Differentiation of human hair by colour and diameter using light microscopy, digital imaging and statistical analysis

Abstract

This research introduces and evaluates a novel method that offers the potential of providing objective criteria to forensic microscopical hair comparisons. The method combines hair diameter with numeric characterisations of red, green, and blue colour content as determined with the use of digital imaging at defined locations of the hair. Thirty hairs were collected from each of twenty participants, all with naturally coloured brown hair. The hairs were examined with an Olympus BX53® polarising light microscope and digital images were viewed with an Olympus DP72® camera under 400× magnification. Using Olympus cellSens Entry software, hair diameter was measured at 1000, 1500 and 2000 μm from the base of the root. The Olympus cellSens Entry software uses a red, green and blue (RGB) colour model to quantitatively define the colour of each pixel on an image based on its composition of these three principal colour components. This software was used to collect numerical characterisations of hair colour at each distance interval. The diameter and colour values for each hair were compared using discriminant analysis (DA) and principal component analysis. Although a large amount of intrapersonal variation was observed, the degree of interpersonal variation was greater and enabled the statistical model to differentiate between the hair samples from each participant. The DA model achieved sample reclassification with an error rate of 7.33%. A validation study was conducted on a subset of hair samples from which 18 of the 20 were correctly assigned to the participant from whom they originated. These results support the potential of this method to provide an objective addition to current microscopical hair comparison practices.

A digital image analysis study on the disintegration kinetics of reticular fibers in the ethylene glycol‐induced rat liver tissue

“…By clicking on the objects to be counted with the mouse's help on the image obtained, the system can detect the objects with the same digital color value on the open image. The system can also automatically determine the shape, diameter, and area of each of the objects that it defines, except for color separation (Mills, Bonetti, Brettell, & Quarino, 2017; Unver Saraydin, Saraydin, & Şahinİnan, 2020).…”

“…After the DIA program was run, in the micrograph, reticular fibers fragments were first marked, and then a specific area was selected for counting (Figure 1). As a result of the counting of this area, the values obtained from the program are stored in an EXCEL file (Mills et al, 2017; Unver Saraydin et al, 2020).…”

Analysis of hair color and texture for forensic examinations

“…When describing pigment density, descriptors used are evenly/consistently distributed, clumped together, uneven, or toward the medulla [15,16]. These descriptors used are not consistent within the research community [7]. Calculating a density ratio would provide an empirical method for analyzing pigment density, and using this value can add support to the overall conclusions made about hair samples.…”

“…The cortex is approximately 90% of the hair and contains many characteristics that can be used for analysis and comparison, such as cortical texture and hair color. Efforts have been made to determine color empirically with some success [6,7]; however, little research has been conducted to analyze hairs' cortical texture.…”

“…Nevertheless, the assessment of color and pigment distribution within the hair is critical. Mills et al showed the potential of using RGB color analysis by taking three measurements of color in the hair's cortex at different locations [7]. Mill's study showed higher between-group variance than within-group variance when collecting discrete measurement of color.…”