Abstract
Objectives
To review current knowledge concerning the application of colour science on tooth colour and whiteness description, measurement, distribution and its psychological impact.
Data sources
“Scopus” databases were searched electronically with the principal keywords tooth, teeth, colour, white, whiteness. Language was restricted to English and original studies and reviews were included. Conference papers and abstracts were excluded.
Conclusions
The appearance and colour of teeth are a common concern for patients across many populations and are associated with an increased desire for treatments that improve dental aesthetics, including tooth whitening. The application of colour science in dentistry has allowed the precise description of tooth colour and whiteness. Coupled with the advances in instrumental tooth colour measurement, such as spectrophotometers, colorimeters, spectroradiometers and digital imaging systems, these parameters are quantifiable in a reproducible and robust manner. These principles have been applied to the tooth colour distribution in many study populations, indicating, in general, differences in tooth colour for subject age and gender, but not for ethnicity. Psychophysical studies on tooth colour and whiteness via third party assessment of images indicate that whitened teeth lead to judgements that are more positive on personality traits such as social competence and appeal, intellectual ability and relationship satisfaction.
1
Introduction
The aesthetics of teeth and their colour is an important topic for many people. These include dentists who want to select a correct tooth shade and esthetic restorative material to maximise the recreation of natural tooth structure, the dental technician who aims to replicate the form and quality of the tooth appearance, and patients who desire to enhance their smiles . The colour of the teeth is influenced by a combination of their intrinsic colour and the presence of any extrinsic stains that may form on the tooth surface . The intrinsic colour of a tooth is determined by how light is scattered and absorbed at the surface and within the structures of the tooth. The enamel is a translucent scattering material and illuminating light can follow highly irregular light paths through the tooth before it emerges at the surface of incidence and reaches the eye of the observer . Enamel does not fully obscure the colour of the underlying dentine and thus dentine can have a significant role in determining the overall tooth colour . Extrinsic stain and colour is determined by the formation of coloured regions within the acquired pellicle on the surface of enamel and can be influenced by, for example, poor tooth brushing technique; tobacco products; dietary intake of coloured foods; subject age, and exposure to iron salts and chlorhexidine .
Concerns by patients and consumers over the appearance and colour of their teeth appears to be common. For examples, studies have shown that in a UK population 28% of adults are dissatisfied with the appearance of their teeth ; 20.4% of a Spanish population are dissatisfied with their dental appearance , and in a Saudi Arabian population 50% are dissatisfied with their tooth appearance . Dissatisfaction with tooth colour is widely reported in many different adult populations , ranging from 19.6% to 65.9% and in a study with 13 year old adolescents, 18% were dissatisfied with their tooth colour . An oral health related quality of life questionnaire for use among young adults reported that tooth colour was the most important concern . In general, this dissatisfaction with tooth colour has been shown to be associated with increased desire for treatments that improve dental aesthetics including tooth whitening . Indeed, the market for tooth whitening has grown significantly with a wide range of tooth whitening approaches and products available including tooth bleaching formats, toothpastes and oral rinses .
Tooth whitening products generally help to improve the overall whiteness of teeth, either by changing their intrinsic colour or by removing and controlling the formation of extrinsic stains. The former products typically use hydrogen peroxide or carbamide peroxide, formulated into gels and applied to the teeth in various formats including mouth guards or strips or simply directly applied. The peroxide diffuses into the teeth where it decolourises or bleaches the coloured materials found within the tooth to give whiter teeth . An alternative approach to changing the intrinsic colour of teeth has been described from a toothpaste containing blue covarine that has been shown to reduce the yellowness of teeth by deposition of the blue covarine, giving an overall perception of improved tooth whiteness . Extrinsic stains can be removed completely by the abrasive and polishing action of a dental prophylaxis and controlled to some extent by the regular use of an effective toothpaste . Whitening toothpastes are formulations with enhanced physical and chemical cleaning abilities and may contain ingredients such as optimized abrasive systems, low level peroxides, phosphate salts and enzymes which are designed to help remove and prevent extrinsic stains .
