Hair drying apparatus control refinement method, refinement system, drying method and related hair drying assembly

Abstract

The present invention relates to a method for controlling a hair drying device (10) with finer control, the method being implemented by a control finer system, the method being characterized by the following steps: determining (104) the control mode of the hair drying device (10) using at least one characteristic parameter of the user's hair determined using information representing the user's hair.

Description

Technical Field

[0001] This invention relates to a hair drying device control refinement method implemented by a control refinement system.

[0002] In particular, this computer-implemented approach aims to provide users with customized recommendations for using hair drying equipment, and / or to automatically implement such recommendations within the hair drying equipment. Background Technology

[0003] When users go to a hair salon or wash their hair at home, they often have to use hair drying equipment, not only to dry their hair but also to create a hairstyle that suits them.

[0004] Conventional hair drying equipment includes multiple control modes, such as two or three modes, in which the speed and / or temperature of the hot air generated by the hair drying equipment varies.

[0005] When users use the drying device, they can, for example, select the first control mode to pre-dry their hair and select the second control mode to create their desired hairstyle.

[0006] In particular, in salons, hairstylists tend to use control modes that generate the highest temperature and air velocity to create hairstyles according to the user's desired style.

[0007] Therefore, drying equipment control is very basic and not entirely satisfactory in terms of aesthetic appeal and energy consumption. In fact, control modes with high temperatures and air speeds are sometimes unsuitable for certain hair types.

[0008] In addition, this control mode is typically used for styling hair and is used for the longest time, which essentially affects the energy consumption of the hair drying equipment. Summary of the Invention

[0009] The purpose of this invention is to achieve control of a hair drying device that produces more satisfactory results for creating a user's hairstyle, while minimizing the energy consumption of the hair drying device as quickly as possible.

[0010] Therefore, the present invention relates to the method described above, characterized by the following steps: - The control mode of the hair drying device is determined using at least one characteristic parameter of the user's hair, which is determined using information representing the user's hair.

[0011] By using characteristic hair parameters obtained using information representing the user's hair, a customized control mode for the hair drying device can be selected that is suitable for the user's hair and uses the correct energy required to achieve the result.

[0012] Therefore, the computer-implemented method according to the invention allows users to receive dryer control recommendations that they can approve, or the controls can be automatically transmitted to the dryer for customized and economical operation.

[0013] The method according to the present invention may include the following steps: - Receive information representing the user's hair; - Determine at least one characteristic parameter of the user's hair based on information representing the hair.

[0014] Receiving information representing a user's hair allows the system to determine characteristic hair parameters based on representative information, and thus obtain the control mode most suitable for the user.

[0015] The method according to the present invention may include the following features: - Representative information includes visual representation data of the user's hair and / or at least one feature data of the user's hair, entered by the operator on a computer terminal.

[0016] Therefore, whether in the form of a visual representation of the user's hair or / and in the form of input of at least one additional feature data of the user's hair, the user can obtain relevant representative information to determine the control mode.

[0017] The method according to the present invention may include the following features: - The visual representation data of the user's hair includes at least one image of the user's hair.

[0018] Receiving representative information in the form of at least one digital image of the hair allows for image analysis (or "machine vision"), which ensures the accurate determination of the hair's characteristic parameters that can be used to implement the method. Capturing images of the hair is a simple implementation method, especially for the user, and image analysis is very effective for determining characteristic parameters.

[0019] The method according to the invention may also include one or / and another of the following features: - The method includes a preliminary step of acquiring at least one image of the user's hair using a camera; - The camera is carried by a mobile electronic device, a device for diagnosing a user's hair and / or head, or a hair drying device, wherein the mobile electronic device is in particular a mobile phone, tablet computer, or laptop computer.

[0020] For users, the initial steps of acquiring at least one image with the help of a camera are easy to perform, especially when the camera is carried by a mobile device (such as a mobile phone or tablet) or a hair diagnostic device.

[0021] In addition, the hair drying equipment itself can be equipped with such a camera, which simplifies gestures and allows users to provide the most accurate image of their hair as if the drying process were to be carried out.

[0022] The method according to the present invention may include the following features: - By using image analysis of at least one image of a user's hair, advantageously using a deterministic model for determining feature parameters and / or using a model for determining feature parameters through artificial intelligence, the determination of at least one feature hair parameter is performed.

