System and method for hair and scalp health analysis

Abstract

A system for one or more of user hair health and scalp health determination of a user is provided, the system comprising: a hair analysis component configured to: acquire a set of user head images of the user; analyzing the set of user head images to detect one or more head characteristics; a set of user head health scores is calculated based on the detected one or more head characteristics. The system may also output a user head health score.

Description

Technical Field

[0001] The present invention relates to the measurement and analysis of hair and scalp characteristics and health using a hair analysis device attached to a smart phone. Background Art

[0002] Manufacturers of hair and scalp care products create products to help users maintain healthy hair and scalp. However, one of the biggest problems is to determine accurate and useful scores for hair and scalp in order to be able to correctly match and recommend products and treatments.

[0003] There are indeed some solutions that attempt to determine accurate and useful analyses. However, limitations and failures of these solutions are everywhere. For example, existing solutions have inaccurate measurements, variability based on users or situations, high costs, expertise required for operating the solutions or performing the analyses, and logistical challenges such as bulky hardware.

[0004] Therefore, there is a need in the art for an improved method and system capable of determining an accurate hair health and scalp health (collectively referred to herein as "head health") assessment or score. Summary of the Invention

[0005] Provided is a system for head health assessment of a user, the system comprising: a hair analysis component configured to: receive an input to initiate capturing a first set of head images of the user; obtain the first set of head images; send the first set of head images to a trained artificial intelligence system for analyzing a first set of head health characteristics of the first set of head images; receive a first set of head health characteristic results from the trained artificial intelligence system, the first set of head health characteristic results including the position and quantity of each of the first set of head health characteristics in each of the first set of user head images; apply a first set of head health rules to the first set of head health characteristic results; derive a first set of head health assessments based on the application; and report the first set of head health assessments.

[0006] The hair analysis component may include a mobile device and a hair analysis device removably attached to the mobile device.

[0007] The hair analysis component may also be configured to receive a product recommendation based on the first set of head health assessments and report the product recommendation.

[0008] The first set of head images may include a first set of hair images, and the first set of head health characteristics may include a first set of hair health characteristics.

[0009] The first set of hair health characteristics may include heat damage, mechanical damage, and dryness.

[0010] The head health rules can include hair health rules, where the hair health rules include comparing the quantity of each of a first set of hair health characteristics in a hair image with a configurable threshold for each of the first set of hair health characteristics.

[0011] The first set of head images can include a first set of scalp images, and the first set of head health characteristics can include a first set of scalp health characteristics.

[0012] The first set of scalp health characteristics can include small debris, medium debris, and large debris, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0013] The head health rules can include scalp health rules, where the scalp health rules can include comparing the quantity of each of a first set of scalp health characteristics in a scalp image with a configurable threshold for each of the first set of scalp health characteristics.

[0014] The hair analysis device can also include cross-polarized light, and a first subset of the first set of scalp health characteristics can be obtained with the cross-polarized light turned on.

[0015] The first set of head images can include a first set of hair images and a first set of scalp images, and the first set of head health characteristics includes a first set of hair health characteristics and a first set of scalp health characteristics.

[0016] The first set of hair health characteristics can include heat damage, mechanical damage, and dryness, and the first set of scalp health characteristics includes small debris, medium debris, and large debris, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0017] The head health rules include hair health rules and scalp health rules, where the hair health rules can include comparing the quantity of each of a first set of hair health characteristics in a hair image with a configurable threshold for each of the first set of hair health characteristics, and where the scalp health rules can include comparing the quantity of each of a first set of scalp health characteristics in a scalp image with a configurable threshold for each of the first set of scalp health characteristics.

[0018] The obtaining can also include preparing the hair analysis device for the head images to be obtained and the head characteristics to be evaluated by establishing capability settings.

[0019] There is also provided a method for head health assessment of a user, the method comprising: receiving an input by a hair analysis component to initiate capturing a first set of head images of the user; obtaining the first set of head images by the hair analysis component; sending the first set of head images to a trained artificial intelligence system to analyze a first set of head health features of the first set of head images; receiving, by the hair analysis component, a first set of head health feature results from the trained artificial intelligence system, the first set of head health feature results including the position and quantity of each of the first set of head health features in each of the first set of user head images; applying a first set of head health rules to the first set of head health feature results; obtaining a first set of head health assessments based on the application; and reporting the first set of head health assessments.