With the continued interest in colour research in dentistry and in tooth whitening , the aim of the current review is to introduce key aspects of colour science and whiteness pertinent to teeth, describe approaches to measuring tooth colour, summarise the distribution of tooth colours in permanent and deciduous dentition, and overview psychophysical studies conducted to evaluate the impact of tooth colour and whiteness.
2
Colour and whiteness
Colour is much more than something physical, it is a sensation . The three key components of colour are sources of light, objects illuminated by them and the vision system . A light source can be characterised by its energy distribution at different wavelengths in the spectrum. When light falls on an object, depending on the physical properties of the object, the light is modified by reflection, scattering, absorption and transmission. The colour of an object is strongly dependent on its spectral reflectance, that is, the amount of the incident light that is reflected from the surface for different wavelengths. When light reaches the eyes, its energy is absorbed by the photoreceptors in the retina and converted into a signal that is interpreted by the brain.
To quantify colour, the Commission Internationale de l’Eclairage (CIE) defined a range of standard illuminants, such as A, D F, which are the representations of incandescent light, daylight and fluorescent lamps respectively. In the series of D illuminants, D65 is intended to represent average midday light in Western/Northern Europe and has a correlated colour temperature of approximately 6500 K. Since the eyes respond to light continuously over the visible spectrum (360 nm–780 nm), CIE tristimulus values XYZ are defined by integrals of the spectrum of an illuminant, spectral data of an object and the human colour matching functions.
To have a better interpretation of colour perception and a uniform colour space, the CIELAB colour space was introduced in 1976. This defines colours in three dimensions associated with three perceptual attributes: lightness, hue and chroma .
Where X n , Y n , Z n are the tristimulus values of the reference white under the chosen illuminant. The L* is known as the lightness and is ranged from 0 (black) to 100 (white). The other two coordinates a* and b* represent red-green and yellow-blue components respectively. Hue (h ab ) and chroma (C* ab ) are defined by converting the rectangular a*, b* axes into polar coordinates:
In many cases, the measure of the differences between colours may often be more useful than a measure of the absolute value of colour. Colour difference ΔE* ab is defined by the Euclidean distance between the coordinates of two stimuli in the CIELAB colour space.
It is often stated that the just-noticeable-difference (JND) for ΔE* ab is equal to 1.0 unit . However, in another study the JND was found to be 2.3 units . The CIELAB colour difference has been widely used in dentistry, despite the fact that its predicted colour differences are not perfectly perceptually uniform throughout the colour space . Other formulae have been developed to address perceptual non-uniformities by adding weights and corrections to the colour difference equation, such as CMC ΔE CMC , CIEDE94 ΔE * 94 and CIEDE2000 ΔE* 00 . To compare the performance between different colour difference formulae for dental applications, one study found that in the natural tooth colour space, the results obtained with the CIELAB formula were between 1.15 and 2.09 times higher than those obtained with the CIEDE2000 formula . It was found that CIEDE2000 formula provided a better fit than CIELAB formula in the evaluation of colour difference thresholds of dental ceramics , and another study suggested that the CIEDE2000 (2:1:1) colour difference formula showed the best estimate to the visual perception .
White is the colour of purity, freshness, and cleanness. It is considered as the combination of all the colours of the visible light spectrum, which is sometimes described as an achromatic colour, like black. A white surface, in physical terms, is one that reflects strongly (more than 50%) throughout the visible spectrum . A higher and more uniform spectral reflectance results in a whiter colour. For a three-dimensional colour space, three colour coordinates are necessary for a complete identification of any white. However, a one-dimensional colour index can be more efficient for identifying the properties of white materials. Since colours perceived as white are in a three-dimensional colour space, most observers are able to arrange white samples in a one-dimensional order according to whiteness .
