A Comparative Evaluation of Three Skin Color Detection Approaches

Skin segmentation is a challenging task due to several influences such as unknown lighting conditions, skin colored background, and camera limitations. A lot of skin segmentation approaches were proposed in the past including adaptive (in the sense of updating the skin color online) and non-adaptive approaches. In this paper, we compare three skin segmentation approaches that are promising to work well for hand tracking, which is our main motivation for this work. Hand tracking can widely be used in VR/AR e.g. navigation and object manipulation. The first skin segmentation approach is a well-known non-adaptive approach. It is based on a simple, pre-computed skin color distribution. Methods two and three adaptively estimate the skin color in each frame utilizing clustering algorithms. The second approach uses a hierarchical clustering for a simultaneous image and color space segmentation, while the third approach is a pure color space clustering, but with a more sophisticated clustering approach. For evaluation, we compared the segmentation results of the approaches against a ground truth dataset. To obtain the ground truth dataset, we labeled about 500 images captured under various conditions.

Color Segmentation using LVQ-Learning Vector Quantization

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Color detection and segmentation for road and traffic signs

This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high robustness. This project is part of the research taking place in Dalarna University / Sweden in the field of the ITS.

The Thermal Effects of Therapeutic Lasers with 810 and 904 nm Wavelengths on Human Skin

Objective: To investigate the effect of therapeutic infrared class 3B laser irradiation on skin temperature in healthy participants of differing skin color, age, and gender. Background: Little is known about the potential thermal effects of Low Level Laser Therapy (LLLT) irradiation on human skin. Methods: Skin temperature was measured in 40 healthy volunteers with a thermographic camera at laser irradiated and control (non-irradiated) areas on the skin. Six irradiation doses (2-12 J) were delivered from a 200mW, 810nm laser and a 60mW, 904nm laser, respectively. Results: Thermal effects of therapeutic LLLT using doses recommended in the World Association for Laser Therapy (WALT) guidelines were insignificant; below 1.5 degrees C in light, medium, and dark skin. When higher irradiation doses were used, the 60mW, 904 nm laser produced significantly (p < 0.01) higher temperatures in dark skin (5.7, SD +/- 1.8 degrees C at 12 J) than in light skin, although no participants requested termination of LLLT. However, irradiation with a 200mW, 810nm laser induced three to six times more heat in dark skin than in the other skin color groups. Eight of 13 participants with dark skin asked for LLLT to be stopped because of uncomfortable heating. The maximal increase in skin temperature was 22.3 degrees C. Conclusions: The thermal effects of LLLT at doses recommended by WALT-guidelines for musculoskeletal and inflammatory conditions are negligible (< 1.5 degrees C) in light, medium, and dark skin. However, higher LLLT doses delivered with a strong 3B laser (200mW) are capable of increasing skin temperature significantly and these photothermal effects may exceed the thermal pain threshold for humans with dark skin color.

Skin cancer in Taubate (SP) - Brazil, from 2001 to 2005: a prevalence study

BACKGROUND - Cancer represents the third principal cause of death in Brazil. Skin is the most frequent location and about 50% of caucasian patients older than sixty years will develop some type of cutaneous cancer OBJECTIVE - To describe the profile of the individuals with skin cancer assisted at the University Hospital of Taubate in the period between 2001 and 2005. METHODS - A hospital-based cross-sectional study involving individuals assisted at the Dermatology Department at the University Hospital of Taubate in the period between January 2001 to December 2005 was performed. Study variables were gender, age, skin color, location and clinical type of the tumor basal cell carcinoma, squamous cell carcinoma, combined and melanoma. Statistical analyses were performed using qui-square, Student`s t-test and ANOVA. RESULTS - A total of 639 individuals were included in the study. Prevalence was 50 cases/100.000 inhabitants. The most prevalent age group was that of individuals older than sixty years of age, gender distribution was higher among females than males (57.2% / 42.8%) and the proportion of white to non-white was of 4:1. CONCLUSION - This study fills a gap that was due to the inexistence of studies in the region and also to the small number of studies in the state of Sao Paulo, and its results are in accordance with, those in the literature.

The role of melanocortin-1 receptor polymorphism in skin cancer risk phenotypes

We have examined melanocortin-1 receptor (MC1R) variant allele frequencies in the general population and in a collection of adolescent dizygotic and monozygotic twins to determine statistical associations of pigmentation phenotypes with increased skin cancer risk. This included hair and skin color, freckling, mole count and sun exposed skin reflectance. Nine variants were studied and designated as either strong R (OR = 63; 95% CI 32-140) or weak r (OR = 5; 95% CI 3-11) red hair alleles. Penetrance of each MC1R variant allele was consistent with an allelic model where effects were multiplicative for red hair but additive for skin reflectance. To assess the interaction of the brown eye color gene BEY2/OCA2 on the phenotypic effects of variant MC1R alleles we imputed OCA2 genotype in the twin collection. A modifying effect of OCA2 on MC1R variant alleles was seen on constitutive skin color, freckling and mole count. In order to study the individual effects of these variants on pigmentation phenotype we have established a series of human primary melanocyte strains genotyped for the MC1R receptor. These include strains which are MC1R wild-type consensus, variant heterozygotes, and homozygotes for strong R alleles Arg151Cys and Arg160Trp. Ultrastructural analysis demonstrated that only consensus strains contained stage III and IV melanosomes in their terminal dendrites whereas Arg151Cys and Arg160Trp homozygous strains contained only immature stage I and II melanosomes. Such genetic association studies combined with the functional analysis of MC1R variant alleles in melanocytic cells should provide a link in understanding the association between pigmentary phototypes and skin cancer risk.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Color stability after accelerated aging of two silicones, pigmented or not, for use in facial prostheses