[0020] The first set of head images may include a first set of hair images, and the first set of head health features includes a first set of hair health features.

[0021] The first set of hair health features may include heat damage, mechanical damage, and dryness.

[0022] The head health rules may include hair health rules, where the hair health rules may include comparing the quantity of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features.

[0023] The first set of head images may include a first set of scalp images, and the first set of head health features may include a first set of scalp health features.

[0024] The first set of scalp health features may include small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0025] The head health rules may include scalp health rules, where the scalp health rules may include comparing the quantity of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

[0026] The hair analysis device may further include cross-polarized light, and a first subset of the first set of scalp health features may be obtained with the cross-polarized light turned on.

[0027] The first set of head images may include a first set of hair images and a first set of scalp images, and the first set of head health features includes a first set of hair health features and a first set of scalp health features.

[0028] The first set of hair health features may include heat damage, mechanical damage, and dryness, and the first set of scalp health features includes small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0029] The head health rules may include hair health rules, where the hair health rules may include comparing the quantity of each of a first set of hair health characteristics in a hair image with a configurable threshold of the first set of hair health characteristics; and scalp health rules, where the scalp health rules may include comparing the quantity of each of a first set of scalp health characteristics in a scalp image with a configurable threshold for each of the first set of scalp health characteristics.

[0030] The obtaining may also include preparing a head analysis device for the head images to be obtained and the head characteristics to be evaluated by establishing capability settings.

[0031] There is a system for one or more of user hair health and scalp health determination for a user, the system including: a hair analysis component configured to: obtain a set of user head images of the user; analyze the set of user head images to detect one or more head characteristics; calculate a set of user head health scores based on the detected one or more head characteristics. The system may also output a user head health rating.

[0032] The hair analysis component may include a mobile device and a hair analysis device attached to the mobile device.

[0033] The hair analysis device may also include cross-polarized light, where the cross-polarized light is used to obtain at least one user head image, and the analysis includes at least one user head image obtained using the cross-polarized light.

[0034] The head characteristics may be one or more of a set of hair characteristics, which may include heat damage, mechanical damage, dryness, and a set of scalp characteristics, which may include small debris, medium debris, and large debris, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0035] The calculation may also be based on one or more hair analysis rules and scalp analysis rules.

[0036] A set of user head health ratings may include one or more hair ratings and one or more scalp ratings.

[0037] The hair analysis component may also be configured to provide product recommendations based on the user head health ratings.

[0038] There is also provided a method for determining one or more of user hair health and scalp health for a user, the method including: obtaining a set of user head images of the user from a hair analysis component; analyzing the set of user head images to detect one or more head characteristics; calculating a set of user head health ratings based on the detected one or more head characteristics; and outputting a user head health rating.

[0039] A hair analysis component may include a mobile device and a hair analysis device attached to the mobile device.

[0040] The hair analysis device may further include cross-polarized light, where the cross-polarized light is used to obtain at least one user head image, and the analysis includes using at least one user head image obtained with cross-polarized light.

[0041] The head characteristics may be one or more of a set of hair characteristics, which may include heat damage, mechanical damage, dryness, and a set of scalp characteristics, and the set of scalp characteristics may include small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

[0042] The calculation may also be based on one or more hair analysis rules and scalp analysis rules.

[0043] A set of user head health scores may include one or more hair scores and one or more scalp scores.

[0044] The method may further include providing product recommendations based on the user head health scores. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The invention is illustrated in the drawings, which are intended as examples and not limitations, where like references are intended to refer to like or corresponding parts, and where:

[0046] Figure 1 Aspects of a hair analysis system according to an embodiment of the invention are shown;

[0047] Figure 2 is a method for determining hair health using a hair analysis system according to an embodiment of the invention; and

[0048] FIGS. 3A-D are exemplary screenshots of an application embodying aspects of the invention;

[0049] FIGS. 4A-C are hair images showing exemplary features useful for hair health assessment;

[0050] FIGS. 5A-G are scalp images showing exemplary features useful for scalp health assessment;

[0051] Figure 6 is a hair image showing the identification of exemplary features related to hair health assessment; and

[0052] Figure 7 is a hair image showing the identification of exemplary features related to hair health assessment. DETAILED DESCRIPTION

[0053] Broadly speaking, system 100 includes a hair analysis component 104 (“HAA”, which may include a hair analysis device 108 - “scanner” that is attached to a mobile device 106, preferably removably attached to the mobile device), which, when used by user 102, performs one or more hair analysis actions, such as capturing an image of the user's hair or face for color assessment, as described herein.