The best way to classify the degree of whiteness is in relation to other white surfaces. In principle, the degree of whiteness is defined by the degree of departure of the colour from a ‘perfect’ white. The important argument is about the description of perfect whiteness and which directions of departure from it (towards blue, yellow or red etc.) should be favoured or avoided . In general, actual white colours depart from the perfect white in two directions: toward yellow and toward grey. In the literature, numerous whiteness indices have been proposed for various industrial needs, but those only relevant to dental applications are considered here. One of them is the CIE whiteness index (WIC), which was proposed by CIE in 1986 for the neutral hue preference .
Where x, y are chromaticity coordinates defined as the ratio of individual tristimulus value and the sum of all three tristimulus values. x n and y n are chromaticity coordinates of the perfect white for the chosen standard observer (2° or 10°), and always under illuminant D65. The WIC formula gives relative, but not absolute, evaluations of whiteness. The higher the value of WIC rating indicates the higher the whiteness of the object. A JND in whiteness to an experienced visual assessor was found to be about three WIC units .
Another whiteness index is based on the Euclidean distance of the test colour from the perfect white diffuser in the CIELAB colour space .
The use of whiteness indices to quantify tooth whiteness is gradually growing in recent years. The WIC formula has been used in some early dental studies to assess whiteness of porcelain teeth samples , extracted human teeth in vitro and VITA Shade Guide tabs . The W* formula has been used in a few tooth bleaching studies to track whiteness changes after treatments . It was suggested that for a whiteness index to be valid, it must be used on the type of materials for which it was intended . It has been found that tooth colours appear to be outside the valid colour range for using whiteness formulae like the WIC . A modified version of the CIE whiteness index (WIO) was proposed specifically for quantifying tooth whiteness based on visual perception of the Vita 3D Shade Guide :
It was found that the WIO index outperformed other whiteness and yellowness indices for tooth whiteness assessment, and was as reliable as the average human observer . In a study of colorimetric analysis of shade guides, it was demonstrated that the WIO gave the best fit with the instrumental colour measurements . This index has been used in a number of tooth whitening studies in vitro and in vivo , including tooth bleaching studies with hydrogen peroxide products and whitening studies with toothpastes containing blue optical whitening technologies .
A new CIELAB-based whiteness index (WI D ) has recently been proposed based on correlations with visual perception of shade guide tabs and dental materials .
The proposed WI D showed an improved correlation to the associated visual perception data than all the other CIELAB and whiteness/yellowness indices tested in the study under laboratory and clinical conditions, only WIO was comparable to WI D .
2
Colour and whiteness
Colour is much more than something physical, it is a sensation . The three key components of colour are sources of light, objects illuminated by them and the vision system . A light source can be characterised by its energy distribution at different wavelengths in the spectrum. When light falls on an object, depending on the physical properties of the object, the light is modified by reflection, scattering, absorption and transmission. The colour of an object is strongly dependent on its spectral reflectance, that is, the amount of the incident light that is reflected from the surface for different wavelengths. When light reaches the eyes, its energy is absorbed by the photoreceptors in the retina and converted into a signal that is interpreted by the brain.
To quantify colour, the Commission Internationale de l’Eclairage (CIE) defined a range of standard illuminants, such as A, D F, which are the representations of incandescent light, daylight and fluorescent lamps respectively. In the series of D illuminants, D65 is intended to represent average midday light in Western/Northern Europe and has a correlated colour temperature of approximately 6500 K. Since the eyes respond to light continuously over the visible spectrum (360 nm–780 nm), CIE tristimulus values XYZ are defined by integrals of the spectrum of an illuminant, spectral data of an object and the human colour matching functions.
To have a better interpretation of colour perception and a uniform colour space, the CIELAB colour space was introduced in 1976. This defines colours in three dimensions associated with three perceptual attributes: lightness, hue and chroma .