[0023] Determining feature parameters using a deterministic model ensures good determination accuracy, regardless of the representativeness of the information provided.

[0024] Based on learning that can be performed by a large number of users, especially in the field of hair drying, the determination made by artificial intelligence models provides a wider variety of modulations for obtaining representative information on feature parameters, since potentially all users of the drying equipment can contribute to such models.

[0025] The method according to the present invention may include the following features: Implementing a deterministic model involves determining the location of the hair root in the hair, then creating a hair segmentation mask using the hair root location, and using the hair segmentation mask to perform calculations of individual feature parameters or per feature parameter.

[0026] Determining the location of the hair root and subsequently creating a segmentation mask allows for easy and accurate access to multiple characteristic hair parameters, particularly size-related hair features such as hair density and / or average hair diameter.

[0027] The method according to the present invention may include the following features: The determination step includes determining the hair curliness level by using image analysis of at least one image of the user's hair, advantageously using a deterministic model and / or an artificial intelligence determination model.

[0028] To obtain the most suitable results, determining the hair curl pattern is particularly important for appropriate customization of the control mode of the hair drying equipment. Different hair curl patterns can be easily classified into different levels, which limits the number of influences and conditions to be handled in the control determination model.

[0029] The method according to the present invention may include at least one of the following features: - At least one feature determined using information representing hair is selected from average hair diameter, local hair curvature, hair density, and hair curl grade; - The method includes the following steps: determining at least one customized data of the user, particularly the user's gender, age and / or cranial sensitivity, and using the user's customized data or each customized data to perform the determination of a control mode for the hair drying device.

[0030] Selecting characteristic hair parameters from the average hair diameter, hair density, local hair curvature, and / or curl of the hair present in the user's hair provides characteristic parameters that can be easily determined by analyzing information representative of the hair; however, these parameters are rich in content and vary from user to user.

[0031] This allows for good differentiation among users, enabling the application of the most personalized hair drying device control modes to each user.

[0032] The method according to the present invention may include at least one of the following features: - The control mode defines at least one operating parameter of the hair drying device, which is selected from drying airflow temperature, drying airflow velocity, hair illumination intensity of the light source present in the hair drying device, drying time and / or illumination time; - The control mode defines the operating parameters based on the drying stage, which is advantageously determined by pre-drying, hair-spraying, and / or diffusion.

[0033] The device offers a variety of hair treatment options by allowing users to select operating parameters such as drying air temperature, drying air speed, optional hair illumination, and / or drying time, based on the determined characteristic parameters, thereby ensuring effective and customized hair drying.

[0034] This is especially true when the control mode is further set according to the drying stage, because the results produced by drying can be completely different depending on the drying stage.

[0035] The method according to the present invention may include the following features: - Determining the control mode includes consulting a database defining multiple control modes that can be applied by the hair drying device based on the determined characteristic parameters or each characteristic parameter, and optionally based on at least one customized data from the user, and / or determining the control mode includes implementing a deterministic or artificial intelligence model that uses the determined characteristic parameters or each characteristic parameter and optionally at least one customized data from the user to calculate the control mode.

[0036] Consulting a database provides a relatively simple way to link control modes with characteristic parameters. For example, the database can be directly integrated into hair drying devices without requiring significant hardware or software resources.

[0037] Using deterministic or AI-based deterministic models may require more resources, but it can offer more options for dry adaptation and customization.

[0038] The present invention also relates to a system for refining the control of a hair drying device, comprising: - A module for determining the control mode of a hair drying device using at least one characteristic parameter of a user's hair determined using information representing the user's hair.

[0039] The system according to the present invention may include: - A module for receiving information representing the user's hair; - A module used to determine at least one characteristic parameter of a user's hair based on information representing the hair.

[0040] This invention also relates to a hair drying method, comprising the following steps: - Implement the refined control method for hair drying equipment as defined above; - Transmit the determined control mode to the hair drying equipment; - Display the control mode determined by the hair drying equipment or / and implement the control mode determined by the hair drying equipment.

[0041] The present invention also relates to a hair drying assembly, comprising: - A hair drying device, the hair drying device including an airflow generator, an airflow temperature control system and an optional light source, the device also including a control unit configured to drive the airflow generator, the airflow temperature control system and the optional light source; - A refinement system for refining the control as defined above, the refinement system being configured to be connected to the control unit via a data transmission link, the control unit being configured to receive the control mode determined by the refinement system.

