Skin Color Tone Research Articles

Enhanced Skin Colour Classifier Using RGB Ratio Model

Skin colour detection is frequently been used for searching people, face detection, pornographic filtering and hand tracking. The presence of skin or non-skin in digital image can be determined by manipulating pixels colour or pixels texture. The main problem in skin colour detection is to represent the skin colour distribution model that is invariant or least sensitive to changes in illumination condition. Another problem comes from the fact that many objects in the real world may possess almost similar skin-tone colour such as wood, leather, skin-coloured clothing, hair and sand. Moreover, skin colour is different between races and can be different from a person to another, even with people of the same ethnicity. Finally, skin colour will appear a little different when different types of camera are used to capture the object or scene. The objective in this study is to develop a skin colour classifier based on pixel-based using RGB ratio model. The RGB ratio model is a newly proposed method that belongs under the category of an explicitly defined skin region model. This skin classifier was tested with SIdb dataset and two benchmark datasets; UChile and TDSD datasets to measure classifier performance. The performance of skin classifier was measured based on true positive (TF) and false positive (FP) indicator. This newly proposed model was compared with Kovac, Saleh and Swift models. The experimental results showed that the RGB ratio model outperformed all the other models in term of detection rate. The RGB ratio model is able to reduce FP detection that caused by reddish objects colour as well as be able to detect darkened skin and skin covered by shadow.

Enhanced Skin Colour Classifier Using RGB Ratio Model

Skin colour detection is frequently been used for searching people, face detection, pornographic filtering and hand tracking. The presence of skin or non-skin in digital image can be determined by manipulating pixels’ colour and/or pixels’ texture. The main problem in skin colour detection is to represent the skin colour distribution model that is invariant or least sensitive to changes in illumination condition. Another problem comes from the fact that many objects in the real world may possess almost similar skin-tone colour such as wood, leather, skin-coloured clothing, hair and sand. Moreover, skin colour is different between races and can be different from a person to another, even with people of the same ethnicity. Finally, skin colour will appear a little different when different types of camera are used to capture the object or scene. The objective in this study is to develop a skin colour classifier based on pixel-based using RGB ratio model. The RGB ratio model is a newly proposed method that belongs under the category of an explicitly defined skin region model. This skin classifier was tested with SIdb dataset and two benchmark datasets; UChile and TDSD datasets to measure classifier performance. The performance of skin classifier was measured based on true positive (TF) and false positive (FP) indicator. This newly proposed model was compared with Kovac, Saleh and Swift models. The experimental results showed that the RGB ratio model outperformed all the other models in term of detection rate. The RGB ratio model is able to reduce FP detection that caused by reddish objects colour as well as be able to detect darkened skin and skin covered by shadow.

Effects of multi-polar radiofrequency and pulsed electromagnetic field treatment in Koreans: case series and survey study

Background: Recently, a novel combined multi-polar radiofrequency and pulsed electromagnetic field device was developed for non-ablative skin tightening. However, little is known about the clinical effects of this device. Objectives: The present study evaluated the clinical efficacy and safety of the multi-polar radiofrequency and pulsed electromagnetic field device. Materials and Methods: Ten Korean patients underwent eight treatment sessions over 6 weeks. Clinical photographs of the skin were taken before and after the treatment at each week of treatment. Satisfaction score (0; dissatisfied, 5; neutral, 10; very satisfied) and pain score (0; no pain, 10; too painful) was determined using weekly questionnaires. A dermatologist evaluated the improvement of facial skin aging, including laxity, nasolabial fold, facial contour, skin texture, and skin color tone. Results:The mean satisfaction score was high (>8) and the mean pain score was low (1.5). Improved skin laxity, nasolabial fold, and facial contour were observed in four, one, and three patients, respectively. Skin texture and skin color tone improved in 90% and 70% of the patients, respectively. Conclusion: The novel combined multi-polar radiofrequency and pulsed electromagnetic field device is safe and effective for rejuvenating aged skin in Korean subjects.

A High-Performance Skin Segmentation Method

A method for skin segmentation is presented which based on a similarity classifier of skin-tone constructed by the Real Adaboost algorithm and dynamic threshold. Based on the clustering property of skin-tone distribution in YCrCb chrominance space, a strengthened classifier is presented by training a set of weak classifiers in look-up-table type using circle-like features by Adaboost. Gray scale images indicating the skin-tone similarity of the pixels is created by processing the multiresolution images of the original image with the strengthened classifier. Then, skin segmentation is implemented according to the dynamic threshold selected through Da-Jing method. Finally the result of skin segmentation could be obtained by composing the skin segmentation for different resolution of Original image. The experimental shows that the strengthened classifier has an outstanding ability for describing the distribution of skin-tone color in the YCrCb space, this method is robust, efficient and is applicable in the application of skin-tone region segmentation.