Where X n , Y n , Z n are the tristimulus values of the reference white under the chosen illuminant. The L* is known as the lightness and is ranged from 0 (black) to 100 (white). The other two coordinates a* and b* represent red-green and yellow-blue components respectively. Hue (h ab ) and chroma (C* ab ) are defined by converting the rectangular a*, b* axes into polar coordinates:
In many cases, the measure of the differences between colours may often be more useful than a measure of the absolute value of colour. Colour difference ΔE* ab is defined by the Euclidean distance between the coordinates of two stimuli in the CIELAB colour space.
It is often stated that the just-noticeable-difference (JND) for ΔE* ab is equal to 1.0 unit . However, in another study the JND was found to be 2.3 units . The CIELAB colour difference has been widely used in dentistry, despite the fact that its predicted colour differences are not perfectly perceptually uniform throughout the colour space . Other formulae have been developed to address perceptual non-uniformities by adding weights and corrections to the colour difference equation, such as CMC ΔE CMC , CIEDE94 ΔE * 94 and CIEDE2000 ΔE* 00 . To compare the performance between different colour difference formulae for dental applications, one study found that in the natural tooth colour space, the results obtained with the CIELAB formula were between 1.15 and 2.09 times higher than those obtained with the CIEDE2000 formula . It was found that CIEDE2000 formula provided a better fit than CIELAB formula in the evaluation of colour difference thresholds of dental ceramics , and another study suggested that the CIEDE2000 (2:1:1) colour difference formula showed the best estimate to the visual perception .
White is the colour of purity, freshness, and cleanness. It is considered as the combination of all the colours of the visible light spectrum, which is sometimes described as an achromatic colour, like black. A white surface, in physical terms, is one that reflects strongly (more than 50%) throughout the visible spectrum . A higher and more uniform spectral reflectance results in a whiter colour. For a three-dimensional colour space, three colour coordinates are necessary for a complete identification of any white. However, a one-dimensional colour index can be more efficient for identifying the properties of white materials. Since colours perceived as white are in a three-dimensional colour space, most observers are able to arrange white samples in a one-dimensional order according to whiteness .
The best way to classify the degree of whiteness is in relation to other white surfaces. In principle, the degree of whiteness is defined by the degree of departure of the colour from a ‘perfect’ white. The important argument is about the description of perfect whiteness and which directions of departure from it (towards blue, yellow or red etc.) should be favoured or avoided . In general, actual white colours depart from the perfect white in two directions: toward yellow and toward grey. In the literature, numerous whiteness indices have been proposed for various industrial needs, but those only relevant to dental applications are considered here. One of them is the CIE whiteness index (WIC), which was proposed by CIE in 1986 for the neutral hue preference .
Where x, y are chromaticity coordinates defined as the ratio of individual tristimulus value and the sum of all three tristimulus values. x n and y n are chromaticity coordinates of the perfect white for the chosen standard observer (2° or 10°), and always under illuminant D65. The WIC formula gives relative, but not absolute, evaluations of whiteness. The higher the value of WIC rating indicates the higher the whiteness of the object. A JND in whiteness to an experienced visual assessor was found to be about three WIC units .
Another whiteness index is based on the Euclidean distance of the test colour from the perfect white diffuser in the CIELAB colour space .
The use of whiteness indices to quantify tooth whiteness is gradually growing in recent years. The WIC formula has been used in some early dental studies to assess whiteness of porcelain teeth samples , extracted human teeth in vitro and VITA Shade Guide tabs . The W* formula has been used in a few tooth bleaching studies to track whiteness changes after treatments . It was suggested that for a whiteness index to be valid, it must be used on the type of materials for which it was intended . It has been found that tooth colours appear to be outside the valid colour range for using whiteness formulae like the WIC . A modified version of the CIE whiteness index (WIO) was proposed specifically for quantifying tooth whiteness based on visual perception of the Vita 3D Shade Guide :
It was found that the WIO index outperformed other whiteness and yellowness indices for tooth whiteness assessment, and was as reliable as the average human observer . In a study of colorimetric analysis of shade guides, it was demonstrated that the WIO gave the best fit with the instrumental colour measurements . This index has been used in a number of tooth whitening studies in vitro and in vivo , including tooth bleaching studies with hydrogen peroxide products and whitening studies with toothpastes containing blue optical whitening technologies .