[0042] The components according to the present invention may include the following features: - The refinement system is carried and hosted in a computer system by hair drying equipment, portable electronic devices (especially mobile phones or tablets), hair diagnostic equipment.

[0043] When the refinement system is carried out by a hair drying device, the hair drying device autonomously determines the optimal control model for a given user based entirely on information representing the hair of that user.

[0044] When the refinement system is installed in a portable electronic device, the user can easily implement the refinement method. When the refinement system is installed in a remote computer device, the appropriate computing power can be used to perform simple remote queries to obtain the optimal control mode. Attached Figure Description

[0045] The invention will be more readily understood after reading the following description, which is provided by way of example only and with reference to the accompanying drawings, in which: -[ Figure 1 ] Figure 1 This is a schematic diagram of a hair drying assembly, which includes an acquisition system for acquiring information representing a user's hair, a refinement system for refining the control of the hair drying device, and the hair drying device itself. -[ Figure 2 ] Figure 2 This is a schematic diagram illustrating an implementation of a method for refining the control of a hair drying device according to the present invention; -[ Figure 3 ] Figure 3 It is a detailed view of the steps to determine characteristic hair parameters based on representative information formed from one or more images of hair. Detailed Implementation

[0046] exist Figure 1 The schematically illustrated component 12 illustrates an example of a method for refining the control of the hair drying device 10 according to the present invention.

[0047] In addition to the hair drying device 10, component 12 also includes an acquisition system 14 for acquiring information representing the user's hair, and a refinement system 16 for refining the control of the hair drying device 10 using the representative information acquired by the acquisition system 14.

[0048] In a known manner, a hair drying device 10 includes a handle 20 intended to be held by a user, a head 22 intended to spray airflow (particularly hot airflow) and / or light flux onto the user's hair, and a control interface 24 of the hair drying device 10, for example, disposed on the handle 20 and controlled by the user.

[0049] The hair drying device 10 also includes: an airflow generator 26, for example disposed in the handle 20 and / or the head 22, configured to generate an airflow at a controlled speed VA; and a regulating system 28 for regulating the temperature TA of the airflow, for example disposed in the head 22.

[0050] The hair drying device 10 also includes at least one light source 30, particularly a light source in the infrared range (e.g., wavelengths between 800 nanometers and 2 micrometers).

[0051] Finally, the hair drying device 10 includes a control unit 32 disposed in the handle 24 or the head 22 and connected to the interface 24. The control unit 32 is configured to control at least one operating parameter of the hair drying device 10, specifically the airflow speed VA generated by the generator 26, the airflow temperature TA regulated by the regulating system 28, the light emission intensity IE emitted by the light source 30, and / or the airflow and / or light emission generation time DA, DE.

[0052] Advantageously, the control unit 32 preferably includes at least one processor and at least one memory, the at least one memory including software modules executable by the processor. Alternatively, the control unit 32 is implemented in the form of at least one programmable logic component (such as a FPGA (Field Programmable Gate Array)) or application-specific integrated circuit (such as an ASIC (Application Specific Integrated Circuit)).

[0053] In one embodiment, the control unit 32 is configured to operate according to a defined number of discrete control modes (e.g., according to...). Figure 2 The five control modes (A to E) shown are used to drive the operation of the hair drying device 10, and specifically drive the emission of airflow and / or light flux.

[0054] Each control mode is defined, for example, by at least one operating parameter selected from airflow temperature TA, airflow velocity VA, drying time DS, and / or optional light emission intensity IE and light emission time DE.

[0055] Preferably, each control mode is defined for a specific drying stage (e.g., pre-drying stage P1, hair styling stage P2, or diffusion stage P3).

[0056] Instead, the control mode is not a predefined discrete mode, but rather an operating point corresponding to a series of control modes defined by a series of continuous evolutions of the aforementioned operating parameters based on a given drying stage.

[0057] refer to Figure 1 The hair drying device 10 includes at least one wired or wireless data transmission interface 34, which is configured to receive at least one control mode selected from a predefined mode or determined from a series of control modes from the refinement system 16.

[0058] Wireless transmission interfaces include, for example, Bluetooth or Wi-Fi protocols. Wired transmission interfaces include, for example, USB ports.