[0054] HAA 104 may be as described in PCT / CA2020 / 050216 or PCT / CA2017 / 050503, or may include another hair analysis system capable of taking images of the user's head that have characteristics sufficient for the analysis described herein. It should be understood that hair analysis component 104 may have hardware components similar to those described therein and be capable of interacting and operating similarly to those described in these references. There may be an application (app) on the HAA that user 102 can use to enable, control, or view the methods described herein.

[0055] Notably, as previously mentioned, system 100 requires the ability to acquire head images (hair images and / or scalp images) that permit the processing described herein. In one embodiment, head images may be taken using cross - polarized light, or using a 10 - megapixel camera with a magnification of not less than 10 times when the cross - polarized light is “on” (e.g., to eliminate glare or reflections of light sources from the head image).

[0056] The user head image may be in one of a variety of color formats, such as LAB or RGB. The user head image may be substantially of any quality, type, format, or size / file size as long as the methods herein can be applied. For example, the image may be compressed or uncompressed, raw or processed, and have various file formats.

[0057] The hair analysis server (HAS) 110 may be a server that stores and processes head characteristic measurements or samples, as described herein. HAS110 may be any combination of a web server, an application server, and a database server, as known to those skilled in the art. Each such server may include typical server components, including a processor, volatile and non - volatile memory storage devices, and software instructions executable thereon. HAS110 may communicate via an application 18 to perform the functions described herein, including exchanging head images, product recommendations, e - commerce capabilities, and the like. Of course, the application may also perform these operations alone or in combination with HAS110.

[0058] HAS110 may include a database server that receives all head feature samples from all users and stores them in the user profiles of each registered user 102 and guest user 102. These may be received from one or more HAAs 104, although the application may be configured to store head images only locally (although this may exclude some of the resulting information based on population and demographic comparisons).

[0059] HAS110 may provide various analysis functions as described herein (such as calculating histograms comparing with user historical results or histograms comparing with peers), and may provide various display functions as described herein (such as providing a website that can present various analyses, providing links or functional links to other websites to access and display such results, recommendations, and the like).

[0060] The product owner 120 may be an entity with hair and scalp care products. For example, the product may be adjusted or selected according to the user's head. The product owner 120 may also have one or more product owner servers, which include web servers, application servers, and database servers, as known to those skilled in the art. Each such server may include typical server components, including a processor, volatile and non-volatile memory storage devices, and software executable thereon. The product owner 120 may be a communication point for the application 18 (directly or through HAS110) for hair analysis measurement samples (such as samples obtained by the user provided to the hair analysis device 20 via the product owner 120) and for storing and executing product recommendation algorithms. For example, HAS110 may store and own one or more general product recommendation algorithms for each product recommendation type, and the product owner may own and implement their own proprietary product recommendation algorithms (for example, the product owner 120 receives the data required to execute the product recommendation algorithm and returns the recommended products).

[0061] The product owner 120 may also directly provide e-commerce services and may recommend suppliers (not shown), such as Amazon TM (alone or with the recommended products), or may not know how the user purchases the recommended products. The product owner 120 may also provide one or more e-commerce websites or screens (separate from or embedded in the application) to facilitate commercial or business transactions involving the transmission of information over the network 130 (such as the Internet). Types of e-commerce websites include, but are not limited to: retail websites, auction websites, and business-to-business websites. Exemplary suppliers that may facilitate the purchase of hair care products may include Amazon TM (Amazon TM ), eBay TM and Overstock TMOf course, the product owner 120 can have their own e-commerce website as part of their general website, or HAS 110 can be such a vendor.

[0062] There may be other users 102 involved in the system 102, such as beauty consultants or counselors who work for the product owner 120 or a commercial website or store, and they can assist the user 102 who is the subject of the image and whose head health is being determined.

[0063] Go to Figure 2 , there is a method 200 for head (hair and / or scalp) health determination and processing.

[0064] When pairing occurs, the method 200 starts at 202.

[0065] The hair analysis device 108 can have an SDK, and the application on the mobile device 104 can use this SDK to access the functions of the HAD 108. The SDK can provide methods for discovering, pairing, and controlling the scanner.