A new CIELAB-based whiteness index (WI D ) has recently been proposed based on correlations with visual perception of shade guide tabs and dental materials .
The proposed WI D showed an improved correlation to the associated visual perception data than all the other CIELAB and whiteness/yellowness indices tested in the study under laboratory and clinical conditions, only WIO was comparable to WI D .
3
Measurement of tooth colour
The measurement of tooth colour and restorative dental materials has many important applications within clinical practice and dental research . In clinical practice, for example when preparing and fitting a tooth crown, the dentist needs to measure the colour of a tooth accurately, then communicate the tooth colour to a laboratory technician who will select the appropriate coloured dental materials to fabricate the crown, and together they will produce a crown that is an acceptable colour match to the existing dentition. Colour measuring instruments and systems are increasingly used in dental research such as for the evaluation of visual colour thresholds, comparison between visual and instrumental assessments, colour compatibility and stability, tooth whitening studies and colour interactions of human teeth and dental materials . There are many methods to measure the colour of teeth and range from visual comparisons using shade guides to instrumental measurements using spectrophotometers, colorimeters, spectroradiometers and digital image analysis techniques.
3.1
Shade guides
The most widely used method of clinically assessing tooth colour is by visual shade matching with a commercial shade guide . It is generally considered an inconsistent and a subjective method, since factors such as lighting, age, sex, eye fatigue and colour vision deficiencies can affect visual shade selection . However, it is a quick and cost-effective method , the discriminatory ability of individuals can be improved with training and experience and has been used successfully in measuring longitudinal changes in tooth colour in a number of tooth whitening studies .
Tooth shade guides come in many types and forms, but essentially the basic design involves a series of standard tooth colours that can be arranged according to chroma and/or value. One of the most widely used shade guides is the VITA Classical shade guide (VITA Zahnfabrik, Bad Sackingen, Germany) which is often arranged according to decreasing value, from the lightest to the darkest tab for shade matching . In general, it has some reported weaknesses including the range of shades are inadequate and the colour differences between shade tabs are not uniform and systematic . The 3D Master Toothguide (VITA Zahnfabrik, Bad Sackingen, Germany) was introduced in 1998 and designed to have a broader and more uniform colour range, better colour distribution, and improved repeatability of measuring tooth shade as compared to other shade guides . The colour of the shade tabs were measured using a spectrophotometer and almost all (99.08%) of the colour differences between the tabs were perceptible ones , in agreement with Lee et al. who reported that no shade tab pairs had colour difference values lower than the visual perceptible limit. More recently, a VITA Bleachedguide 3D-Master was designed and developed to include additional lighter shade tabs and value ordered to increase its applicability for monitoring tooth bleaching .
3.2
Spectrophotometers
Spectrophotometers measure the amount of light energy reflected from an object at 1–25 nm intervals along the visible spectrum and can convert the measured spectral reflectance to colour coordinates (CIEXYZ, CIELAB or CIELCH) and various tooth shade values. This can be a single shade or map subtle differences in shade across a tooth surface. In a systematic review of visual and instrumental shade matching ability, most of the studies reported more precise outcomes when using a spectrophotometer . For example, Paul et al. showed that visual shade selection matched only 26.6% whereas spectrophotometric shade selection matched 83.3%. Similarly, Bahannan in a study to compare the shade matching quality among dental students, the correct shade was selected only 36.3% by visual methods and 80.4% using a spectrophotometer.