[0059] In one example, the control unit 32 is configured to activate the flow generator 26, the conditioning system 28, and / or the light source 30 when a control mode is received via the transmission interface 34, so as to automatically apply the operating parameters of the received control mode without user interaction.

[0060] Alternatively, the control unit 32 is configured to display the control modes suggested by the refinement system 16 on the control interface 24 to allow the user to confirm whether to implement the control mode.

[0061] In another variation, the control unit 32 is configured to receive a control mode previously checked and verified by the user from an external system (e.g., from the acquisition system 14), and to automatically implement the control mode if a previous control mode verification message is received along with the control mode.

[0062] The representative information acquisition system 14 preferably includes: at least one camera 40 configured to acquire at least one image of a user's hair; and at least one user interface 42 configured to control the camera 40 and optionally guide the user to capture images of the hair through the camera.

[0063] In addition, user interface 42 can allow users to input at least one feature data of the user's hair (e.g., measured hair thickness) or respond to a questionnaire designed to identify feature data of the hair.

[0064] The acquisition system 14 also includes at least one data transmission interface 42, which is designed to send the images or each image and / or the feature data or each feature data acquired by the camera 40 to the refinement system 16.

[0065] Preferably, the acquisition system 14 includes a computer 46, which includes at least one processor and at least one memory, the at least one memory being designed to implement software modules for executing applications (particularly an image acquisition application displayed on the user interface 42).

[0066] Preferably, the user interface 42 includes a display screen and at least one hardware or software control button configured to trigger the camera 40 to capture an image of the user's hair.

[0067] Advantageously, such as Figure 2 As shown, the acquisition system 14 is an electronic device 50, particularly a mobile electronic device, such as a mobile phone, tablet computer, or laptop computer.

[0068] Alternatively, the acquisition system 14 is a diagnostic system 52 for diagnosing the user's skull and / or hair.

[0069] Alternatively, the acquisition system 14 may include a camera 40 mounted directly on the hair drying device 10. Advantageously, the acquisition system 40 may not have a user interface 42.

[0070] The transmission interface 44 is configured to transmit the images or each image captured by the camera 40 to the refinement system 16.

[0071] The transmission interface 44 is, for example, a wireless transmission interface, especially a Wi-Fi or Bluetooth protocol transmission interface, or a wired transmission interface, especially when the camera 40 is mounted on the hair drying device 10.

[0072] Preferably, the user interface 42 includes at least one software application to guide the user to indicate which photos of their hair need to be taken, particularly frontal photos, top photos, and / or photos of at least one strand of hair, such as... Figure 2 As shown in the top left corner.

[0073] The refinement system 16 is configured to receive, in particular, information representing a user's hair from the acquisition system 14. The refinement system is configured to use the representative information to determine at least one characteristic hair parameter, and then use the determined characteristic parameter, or each characteristic parameter, to determine the control mode of the hair drying device 10.

[0074] The refinement system is also configured to transmit the determined control to the hair drying device 10 to perform the control, or optionally to the acquisition system 14 to obtain user approval.

[0075] exist Figure 1 In the schematically illustrated embodiment, the refinement system 16 is shown independently of the hair drying device 10 or the representative information acquisition system 14.

[0076] The hair styling system is advantageously hosted in a computer system independent of the hair drying device 10 and the acquisition system 14, particularly in a cloud computer system referred to using the term "cloud". Alternatively, the hair styling system 16 is hosted by the acquisition system 14 and / or by the hair drying device 10.

[0077] like Figure 1 As shown, the detailed system 16 includes a computer, which includes a processor 60 and a memory 62, the memory 62 including software modules intended to be executed by the processor 60 to perform the functions of the aforementioned modules.

[0078] Alternatively, the computer is implemented in the form of programmable logic components (such as FPGAs (Field Programmable Gate Arrays)) or integrated circuits (such as ASICs (Application-Specific Integrated Circuits)) capable of performing the functions of the aforementioned modules.

[0079] exist Figure 1In the example, the refinement system 16 includes a receiving module 64 for receiving information representing a user's hair, a determining module 66 for determining using information representing at least one characteristic hair parameter, and a determining module 68 for determining a control mode of the hair drying device 10 using the characteristic parameter or each characteristic parameter determined by the determining module 66.

[0080] Furthermore, advantageously, the refinement system 16 includes a module 70 for automatically or, upon user approval, transmitting the control mode to the hair drying device 10 and / or the acquisition system 14 to present the determined control mode to the user and / or for the hair drying device 10 to implement the control mode.

