, the reflectance modifying agent being applied based on the digital image feature map.

10. The system of claim 9, wherein the digital image feature map comprises data provided as an average of data across the plurality of digital images.