There are various commercial spectrophotometers available for clinical applications, having different designs, software and output of data . A number of reported studies compare the repeatability and accuracy of various instruments in vitro and in vivo . For example, the repeatability of the SpectroShade (MHT Optic Research AG, Switzerland) and VITA Easyshade (VITA Zahnfabrik, Bad Sackingen, Germany) spectrophotometers for measuring shade tabs in vitro has been shown to be 96.9% and 96.4% respectively, and their accuracy as 80.2% and 92.6% respectively . In a clinical study, the Spectroshade was the most repeatable device (82.7%) in recording tooth shades compared to the VITA Easyshade and a colorimeter . In another clinical study measuring maxillary and mandibular teeth, both devices showed excellent repeatability with no significant differences between devices in CIELAB values . Therefore, various spectrophotometers have found broad application and success in dental research areas such as measuring the colour stability of ceramic crowns in vivo , developmental defects of enamel , tooth colour prevalence and longitudinal tooth whitening studies . However, care must be taken when using these devices, since studies have shown that the degree of matching repeatability can be influenced by the ambient illuminant and by the background that may be applied to teeth . Fogging of the optical lens can occur during in vivo measurement, which leads to inaccurate readings . As these devices are contact-measuring instruments, minor patient discomfort may occur since the head of some devices must be held stable against the gingival tissues .
3.3
Colorimeters
Colorimeters measure tristimulus values (CIE XYZ) by filtering the reflected light from an object into red, green and blue areas of the visible spectrum and typically convert these to CIELAB values. Their key optical elements include a light source and a detector that consists of three filters intended to have a close match to the CIE colour matching functions or to a linear combination of them. In general, colorimeters have been shown to be reliable, have good repeatability, and are accurate for colour difference measurements . For example, the repeatability of a colorimeter for measuring shade tabs in vitro has been shown to be 99.0% with an accuracy of 92.6% . The measurement of the colour of maxillary incisors in vivo with a colorimeter also showed excellent repeatability .
Some disadvantages of colorimeters have been described, including: colorimeters are designed to measure flat surfaces, teeth are often not flat and can have surface anomalies; teeth are translucent which can lead to light loss at the edge of the tooth sample being measured giving incorrect colour values, and inter-instrument agreement is relatively poor .
The strengths of instrumental colorimetry include its ease of use and its sensitivity in detecting and measuring small colour differences between samples of similar colour . It is therefore ideal for many aspects of colour research in dentistry. Indeed, colorimeters have found widespread use in dental research for measuring the colour of teeth, restorative materials and soft tissues . The change in tooth colour following tooth whitening treatments has been described in both in vitro and in vivo studies . For longitudinal tooth whitening clinical studies, the use of custom-made mouthguards with apertures aligned to the anterior teeth are frequently used to ensure accurate realignment of the colorimeter measuring head onto the tooth surface before and after treatment .
3.4
Spectroradiometers
Spectroradiometers measure radiometric quantities (irradiance, radiance) emitted or reflected from objects along the visible spectrum. Their colorimetric values are expressed by luminance and illuminance for radiance and irradiance units respectively and can be converted into colour coordinates (CIEXYZ, CIELAB and CIECLH) . The main differences between spectrophotometers and spectroradiometers are that the latter ones do not have built-in light sources and they are non-contact measurement devices. Conventional contact measurements are subject to the edge-loss effect for translucent materials, where the illuminant light scatters inside of the material and travels to the edges, without reflecting back to the surface . The edge-loss effect for a wide range of translucent dental materials can be avoided by using non-contact colour measurement systems, such as spectroradiometers, which use external light sources and do not need to attach apertures onto the material surface .
Using spectroradiometers to measure tooth colour has been applied in dental studies in vitro and in vivo . Spectroradiometers SpectraScan PR series (PhotoResearch, USA) were used to measure colours and white spot lesions of extracted human teeth in viewing cabinets with illuminant D65 at a 45/0 viewing geometry . Tooth colours measured by a SpectraScan PR650 spectroradiometer and a hemisphere diffuse lighting were used to monitor progression of erosive enamel loss in vitro . A spectroradiometer Minolta CS1000 (Konica Minolta, Inc., Japan) was used to measure colours of shade guide tabs in a study for developing a tooth whiteness index, as the device measured colours in a way that matched the settings of visual assessments . For in vivo studies, spectroradiometers are usually equipped with custom-built light sources, such as Xenon light sources with fiber optic cables , four 100-W bulb dedolights with filters , to give a 45/0 viewing geometry for measuring tooth colour of subjects. As the aperture of the device can be adjusted to be relatively small (1–2.5 mm), measurements have been made at different regions of a single incisor in vivo .