[0081] The receiving module 64 is configured to communicate with the transmission interface 44 to receive information representing hair, specifically one or more images of hair taken using the camera 40 of the acquisition system 14. Figure 3 An example of image 72 is shown.

[0082] Optionally, the receiving module 66 is configured to process the image 72 to improve its sharpness and / or its contrast.

[0083] The feature parameter determination module 66 is configured to process representative information to infer at least one feature hair parameter from it.

[0084] Characteristic hair parameters include, for example, the average hair diameter DM, hair density DC, local hair curvature CL, and curl grade CF of a single hair present in the hair.

[0085] Advantageously, the determining module 66 is also configured to use information representing hair (in particular, using at least one image of hair taken by the camera 40 of the acquisition system 14) to determine user-customized data, in particular user gender G, user age A, or user cranial sensitivity SC.

[0086] The determination of the feature parameters, or each feature parameter, is performed, for example, by a deterministic model for processing representative information. The deterministic model implements, for example, image analysis (or “machine vision”) algorithms to extract at least one feature parameter as defined above from at least one image 72 of a user’s hair captured by camera 40 and received by receiving module 64.

[0087] For example, in Figure 3 In the example, the deterministic model is configured to determine the location 74 of the root of each individual hair present in image 72, and then determine a segmentation mask 76 from each location 74 for segmenting the image to identify the different individual hairs 78 present in image 72.

[0088] The segmentation mask specifically identifies pixels in image 72 that belong to each individual hair 78, and conversely identifies pixels in image 72 that do not belong to any hair.

[0089] Using a segmentation mask, the deterministic model calculates the average diameter of each individual hair (78), and then calculates the average hair diameter (DM). The deterministic model then calculates the hair density (DC).

[0090] exist Figure 3 In the example, the deterministic model also determines the skull sensitivity SC based on the color of the skull, and determines the user's gender G and age A based on hair type 78 and size.

[0091] Alternatively, gender and age are input by the user using the acquisition system 14 during image capture by the camera 40 and are transmitted to the receiving module 64, and then to the determining module 66.

[0092] Similarly, the feature parameter determination module 66 is configured to use the hair bundle image 80 to classify the hair present in the image 80 according to the curl level CF of the user hair from multiple predefined curl level CFs.

[0093] For example, based on the wave pattern of the hair (see example). Figure 3 Grades 2a, 2b, and 2c are also used, and the presence and size of curls on the hair are also considered. Figure 3 The predefined curl level CF is defined using levels 3a, 3b, 3c and 4a, 4b and 4c.

[0094] Alternatively, the model used to determine at least one feature parameter is an artificial intelligence determination module using, for example, a neural network.

[0095] A neural network consists of a series of ordered neural layers, with each layer receiving input from the output of the previous layer.

[0096] More specifically, each layer consists of neurons whose inputs come from the outputs of neurons in the previous layer or from input variables in the first layer.

[0097] Alternatively, one could consider more complex neural network structures where a layer can connect to layers further away than the layer immediately preceding it.

[0098] The operations performed by the neurons in the corresponding processing layer (i.e., the type of processing) are also associated with each neuron.

[0099] Each layer is connected to other layers via multiple synapses. Synaptic weights are associated with each synapse, and each synapse forms a link between two neurons. Synaptic weights are typically real numbers, which can take both positive and negative values. In some cases, synaptic weights are complex numbers.

[0100] Each neuron can perform a weighted summation of values ​​received from neurons in the previous layer, then multiply each value by the corresponding synaptic weight of each synapse or connection between that neuron and the neurons in the previous layer. An activation function (typically a non-linear function) is then applied to this weighted summation, and the value obtained by applying the activation function is output from that neuron, particularly to the neurons in the next layer connected to it. The activation function allows the introduction of non-linearity into the processing performed by each neuron. Examples of activation functions include the sigmoid function, the hyperbolic tangent function, and the Heaviside function.

[0101] Alternatively and optionally, each neuron may further apply a multiplicative factor (also known as a bias) to the output of the activation function, and the value output from the neuron is then the product of the bias value and the value obtained from the activation function.

[0102] Advantageously, the input parameters of the neural network are, for example, at least one image 72 of hair previously transmitted to the receiving module 64, captured by the user using camera 40.