[0066] When the application is launched for the first time, it is recommended to scan, discover, and display all scanners within range (using the scanForDevices method). If only one scanner is discovered after the scan session, consider automatically starting the pairing (connectToDevice method) without displaying the list of discovered scanners. See Figure 3a.

[0067] After successful pairing, to obtain a better user experience, the ID of the paired device can be stored. Then, each time the application is launched continuously, it can be automatically reconnected to the device without repeating the pairing process.

[0068] When the application exits (resign) or leaves the active state (the smartphone enters the sleep state or the application moves to the background), the SDK can automatically disconnect from the scanner. When the application returns to the foreground, the SDK can reconnect to the paired scanner. Note that when performing scanner-related actions, the application should always check whether a valid connection is available. This verification can be part of the pairing at 202.

[0069] The method 200 continues at 204, where alignment occurs. If the scanner is removably attached to the mobile device in a way that ensures correct alignment, this operation can be omitted.

[0070] For clip-on scanner models, the SDK can provide an assistive method to guide the user in aligning the scanner. The scanner needs to be clipped onto the correct camera lens and centered precisely to eliminate any optical distortion or occlusion. The startLensPositioningValidation method can be used to begin tracking the position of the scanner. This method provides continuous status updates on the alignment information. After the user confirms the alignment, the endLensPositioningValidation method needs to be called to stop the alignment status updates. It may be helpful to turn on the LED white light when displaying the camera live view. See Figure 3b.

[0071] At 206 and 208, one or more head health assessments or head health scans are initiated and performed, where a set or sets of head images are obtained.

[0072] The Scanner SDK provides a takeScalpPhoto method to initiate the capture of the user's scalp. Typically, this method should be triggered via a button click or other form of user input to ensure that the user can place the scanner on the scalp (either themselves or their customer). It is recommended to display the live view of the camera simultaneously. An exemplary live view setup for scalp image capture is shown in Figure 3c.

[0073] The Scanner SDK provides a takeHairPhoto method to initiate the capture of the user's hair. Typically, this method should be triggered via a button click to ensure that the user can place the scanner at the end of the hair bundle (either their own or their customer's). It is recommended to display the live view of the camera simultaneously. An exemplary live view setup for hair image capture is shown in Figure 3d.

[0074] Considering the different distance focus for each head image capture (hair image capture and scalp image capture), the initiation of scalp image capture and hair image capture typically does not occur simultaneously. Thus, as part of 206 and / or 208, the HAA can prepare for the specific head image capture being initiated (e.g., by setting the correct focal length, turning on the right light, adjusting to the correct magnification, and the like, i.e., establishing the capability settings applicable to the head image type (hair or scalp) and head characteristics ((one or more) hair characteristics or (one or more) scalp characteristics)). However, the capture of a set of hair images and a set of scalp images can occur in any order.

[0075] In addition, each head image capture can include capturing one or more images using one or more capabilities of the scanner. For example, different lighting, flash, and camera elements / settings (such as magnification, focal length, lights used) can be employed. Each set of settings of the capabilities can be referred to as a capability setting and can be related to the specific type of head image to be captured and the head characteristics to be evaluated. As can be further discussed, cross-polarized light can be used for a scalp image capture (e.g., because it helps identify some of the detected features to evaluate scalp health, namely debris and flaky hair shafts on the scalp). It should be understood that various combinations of images taken with various setting combinations are within the scope of the present invention depending on the health features desired, practicality, hardware of the scanner, etc.

[0076] Image analysis occurs at 210 and includes hair health analysis (analyzing one or more images of a user's hair as described herein) and scalp health analysis (analyzing one or more images of a user's scalp as described herein).

[0077] Analysis can be performed by providing appropriate user head images to an artificial intelligence system, such as a common object detection ML model, e.g., YOLOv2, which is trained to identify one or more hair health features and / or scalp health features (hair health features and scalp health features are examples of head health features). Such an AI system can view the image and locate and quantify the occurrence of such hair health features, such as Figure 6 and Figure 7 those hair health features shown in (as described herein, in head images 600 (hair image) and 700 (scalp image)). After identifying the head health features, various head health rules (hair health rules and scalp health rules) can be applied for head health assessment, such as hair health assessment / scoring and scalp health assessment / scoring, as described herein. The trained artificial intelligence system can be local (e.g., on a mobile device) or remote from the hair analysis component 104.

