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Shape Variability and Classification of Human Hair: A Worldwide Approach
Abstract
Human hair has been commonly classified according to three conventional ethnic human subgroups, that is, African, Asian, and European. Such broad classification hardly accounts for the high complexity of human biological diversity, resulting from both multiple and past or recent mixed origins. The research reported here is intended to develop a more factual and scientific approach based on physical features of human hair. The aim of the study is dual: (1) to define hair types according to specific shape criteria through objective and simple measurements taken on hairs from 1442 subjects from 18 different countries and (2) to define such hair types without referring to human ethnicity. The driving principle is simple: Because hair can be found in many different human subgroups, defining a straight or a curly hair should provide a more objective approach than a debatable ethnicity-based classification. The proposed method is simple to use and requires the measurement of only three easily accessible descriptors of hair shape: curve diameter (CD), curl index (i), and number of waves (w). This method leads to a worldwide coherent classification of hair in eight well-defined categories. The new hair categories, as described, should be more appropriate and more reliable than conventional standards in cosmetic and forensic sciences. Furthermore, the classification can be useful for testing whether hair shape diversity follows the continuous geographic and historical pattern suggested for human genetic variation or presents major discontinuities between some large human subdivisions, as claimed by earlier classical anthropology.
... far been severely limited by available descriptions of hair. Hairstyle names are culturally specific [Corson 2001;Gittens et al. 2002;Sherrow 2006] and their attributes are often described using subjective, inconsistent and ambiguous terms [Lasisi 2021;Mettrie et al. 2007;. Poor categorization or description has therefore led to systems which do not support the full range of human hairstyles. ...
... Walker [2018] assigns values 1-4 to hair with varying degrees of curliness. Mettrie et al. [2007] introduce 8 classes based on statistical analysis of physical measurements of hair strands from subjects of diverse ancestry. These systems describe only physical characteristics of hair strands, and not styling, so are useful but not sufficient for the task of hairstyle prediction. ...
... Summary. Hair type is reasonably well described in literature [Byrd 2023;Mettrie et al. 2007;Walker 2018]. We adopt the four types of Walker [2018], though use named categories rather than numbered ones [Kim et al. 2022]. ...
We present a method for prediction of a person's hairstyle from a single image. Despite growing use cases in user digitization and enrollment for virtual experiences, available methods are limited, particularly in the range of hairstyles they can capture. Human hair is extremely diverse and lacks any universally accepted description or categorization, making this a challenging task. Most current methods rely on parametric models of hair at a strand level. These approaches, while very promising, are not yet able to represent short, frizzy, coily hair and gathered hairstyles. We instead choose a classification approach which can represent the diversity of hairstyles required for a truly robust and inclusive system. Previous classification approaches have been restricted by poorly labeled data that lacks diversity, imposing constraints on the usefulness of any resulting enrollment system. We use only synthetic data to train our models. This allows for explicit control of diversity of hairstyle attributes, hair colors, facial appearance, poses, environments and other parameters. It also produces noise-free ground-truth labels. We introduce a novel hairstyle taxonomy developed in collaboration with a diverse group of domain experts which we use to balance our training data, supervise our model, and directly measure fairness. We annotate our synthetic training data and a real evaluation dataset using this taxonomy and release both to enable comparison of future hairstyle prediction approaches. We employ an architecture based on a pre-trained feature extraction network in order to improve generalization of our method to real data and predict taxonomy attributes as an auxiliary task to improve accuracy. Results show our method to be significantly more robust for challenging hairstyles than recent parametric approaches.
This study aims to formulate and evaluate a herbal hair gel specifically tailored for men. The formulation process involved selecting natural herbal ingredients known for their hair nourishing and styling properties, such as flax seeds, Almond oil, Various formulations were prepared and assessed for their viscosity, spreadability, pH, stability, and sensory attributes. The finalized formulation exhibited desirable characteristics, including optimal viscosity for easy application, good spreadability, suitable pH for scalp health, and pleasant aroma. Additionally, the herbal hair gel was subjected to stability studies to ensure its efficacy over time. Overall, the developed herbal hair gel presents a promising solution for men seeking a natural and effective hair styling product with added benefits for hair health.
Facial recognition is one of the most academically studied and industrially developed areas within computer vision where we readily find associated applications deployed globally. This widespread adoption has uncovered significant performance variation across subjects of different racial profiles leading to focused research attention on racial bias within face recognition spanning both current causation and future potential solutions. In support, this study provides an extensive taxonomic review of research on racial bias within face recognition exploring every aspect and stage of the associated facial processing pipeline. Firstly, we discuss the problem definition of racial bias, starting with race definition, grouping strategies, and the societal implications of using race or race-related groupings. Secondly, we divide the common face recognition processing pipeline into four stages: image acquisition, face localisation, face representation, face verification and identification, and review the relevant corresponding literature associated with each stage. The overall aim is to provide comprehensive coverage of the racial bias problem with respect to each and every stage of the face recognition processing pipeline whilst also highlighting the potential pitfalls and limitations of contemporary mitigation strategies that need to be considered within future research endeavours or commercial applications alike.
Scalp hair is a key feature of humans and its variability has been the subject of a broad range of studies. A small subset of these studies has focused on geometric quantification of human scalp hair fibres, however the use of race‐ and ethnicity‐based classification systems makes it challenging to draw objective conclusions about fibre variability. Furthermore, sample preparation techniques for micro‐imaging studies often alter the original form of hair fibres. This study sought to determine which of the commonly reported descriptors could be resolved using micro‐computed tomography (micro‐CT) for fibres of varying curl. Images obtained from micro‐CT were used to reconstruct three‐dimensional images that were then analysed. The study also explored the capabilities and limitations of micro‐CT as an imaging modality by comparing and cross‐validating findings with those obtained from scanning electron microscopy (SEM) and laser micrometry. The former deals with surface imaging while the latter deals with cross‐sectional measurements. Micro‐CT was found to be highly effective at resolving cross‐sectional ellipsoidal parameters, but performed more poorly than SEM in reconstructing surface level details at a 2 resolution. The technique was, however, able to reveal the presence of the medulla in type VI (high curl) hair fibres. When compared with high curl fibres, greater intra‐fibre variability was observed for the low and medium curl fibres, highlighting the importance more objective classification systems.