[0103] The output parameters of the neural network are specifically selected from one or more feature parameters, such as average hair diameter DM, hair density DC, local hair curvature CL, and hair curl level CF.

[0104] For example, a neural network is trained by submitting multiple images of hair taken on a user, where previous image analysis has been performed to determine each feature parameter present in the images.

[0105] Similarly, AI-based identification models can be used to identify user-specific data using representative information, particularly the user's gender (G), age (A), or sensitivity of the user's head (SC).

[0106] For example, a neural network can be trained by submitting multiple images of hair taken on a user, where previous image analysis has already been performed to determine each customized data point.

[0107] The control mode determination module 68 is configured to, for example, associate a customized control mode with characteristic parameters of the user's hair, the control mode being selected from multiple discrete control modes (such as... Figure 2 (As shown in modes A to E) or a custom control mode selected from a range of possible control modes.

[0108] As described above, each control mode defines multiple operating parameters of the hair drying device 10 based on the characteristic parameters determined by the characteristic parameter determination module 66.

[0109] In one example, the control mode determination module 68 is configured to query the database 90 of the determined control mode based on one or more characteristic parameters and / or the hair drying stage.

[0110] exist Figure 1 In the example shown, database 90 is received in the memory of refinement system 16. Alternatively, database 90 is hosted in a separate computer system from refinement system 16 and queried by refinement system 16 using a data transmission link.

[0111] exist Figure 2 In the example shown, database 90 is schematically represented by a table showing control modes M ranging from A to E selected according to drying stages P1 to P3. Specifically, each mode A to E includes multiple operating parameters according to drying stages P1 to P3, such as airflow temperature TA and airflow velocity VA associated with each mode A to E for each drying stage P1 to P3.

[0112] Furthermore, database 90 associates at least one characteristic hair parameter among average hair size DM, hair density DC, local hair curvature CL, and / or the level of curl present in the hair CF with an operating mode in predefined operating modes A through E. Additionally, operating modes A through E can be associated with the user's customized data (specifically, gender G, age A, and / or head sensitivity SC).

[0113] In a specific example, each pattern A through E is associated with a curling level CF, and the airflow temperature TA and airflow velocity VA are defined according to the curling level CF.

[0114] Alternatively, where the control mode is defined by a continuous range of operating parameters, a deterministic model may be used to determine the operating parameters, in particular airflow velocity VA or airflow temperature TA, based on at least one characteristic parameter of the user's hair and optional custom data.

[0115] Alternatively, an AI-based determination model can be used to determine operating parameters, particularly airflow velocity (VA) or airflow temperature (TA), based on characteristic parameters and / or optional custom data. An AI-based determination module is, for example, a model as defined above.

[0116] For example, the model can be trained by submitting multiple sets of feature parameters and by associating user-appropriate operational parameters with each set of feature parameters.

[0117] The transmission module 70 is configured to transmit the operating parameters of the control mode selected by the control mode determination module 68 to the control device 10 for automatically executing the control mode according to the drying stages P1 to P3.

[0118] Alternatively, as described above, the transmission module 70 is configured to transmit the definition of the control mode and / or the definition of the operating parameters of the control mode to the information acquisition system 14 for presentation to the user and approval by the user before transmission to the hair drying device 10.

[0119] Special references are now available. Figure 2 and Figure 3 This describes a refined method for controlling hair drying equipment.

[0120] First, step 100, representing information acquisition, is performed. Step 100 includes acquiring at least one image of the user's hair using camera 40 and / or acquiring characteristic parameters of the hair through user input. For this purpose, in the example shown at the top of the figure, the user activates an application on mobile device 50 to capture one or more photographic images of their hair, such as a frontal image, a top image, or an image of a strand of hair.

[0121] In one variant, the hair diagnostic device 52 is used to capture one or more images.

[0122] In another variation, such as Figure 2 As shown, a camera 40, directly mounted on the hair drying device 10, is used to take one or more photos.

[0123] Then, the data transmission interface 44 of the acquisition system 14 transmits representative information to the refinement system 16.

[0124] In step 101, the receiving module 64 of the thinning system 16 receives information representing hair. In the case of image 72, the receiving module may optionally perform preprocessing to improve contrast and / or sharpness.

[0125] Then, the determining module 66 performs step 102 of determining at least one characteristic hair parameter.