[0078] Exemplary hair health features and rules and / or scalp health features and rules are described below, but others are possible.

[0079] Hair health analysis (split ends) and hair health characteristics / features

[0080] Processing and output are the detection of heat damage characteristics / attributes (count or quantity, location, and size or severity) (see Figure 4a - possibly due to hair being exposed to high temperatures, such as from hair dryers, irons, etc., and causing the hair to become weak, lose elasticity, and be more prone to damage), mechanical damage (see Figure 4b - possibly caused by improper combing techniques, tension, and overmanipulation, and resulting in thinning of the hair edges, knotting, and excessive splitting and breakage), and dryness (see Figure 4c - possibly caused by dry climate and washing hair too frequently with hot water or lack of heat insulation protection from hair dryers, flat irons, etc., where dry hair may cause the hair to become brittle, resulting in split ends). According to one or more configurable evaluation rules, the algorithm can output an assessment of heat, mechanical, dry (or some combination thereof) damage (user hair score) or not output an injury assessment.

[0081] Exemplary hair analysis or evaluation rules include:

[0082] (a) If the count of "heat damage" feature detection exceeds 4 (or some other configurable number / threshold), then select heat damage as the final analysis assessment; otherwise (ELSE)

[0083] (b) If the count of "mechanical damage" feature detection exceeds 4 (or some other configurable number / threshold), then select mechanical damage as the final analysis assessment; otherwise

[0084] (c) If the count of "dryness" feature detection exceeds 4 (or some other configurable number / threshold), then select dry damage as the final analysis assessment; otherwise

[0085] (d) None.

[0086] It should be understood that each of the above numbers (e.g., the count above "4") is configurable and can vary according to the parameters that determine the composition of a particular feature detection. Additionally, other evaluation rules can be selected, such as by running the system to identify damage and formulating rules based on the observed (human or machine - driven) results.

[0087] It should also be understood that various features (hair and / or scalp) and combinations of features (hair and / or scalp) can be evaluated for any given set of head images, and some or all of the selected features can be used in various rules that can be used to perform one or more evaluations. In one embodiment, heat damage, mechanical damage, and dryness are all features analyzed using hair images and are all factors in rules for evaluating hair health. However, various permutations and combinations are possible.

[0088] Scalp health analysis and scalp health characteristics / features

[0089] Processing and output detect (count or quantity, position, and size or severity) features / characteristics of small debris (see Fig. 5a - preferably using cross - polarized images, where small debris is a small piece of dead scalp skin, usually no larger than 1 mm in diameter, indicating dry scalp), medium - large debris (see Fig. 5b - using cross - polarized images, where medium - large debris is a small piece of scalp dead skin, with a diameter greater than 1 mm and processed separately from small debris as small debris often indicates dry scalp while medium - large debris often indicates dandruff), flaky hair shafts (see Fig. 5c - preferably using cross - polarized images, where flaky hair shafts are unhealthy hair shafts covered with small pieces of fine scalp dead skin, indicating dry scalp, which can be separately identified by an AI tool and thus used separately from other flakes), flaky scalp (see Fig. 5d - preferably using cross - polarized images, where flaky scalp is a small piece of scalp dead skin that is still partially attached to the scalp and is turning into a large piece. Like flaky hair shafts, this structure has unique visual characteristics, mainly being translucent and never attached to the hair shaft, which may require an ML model to treat it as a separate feature), oil pools (see Fig. 5e - preferably not using cross - polarized images, where an oil pool is the scalp condition when there is excessive oil accumulation around the hair shaft. It can be described as a translucent circle formed around the hair shaft. The presence of these features indicates oily scalp), sticky hair shafts (see Fig. 5f - preferably not using cross - polarized images, where sticky hair shafts are an oily scalp feature indicating excessive oil around the hair shaft, which can be described as a translucent substance accumulated around the hair shaft, and the presence of these features can indicate excessive scalp oil), and deposits (see Fig. 5g - not using cross - polarized images, where deposits can be caused by excessive oil and dry scalp and, in rare cases, by product buildup). Although deposits visually resemble "sticky hair shafts", a distinction can be made as it is usually not translucent and there are usually tiny particles around the hair shaft). Based on one or more configurable evaluation rules, the algorithm can output an assessment of oily, buildup, flaky, or normal damage.