Human hair is characterised by variability, determined by genetic and macromolecular factors. Whilst the European hair type has been a focus of extensive research, Afro-textured hair care faces challenges created by insufficient knowledge of its properties. Applications of hair care products that are incompatible with Afro-textured hair frequently have detrimental effects on the scalp. This highlights the need for partnerships to bridge the gap between research and hair care practices and address challenges related to Afro-textured hair. In this review, we performed data mining of the existing literature and in silico network analysis of the biomarkers relevant to Afro-textured hair. The approaches to hair maintenance are highlighted in the context of hair anatomy and growth cycles, organisation of keratins, surface lipids, and chemical bonds. We discuss a range of biomarkers affecting hair fibre’s shape and mechanical strength, with the gene interactive network pointing to the hierarchical organisation of important traits, notably hair shaft diameter, keratinization, and hair follicle patterning, which likely contribute to the increased sensitivity of hair to extrinsic factors. We propose that a better understanding of the genetic traits, molecular structure, and biomechanics of Afro-textured hair is required to initiate more effective hair care solutions that would benefit the wider population.
Transcranial Magnetic Stimulation (TMS) is a technique that is frequently utilized in neuroscience for both therapeutic and research purposes. TMS offers critical medical services like treating major depression and is vital in almost every research facility. Because TMS relies on scalp placement, hair is thought to affect efficacy because it varies the distance to the target site. Further, it is presumed that the hair textures and length that are predominantly seen in minoritized persons might pose significant challenges to collecting high-quality data. Here, we present preliminary data demonstrating that TMS may be influenced by hair, particularly in historically underrepresented minoritized groups. The Sol braiding approach is introduced here as an easy-to-learn, quick-to-implement technique that reduces variability in TMS. Compared across nine participants, it was found that the Sol method significantly increased motor evoked potential (MEP) strength and consistency (p < 0.05). By removing the physical hair barrier that impedes direct coil-to-scalp contact, the Sol approach enhances TMS delivery. The MEP peak amplitude and the MEP area under the curve (AUC) were shown to increase as a result. While preliminary, these data are an important step in addressing diversity in neuroscience. These procedures are explained for non-braiding experts.
A further inquiry on modern human origins, based on common genetic pool surveys of rigorously selected population samples and highly informative immunological polymorphisms, provides new evidence of an Occidental-Oriental population split as the origin of human gene pool divergencies. The most likely ancestral genetic profile is discussed in the context of the debate raised by preliminary DNA restriction fragment length polymorphism studies, which contradict the conclusions drawn from classical blood group analyses.
The alleged relationship between the cross sectional shape of the hair shaft and the form of the hair, eg, curly or straight hair, has been challenged. By serial sections of human hair follicles from ten patients representing the three biological races, the relation between the follicle form and the hair form was studied. Using three-dimensional computer-aided reconstruction it was demonstrated that the follicle form determines the hair form, eg, the Negroid follicle has a helical form, whereas that of the Oriental follicle is completely straight. The caucasoid follicle represent variation between these extremes. However, even a straight caucasoid follicle may produce a hair shaft that has an oval cross section.
Human hair is the subject of a remarkably wide range of scientific investigations. Its chemical and physical properties are of importance to the cosmetics industry, forensic scientists and to biomedical researchers. The fifth edition of this book confirms its position as the definitive monograph on the subject. Previous editions were recognized as “concise and thorough” (Journal of the American Chemical Society), “an invaluable resource” (Canadian Forensic Science Society Journal), and “highly recommended” (Textile Research Journal). Chemical and Physical Behavior of Human Hair is a teaching guide and reference volume for cosmetic chemists and other scientists in the hair products industry, academic researchers studying hair and hair growth, textile scientists and forensic specialists. Features of the Fifth Edition: Recent advances in the classification and characterization of the different proteins and genes in IF and keratin associated proteins in human hair are described. The mechanism and incidence of hair growth and loss and hair density vs. age of males & females are described for Asians, Caucasians and Africans in different scalp regions. Details of hair surface lipids and cuticle membranes provide a better understanding of the surface and organization of the CMC and its involvement in stress strain is presented. Recent evidence demonstrates a more bilateral structure in curly hair and a more concentric arrangement of different cortical proteins in straighter hair. SNPs involved in hair form (curl and coarseness) and pigmentation and genes in alopecia and hair abnormalities are described. The latest biosynthetic scheme for hair pigments and structures for these and the different response of red versus brown-black pigments to photodegradation is described. A new method for curvature on 2,400 persons from different countries and groups is used to assign curvature throughout this book. Additional data for age and effects on diameter, ellipticity, elastic modulus, break stress and other parameters are presented with much larger data sets featuring statistical analyses. Hair conditioning, strength, breakage, split ends, flyaway, shine, combing ease, body, style retention, manageability and feel parameters are defined and described. A new section of different life stages by age groups considering collective and individual changes in hair fiber properties with age and how these affect assembly properties.
We present first the main basic choices which are preliminary to any clustering and then the dynamic clustering method which gives a solution to a family of optimization problems related to those choices. We show then how these choices interfere in pattern recognition using three approaches: the syntactic approach, the logical approach and the numerical approach. For each approach we present a practical application.