One of the greatest challenges faced by buccomaxillofacial prosthetists is to reproduce the patient's exact skin color and provide adequate esthetics. To reach this objective, professionals must use materials with easy characterization and that maintain color over long periods of time. The objective of this study was, thus, to evaluate the color stability of two types of silicones, Silastic 732 and Silastic MDX4-4210. Twenty-four test specimens were made from each type of silicone and were divided into a colorless group and groups intrinsically pigmented with ceramics, cosmetics or iron oxide. The specimens were submitted to an accelerated system of aging for non-metallic materials. Readings were carried out initially and after periods corresponding to 163, 351, 692 and 1,000 hours of aging, using a reflection spectrophotometer analysis, and color alterations were calculated by the CIE L*a*b* system. The data were submitted to variance analysis and Tukey's test at a 5% level of probability. The results demonstrated that, irrespective of the period of time analyzed, all the materials underwent some type of chromatic alteration (ΔE > 0). The test specimens made with Silastic 732 and MDX4-4210, without pigmentation, presented the lowest color alteration values after 1,000 hours of aging. Of the pigments, ceramic presented the lowest color alteration values and cosmetic powder presented the highest values. Thus, it may be concluded that the materials without the incorporation of pigments presented similar color alteration values, and did not differ statistically. The cosmetic powder used in this study was the pigment that most altered the color of the test specimens. © 2009 Sociedade Brasileira de Pesquisa Odontológica.

Anuran skin and basking behavior: the case of the treefrog Bokermannohyla alvarengai (Bokermann, 1956)

We investigated the morphology of the skin and the biochemistry of the lipids in the skin secretion of Bokermannohyla alvarengai, a montane treefrog that is known to bask regularly, motionless in full sunlight for extended periods of time. Our primary goal was to identify structural and biochemical modifications that might assist this frog species to accommodate the conflicting demands for heat exchange and water balance while basking. The modulation of heat exchange in basking B. alvarengai involves changes in skin coloration. We found that this response was supported by a prominent monolayer of large iridophores, whose light reflectance property is adjusted by the response of intervening melanophores. Mucosubstances and lipid compounds, mainly consisted of saturated fatty acids and presumably secreted from granular glands, were detected on the skin of B. alvarengai. These compounds formed an extra-epidermal layer over the animal's dorsal surface that might assist in the prevention of excessive water loss through evaporation. Additionally, we found well-developed skin folds at the ventral region of the frogs that lead to an increment of surface area. This feature combined with the extensive hypervascularization, also noticed for the skin of B. alvarengai, may play an important role in water reabsorption. The suite of structural and biochemical modifications identified for the integument of B. alvarengai seems to conjugate aspects relevant to both, heat exchange and water balance, allowing for this species to explore basking as an efficient thermoregulatory strategy. J. Morphol. 276:1172-1182, 2015. © 2015 Wiley Periodicals, Inc.

Mercado de trabajo y condicionamiento por color de piel en grandes centros urbanos de la Argentina

La discriminación por aspecto físico, y más en particular, el trato diferenciado hacia personas cuyos rasgos remiten a un origen entendido como indígena o no-europeo, constituye un problema escasamente tratado en los estudios de la desigualdad en la Argentina. Esta carencia, sumada a la falta de una articulación en las explicaciones de estos mecanismos relacionados con las desigualdades derivadas de las condiciones de clase, con frecuencia opacan el estudio del fenómeno profundizando sus efectos de invisibilidad. En este sentido, se mantienen ocultas las dificultades que afrontan quienes poseen estos rasgos para sobreponerse a prejuicios que reeditan cotidianamente principios racistas que asocian los rasgos nativos con la delincuencia, la falta de capacidades y saberes y, en términos generales, con la inferioridad socialmente entendida. En este artículo se investiga la incidencia del trato desigual basado en el aspecto físico -en particular, en el color de piel- sobre los logros laborales en una muestra de 2.500 personas de grandes centros urbanos de la Argentina en el año 2007. La discriminación por rasgos físicos, como efecto de la persistencia de principios operativos basados en la racialización de las interacciones sociales, pone de manifiesto la continuidad de principios jerárquicos, simbólicos y materiales que obstruyen la posibilidad de una mayor igualdad en el desarrollo cotidiano de las condiciones de vida de las personas