[0090] Exemplary scalp assessment or analysis rules include:

[0091] (a) If the detection count of the "oil pool" + "sticky hair shaft" features is equal to or greater than 4, then select oily damage as the final analysis assessment; otherwise (ELSE)

[0092] (b) If the detection count of the "deposit" feature is equal to or greater than 2, and the "sum of all debris detections" ("small debris" + "medium - large debris" + "flaky hair shafts" + "flaky scalp") is lower than the "deposit" count multiplied by 5, then select deposits; otherwise

[0093] (c) If the sum of all debris detections ("small debris" + "medium and large debris" + "flaky dry hair" + "flaky scalp") feature detection count exceeds 4 or "flaky scalp" is equal to or greater than 1, then select flaky; otherwise

[0094] (d) None.

[0095] It should be understood that each of the above numbers (e.g., the count above "4") is configurable and can vary depending on the parameters that determine the composition of a particular feature detection. Additionally, other evaluation rules can be selected, such as by running the system to identify damage and formulating rules based on the observed (human or machine-driven) results.

[0096] It should also be understood that various features (hair and / or scalp) and combinations of features (hair and / or scalp) can be evaluated for any given set of head images, and some or all of the selected features can be used in various rules that can be used to perform one or more evaluations. In one embodiment, oil pools, sticky dry hair, small debris, medium and large debris, flaky dry hair, and flaky scalp are all features of scalp image analysis and are all factors in rules for evaluating scalp health. However, various permutations and combinations are possible.

[0097] At 212, the head health assessment and head health assessment data (which can include the underlying user head image, the processed user head image showing the detected features, the score, and the assessment) can be reported or saved (e.g., displayed on a mobile device, sent to cloud storage, such as to product owner 120 or hair analysis server 110, etc.). In addition to reporting and saving, one or more product recommendations can also be provided to the user to assist them in their head health assessment. The product owner can also make recommendations based on their understanding of how the product affects head health features and the user's answers to questions about their experiences and goals.

[0098] The above embodiments of the present disclosure can be implemented in any of a variety of ways. For example, the embodiments can be implemented using hardware, software, or a combination thereof. When implemented in software, the software code can be executed on any suitable processor or set of processors, whether provided in a single computer or distributed across multiple computers.

[0099] Furthermore, the various methods or processes outlined herein can be encoded as software executable on one or more processors employing any of a variety of operating systems or platforms. Additionally, such software can be written using any of a variety of suitable programming languages and / or programming or scripting tools, and can also be compiled into executable machine language code or intermediate code executable on a framework or virtual machine.

[0100] In this regard, the concepts disclosed herein can be embodied as a non-transitory computer-readable medium (or multiple computer-readable media) (e.g., computer memory, one or more floppy disks, optical disks, optical discs, magnetic tapes, flash memories, circuit configurations in a field-programmable gate array or other semiconductor devices, or other non-transitory, tangible computer storage media) encoded with one or more programs that, when executed on one or more computers or other processors, perform the methods implementing the various embodiments of the present disclosure above. The computer-readable medium or media can be transportable such that the programs stored thereon can be loaded onto one or more different computers or other processors to implement the various aspects of the present disclosure as described above.

[0101] The terms "program", "application program", or "application" or "software" are used herein to refer to any type of computer code or set of computer-executable instructions that can be used to program a computer or other processor to implement the various aspects of the present disclosure as described above. Further, it should be understood that, according to one aspect of this embodiment, one or more computer programs that, when implemented, execute the methods of the present disclosure need not reside on a single computer or processor but can be distributed in a modular fashion among multiple different computers or processors to implement the various aspects of the present disclosure.

[0102] Computer-executable instructions can be in many forms, such as program modules executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Generally, in various embodiments, the functions of program modules can be combined or distributed as needed.

[0103] In addition, data structures can be stored in a computer-readable medium in any suitable form. For simplicity of illustration, a data structure can be shown as having fields related by their positions in the data structure. This relationship can equally be achieved by allocating storage locations for the fields in a computer-readable medium that conveys the relationship between the fields. However, any suitable mechanism can be used to establish the relationship between the information in the fields of a data structure, including by using pointers, tags, or other mechanisms that establish relationships between data elements.