[0126] As described above, the determination of the feature parameters, or each feature parameter, is performed, for example, by a deterministic model used to process representative information. The deterministic model extracts at least one feature parameter as defined above from at least one image 72 of the user's hair captured by camera 40 and received by receiving module 64. This is advantageously performed by determining a segmentation mask 76 and then calculating the feature parameters (particularly the average hair diameter DM and hair density DC).

[0127] exist Figure 3 In the example, the deterministic model also determines customized data for the user, such as skull sensitivity S, the user's gender G, and age A.

[0128] Similarly, the feature parameter determination module 66 uses the hair bundle image 80 to classify the hair present in the image 80 according to the curl level CF among multiple curl level CFs.

[0129] Alternatively, the model used to determine at least one feature parameter is an artificial intelligence determination module as defined above.

[0130] Therefore, one or more characteristic hair parameters DM, DC, and curl level CF are obtained. Similarly, one or more user-customized data SC, G, and A are obtained.

[0131] Then, step 104 of determining the control mode is performed to determine at least one control mode.

[0132] To this end, the control mode determination module 68 associates a customized control mode with the characteristic parameters of the user's hair determined by the characteristic parameter determination module 66, the control mode being selected from multiple discrete control modes or from a series of possible control modes.

[0133] As described above, each control mode defines multiple operating parameters of the hair drying device 10 based on the characteristic parameters determined by the characteristic parameter determination module 66.

[0134] In one example, the control mode determination module 68 queries the operation mode database 90, which defines operation parameters based on the feature parameters determined by the module 66 for determining feature parameters and optional user-customized data.

[0135] Alternatively, a deterministic or artificial intelligence model is used to determine the operating mode based on the feature parameters determined by module 66 for determining feature parameters and optional user-customized data.

[0136] Then, in step 106, the control mode is transmitted to the hair drying device 10. This transmission results in a first example of implementing the drying stage 110 according to the defined control mode.

[0137] Then, the control unit 32 activates the flow generator 26 to control the air speed VA corresponding to the determined control mode, activates the temperature regulation system 28 to control the temperature TA corresponding to the determined control mode, optionally controls the drying time DS corresponding to the determined control mode, and / or uses the light source 30 to control the intensity IE and the light emission time DE.

[0138] Alternatively, before the hair drying device 10 implements the control mode, a suggested control mode is presented to the user on the control interface 24 and / or in the acquisition system 14 to allow the user to approve the control mode. If the user confirms the control mode, the hair drying device 10 implements the control mode.

[0139] An illustrative example describing an implementation of the method according to the present invention will now be provided.

[0140] According to existing technology, the hair styling process is performed at an airflow temperature (TA) of 160°C, regardless of the curl level (CF) of the user's hair.

[0141] The same scheme was also implemented for nine users at 140°C and 150°C, and the results were compared in terms of performance using a standardized performance panel.

[0142] The results are given in Table 1 below, where performance was measured by the appearance and arrangement of the hair.

[0143] [Table 1]

[0144] As shown in Table 1, control modes can be defined to reduce the airflow temperature according to the curl level CF, for example, to 140°C for curl levels CF1 or 2, to 150°C for curl levels 3 or 4, or even to 150°C for curl level 5 in some cases, thereby achieving performance that is better than, equal to or substantially equal to that obtained at 160°C.

[0145] Subsequently, the control mode is adjusted according to the curl level CF determined for the user using the method according to the invention, which saves power consumption while providing a hairstyle quality that is almost equal to or better than that obtained at 160°C according to the prior art.

[0146] In one variant, instead of acquiring visual representation data of hair in the form of an image of hair taken using camera 40, system 14 suggests to the user a visual representation in the form of a thumbnail that best represents their hair from a selection of predefined thumbnails representing different types of hair 15. These predefined thumbnails are displayed, for example, on the display screen of user interface 42.

[0147] Then, the characteristic hair parameters are determined using the thumbnail selected by the user, for example by retrieving these characteristic hair parameters from a database, and then, as described above, the control mode is determined.

[0148] In another variation, the characteristic hair parameters previously determined using information representing the user's hair are stored in the form of a user profile, for example, hosted in the acquisition system 14, the refinement system 16, the hair drying device 10, or / and an external database.

[0149] Then, the control mode determination module 68 directly retrieves characteristic hair parameters from the user profile to determine the control mode.