The advantages of measuring tooth colour using spectroradiometers are mainly associated with their non-contact measurement approach. Some studies have showed that spectroradiometry-based colour measurement are closer to human colour perception of dental materials compared to other contact-measurement devices . However, there are fewer published studies using spectroradiometers than using other colour measurement devices for tooth colour measurements. The reasons for this could be their relatively high cost and the needs of setting careful lighting/viewing conditions for measurement.
3.5
Digital cameras and imaging systems
Another non-contact colour measurement method is using digital imaging. Digital cameras record the scene onto a light-sensing material and output images represented by red, green and blue (RGB) values for each pixel . There is an increased interest in using digital imaging for colour matching and communications in dentistry . The advantages of this approach include non-contact measurement; ability to assess the whole tooth surface; systematic error due to translucency and surface curvature can be minimised ; provides a permanent database of images that can be analysed and re-investigated at a later date; quick and simple training and operation, and not requiring a clinician .
A typical dental imaging system for colour measurement consists of a digital camera and a light source. Commercial single-lens reflex (SLR) cameras when combined with the appropriate calibration protocols showed potential for use in dental colour measurement . Industrial cameras (e.g. 3CCD cameras) have also been used for in vitro and in vivo studies and provides live videos in addition to still images . Since it uses a non-contact measuring approach, the type of light source used is important as well as the viewing angle . Common light sources used are dual daylight D65 or D55 lamps, four halogen lamps with UV fluorescent tubes and ring light sources . Polariser filters are often used to exclude the specular reflection from the tooth surface for more accurate colour measurement . For post image analysis, as camera RGB values are device-dependent which are related to their sensor spectral sensitivity, the RGB values are converted into device-independent colour systems (CIE XYZ, CIE LAB etc.) through mathematical modelling . Some studies have used the built-in functions in Adobe Photoshop (Adobe Systems Inc., USA) to extract the RGB values and convert them into L*a*b* or L*c*h* values . The standard RGB colour model with fixed coefficients endorsed by colour and imaging manufactures was used to convert RGB into L*a*b* in other studies . More accurate mathematical models based on least squares polynomial regression was recommended for colour measurement using digital cameras , which has been applied in in vivo tooth colour measurement studies . In addition, regression models and shade selection programs have been developed that allow tooth colour information to be translated to accurate shade tab values for colour matching purposes in dentistry .
From studies comparing the performance between digital imaging and contact measurement methods, digital imaging was recommended as an alternative to colorimeters in dentistry when the proper object-camera distance, camera settings and suitable illumination are used . In a study with spectrophotometric and digital image measurement methods, it was found that both methods gave a comparable and an objective evaluation of bleaching efficiency . In another study, it was found that digital camera imaging was reliable in tooth colour quantification, whereas spectrophotometry (colorimetry) gave relatively inaccurate absolute values for tooth colours but gave the same ranking order as the digital imaging method . A meta-analysis of tooth whitening studies in a 4-year period confirmed the usage and reliability of digital image analysis for long-term tooth whitening studies . Disadvantages of digital imaging are rarely reported in the literature. Metamerism could be a potential problem when different tooth colours under different lighting conditions look the same due to the metamerism phenomenon . Therefore, the lighting and viewing conditions for digital imaging is critical .
Digital imaging may be used to measure other appearance attributes beyond intrinsic colour such as extrinsic stains and shade matching. With quantitative light-induced fluorescence (QLF), digital imaging was used to quantify staining and stain removal on teeth . Shade matching assisted by digital images and computer software was significantly more accurate than by conventional visual methods in a study with shade guide tabs in a phantom head . The shade matching accuracy for digital imaging was found to be comparable to that of colorimetric or spectrophotometric analysis of shade guide tabs .
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