[0104] The various features and aspects of the present disclosure can be used alone, in any combination of two or more, or in various arrangements not specifically discussed in the above embodiments, and thus their application is not limited to the details and arrangements of the components set forth in the above description or shown in the drawings. For example, the multiple aspects described in one embodiment can be combined with the multiple aspects described in other embodiments in any manner.

[0105] Furthermore, the concepts disclosed herein can be implemented as a method, for which an example has been provided. The actions performed as part of the method can be ordered in any suitable way. Thus, embodiments can be constructed that perform the actions in an order different from the order shown, which can include performing some actions simultaneously, even if shown as sequential actions in the exemplary embodiments.

[0106] The use of sequential terms such as "first", "second", and "third" in the claims to modify the claim elements themselves does not mean any priority, precedence, or order of one claim element with respect to another, nor does it mean the temporal order of performing method acts, but is merely used as a label to distinguish one claim element having a particular name from another element having the same name (but for which the sequential term is used), to distinguish claim elements.

[0107] Furthermore, the language and terminology used herein are for descriptive purposes only and should not be regarded as limiting. The terms "comprising", "including", "having", "containing", "involving", and their variants as used herein are intended to include the items listed hereinafter and their equivalents as well as additional items.

[0108] Several (or different) elements discussed and / or claimed hereinafter are described as "coupled", "communicating with", or "configured to communicate with". The term is intended to be non - restrictive and, where appropriate, should be interpreted to include, but not be limited to, wired and wireless communication using any one or more suitable protocols, and communication methods that are continuously maintained, performed periodically, and / or initiated as needed.

[0109] Embodiments can also be implemented in a cloud computing environment. In this specification and the following claims, "cloud computing" can be defined as a model for enabling ubiquitous, convenient, on - demand network access to a shared pool of configurable computing resources (such as networks, servers, memory, applications, and services), which can be rapidly provisioned through virtualization and released with minimal management effort or service provider interaction, and then scaled accordingly. The cloud model can consist of various characteristics (such as, on - demand self - service, broad network access, resource pooling, rapid elasticity, measurable service, etc.), service models (such as software as a service ("SaaS"), platform as a service ("PaaS"), infrastructure as a service ("IaaS")), and deployment models (such as private cloud, community cloud, public cloud, hybrid cloud, etc.).

[0110] This written description uses examples to disclose the invention and enable those skilled in the art to make and use the invention. The patentable scope of the invention is defined by the claims and may include other examples that occur to those skilled in the art. If these other examples have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements that do not differ materially from the literal language of the claims, then these other examples are within the scope of the claims.

[0111] It is understood that the above components and modules can be connected to each other as needed to perform the required functions and tasks within the scope of those skilled in the art, such that such combinations and arrangements can be made without having to describe each one in explicit terms. No particular component or part can be superior to any equivalents available to those skilled in the art. As long as these functions can be performed, there is no particular way that can be superior to other ways of implementing the disclosed subject matter. It is believed that all key aspects of the disclosed subject matter have been provided herein. It should be understood that the scope of the invention is limited to the scope provided by the independent claims, and it should also be understood that the scope of the invention is not limited to: (i) the dependent claims, (ii) the detailed description of the non-limiting embodiments, (iii) the summary of the invention, (iv) the abstract, and / or (v) the description provided outside of this document (i.e., outside of the present application as filed, prosecuted, and / or granted). For this document, it is understood that the phrase "comprising" is equivalent to the word "including". The above outlines non-limiting embodiments (examples). Specific non-limiting embodiments (examples) have been described. It should be understood that the non-limiting embodiments are provided only as examples.

Claims

1. A system for head health assessment of a user, the system comprising: a hair analysis component configured to: receive an input to initiate capture of a first set of head images of the user; obtain the first set of head images; send the first set of head images to a trained artificial intelligence system for analyzing a first set of head health features of the first set of head images; receive a first set of head health feature results from the trained artificial intelligence system, the first set of head health feature results including the location and quantity of each of the first set of head health features in each of the first set of user head images; apply a first set of head health rules to the first set of head health feature results; derive a first set of head health assessments based on the application; and report the first set of head health assessments.

2. The system according to claim 1, wherein the hair analysis component comprises a mobile device and a hair analysis device removably attached to the mobile device.

3. The system according to claim 1, wherein the hair analysis component is further configured to receive and report product recommendations based on the first set of head health assessments.