Claims

1. A method for controlling a hair refining device (10), said method being implemented by a hair refining control system (16), said method being characterized by the following steps: - The control mode of the hair drying device (10) is determined using at least one characteristic parameter of the user's hair determined using information representing the user's hair.

2. The method according to claim 1, comprising the following steps: - Receive information representing the user's hair; - Determine at least one characteristic parameter of the user's hair based on the information representing the hair.

3. The method according to claim 1 or 2, wherein, Representative information includes visual representation data of the user's hair and / or at least one feature data of the user's hair, entered by the operator on a computer terminal.

4. The method according to claim 3, wherein, The visual representation data of the user's hair includes at least one digital image (72) of the user's hair.

5. The method of claim 4, comprising a preliminary step of acquiring at least one image of the user's hair via a camera (40), wherein, Optionally, the camera (40) is carried by a mobile electronic device (50), a device (52) for diagnosing the user's hair and / or skull, or the hair drying device (10), wherein the mobile electronic device is in particular a mobile phone, tablet computer, or laptop computer.

6. The method according to claim 4 or 5, wherein, At least one characteristic hair parameter is determined by using image analysis of at least one image (72) of the user's hair, advantageously using a deterministic model for determining the at least one characteristic parameter and / or using a model for determining the at least one characteristic parameter by artificial intelligence.

7. The method according to claim 6, wherein, Implementing the deterministic model involves determining the location of the hair root in the hair (74), then creating a hair segmentation mask (76) using the hair root location (74), and performing the calculation of the feature parameters or each feature parameter using the hair segmentation mask (76).

8. The method according to any one of claims 4 to 7, wherein, The determination step includes determining the hair curliness level by using image analysis of at least one image (72) of the user's hair, advantageously using a deterministic model and / or an artificial intelligence determination model.

9. The method according to any one of the preceding claims, wherein, The characteristic parameters determined using the information representing the hair are selected from average hair diameter, local hair curvature, hair density, and hair curl level. The method may optionally include the following steps: determining at least one customized data of the user, particularly the user's gender, age, and / or cranial sensitivity, and using the user's customized data or each customized data to perform the determination of a control mode for the hair drying device.

10. The method according to any one of the preceding claims, wherein, The control mode defines at least one operating parameter of the hair drying device (10), which is selected from the drying airflow temperature, drying airflow velocity, hair illumination intensity of the light source (30) present in the hair drying device, drying time and / or illumination time.

11. The method according to claim 10, wherein, The control mode defines the operating parameters according to the drying stage, which is advantageously determined by pre-drying, hair styling, and / or diffusion.

12. The method according to any one of the preceding claims, wherein, Determining the control mode includes consulting a database (90) that defines multiple control modes that can be applied by the hair drying device (10) based on the determined feature parameters or each feature parameter, and optionally based on any custom data from the user, and / or determining the control mode includes implementing a deterministic or artificial intelligence model that uses the determined feature parameters or each feature parameter and optionally at least one custom data from the user to calculate the control mode.

13. A system (16) for refining the control of a hair drying device (10), comprising: - A module (68) for determining the control mode of the hair drying device using at least one characteristic parameter of the user's hair determined using information representing the user's hair.

14. The system (16) according to claim 13, comprising: - Module (64) for receiving information representing the user's hair. - A module (66) for determining at least one characteristic parameter of the user's hair based on the information representing the hair.

15. Hair drying method, including the following steps: - Implement the hair drying device (10) control refinement method according to any one of claims 1 to 12; - Transmit the determined control mode to the hair drying device (10). - Display the control mode determined by the hair drying device and / or implement the control mode determined by the hair drying device.

16. Hair drying components (12), including: - Hair drying device (10), the hair drying device includes an airflow generator (26), an airflow temperature control system (28) and an optional light source (30), the device also includes a control unit (32) configured to drive the airflow generator (26), the airflow temperature control system (28) and the optional light source (30). - A refinement system (16) for refined control according to claim 14 or 15, the refinement system being configured to be connected to the control unit (32) via a data transmission link, the control unit (32) being configured to receive a control mode determined by the refinement system (16).

17. The component (12) according to claim 16, wherein, The hair styling system (16) is carried by and / or hosted in a computer system by the hair drying device (10), the portable electronic device (50), the hair diagnostic device (52), and the portable electronic device, particularly a mobile phone or tablet computer.

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