4. The system according to claim 1, wherein the first set of head images comprises a first set of hair images, and the first set of head health features comprises a first set of hair health features.

5. The system according to claim 4, wherein the first set of hair health features comprises heat damage, mechanical damage, and dryness.

6. The system according to claim 5, wherein the head health rules comprise hair health rules, and the hair health rules comprise comparing the quantity of each of the first set of hair health features in the hair images with configurable thresholds for each of the first set of hair health features.

7. The system according to claim 1, wherein the first set of head images comprises a first set of scalp images, and the first set of head health features comprises a first set of scalp health features.

8. The system according to claim 7, wherein the first set of scalp health features comprises small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

9. The system according to claim 8, wherein the head health rules comprise scalp health rules, and the scalp health rules comprise comparing the quantity of each of the first set of scalp health features in the scalp images with configurable thresholds for each of the first set of scalp health features.

10. The system according to claim 9, wherein the hair analysis device further comprises cross-polarized light, and wherein the obtaining is to obtain a first subset of the first set of scalp health features with the cross-polarized light turned on.

11. The system according to claim 1, wherein the first set of head images comprises a first set of hair images and a first set of scalp images, and the first set of head health features comprises a first set of hair health features and a first set of scalp health features.

12. The system according to claim 11, wherein the first set of hair health characteristics includes thermal damage, mechanical damage, and dryness, and the first set of scalp health characteristics includes small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

13. The system according to claim 12, wherein the head health rules include hair health rules and scalp health rules, wherein the hair health rules include comparing the quantity of each of the first set of hair health characteristics in the hair image with a configurable threshold for each of the first set of hair health characteristics, and wherein the scalp health rules include comparing the quantity of each of the first set of scalp health characteristics in the scalp image with a configurable threshold for each of the first set of scalp health characteristics.

14. The system according to claim 13, wherein the obtaining further includes preparing the head analysis device for the head images to be obtained and the head characteristics to be evaluated by establishing capability settings.

15. A method for head health assessment of a user, the method comprising: receiving, by a hair analysis component, an input to initiate the capture of a first set of head images of the user; obtaining, by the hair analysis component, the first set of head images; sending the first set of head images to a trained artificial intelligence system to analyze a first set of head health characteristics of the first set of head images; receiving, by the hair analysis component, from the trained artificial intelligence system a first set of head health characteristic results, the first set of head health characteristic results including the location and quantity of each of the first set of head health characteristics in each of the first set of user head images; applying a first set of head health rules to the first set of head health characteristic results; deriving a first set of head health assessments based on the application; and reporting the first set of head health assessments.

16. The method according to claim 15, wherein the first set of head images includes a first set of hair images, and the first set of head health characteristics includes a first set of hair health characteristics.

17. The method according to claim 16, wherein the first set of hair health characteristics includes thermal damage, mechanical damage, and dryness.

18. The method according to claim 17, wherein the head health rules include hair health rules, and the hair health rules include comparing the quantity of each of the first set of hair health characteristics in the hair image with a configurable threshold for each of the first set of hair health characteristics.

19. The method according to claim 15, wherein the first set of head images includes a first set of scalp images, and the first set of head health characteristics includes a first set of skin health characteristics.

20. The method according to claim 19, wherein the first set of scalp health characteristics includes small flakes, medium flakes, and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

21. The method according to claim 20, wherein the head health rules include scalp health rules, and wherein the scalp health rules include comparing the quantity of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

22. The method according to claim 21, wherein the hair analysis device further includes cross-polarized light, and wherein the obtaining is obtaining a first subset of the first set of scalp health features with the cross-polarized light turned on.

23. The method according to claim 15, wherein the first set of head images includes a first set of hair images and a first set of scalp images, and the first set of head health features includes a first set of hair health features and a first set of scalp health features.

24. The method according to claim 23, wherein the first set of hair health features includes thermal damage, mechanical damage, and dryness, and the first set of scalp health features includes small debris, medium debris, and large debris, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and deposits.

25. The method according to claim 24, wherein the head health rules include hair health rules and scalp health rules, and wherein the hair health rules include comparing the quantity of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features, and wherein the scalp health rules include comparing the quantity of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

26. The method according to claim 25, wherein the obtaining further includes preparing the head analysis device for the head images to be obtained and the head characteristics to be evaluated by establishing capability settings.

Images