Increasing the reliability of skin detectors

Skin detection is a well-known image processing technique that has been used in many applications such as video surveillance, naked image filters, and face detection. This paper proposes a reliable skin detection method that integrates both color and texture features. To increase the reliability of the skin detection process, neighborhood pixel information is incorporated into the proposed method. Texture features were estimated using statistical measures as range, standard deviation, and entropy. Back propagation artificial neural network is then used to learn features and classify any given input. In this work, three skin detectors based on pre-defined rules of skin color tones, texture features only, and a combination of both color and texture features have been constructed. Furthermore, the paper analyzes and compares the obtained results from the proposed skin detector with pre-defined color tones and texture feature-based skin detectors to show the level of robustness of the proposed skin detector. It found that the proposed skin detection method achieved a true positive rate of approximately 95.6176% and a false positive rate of approximately 0.8795%. Experimental results showed that our approach is more efficient compared with other state-of-the-art color-based or texture-based skin detector approaches. Key words: Skin detector, supervised learning, back propagation ANN, Image texture features, Image segmentation.

New approach to the evaluation of skin color of pigmentary lesions using Skin Tone Color Scale

Objective methods of measuring skin color are needed to evaluate pigmentary lesions quantitatively. We have developed a new method of measuring skin color using a plastic bar system called the Skin Tone Color Scale based on Munsell's color space system. We have also evaluated the effectiveness of various therapies using this measurement system. Our system was designed to measure skin color in normal skin, pigmentary lesions of solar lentigo, chloasma and ephelides, and postinflammatory pigmentation. Moreover, effectiveness of various therapies for these pigmentary lesions was evaluated. The evaluations made with this system were closely related to physician assessment. This method may be useful in measuring of skin color and evaluating the effectiveness of therapies for pigmentary diseases.

Spectroscopic Characterization of Color Polymorphism in the Orbital Skin

The color and shape of the orbital skin have specific properties, differing from those of the cheek and forehead. Changes in the properties of the orbital skin are recognized as so-called “dark circles.” To understand the variety in the color and shape of the orbital skin, we previously observed the orbital skin in 180 healthy females, and found color tone characteristics (brown, red, and blue) and various morphological characteristics. We also established a photographic scale for their scoring and reported the results of the analysis of their correlation with age at the 48th Conference of the SCCJ. In this study, to clarify the association of skin color tone with melanin and regional blood flow, analysis of skin properties by non-invasive spectroscopy and assessment by scoring using the photographic scale were performed in 60 healthy females. The brown tone score was positively correlated with the melanin index. This suggested that the brown tone in the orbital skin is due to melanin. The red tone score was positively correlated with the Hb value and negatively correlated with the blood flow rate. These results suggested that the red tone in the orbital skin is due to increased Hb and blood flow stagnation. The blue tone score was negatively correlated with oxygen saturation and blood flow, suggesting that the blue tone in the orbital skin reflects blood flow stagnation and decreased skin circulation. These results suggested the important role of regional blood flow, and changes in melanin content play important roles in changes in the color tone of the orbital skin.

컬러영상에서 Pulse-Coupled Neural Network를 이용한 얼굴 추출 알고리즘

본 논문에서는 컬러영상에서 Pulse-Coupled Neural Network를 이용한 얼굴 추출 알고리즘의 성능을 향상시키는 방법에 대하여 논의하였다. 색상정보를 이용한 얼굴 추출 알고리즘은 얼굴의 기울어진 정도나 크기 등에 영향을 받지 않으므로, 형태정보를 이용한 얼굴 추출 알고리즘에 비해 비교우위를 가진다. 그러나, 조명의 변화가 심하거나 피부색과 유사한 배경이 포함되어 있을 경우 적절한 성능을 내기 어렵다. 이러한 문제점들을 해결하기 위해 본 논문에서는 실험을 통해 피부색의 평균과 분산 값을 미리 구한 후, 전처리 과정을 거쳐 피부색의 평균값을 갖는 픽셀이 255값을 갖고, 나머지 픽셀 값들이 255를 중심으로 정규분포를 이루도록 하였다. 이러한 전처리 과정을 통해 Pulse-Coupled Neural Network의 linking coefficient를 보다 쉽게 결정하도록 하였다. In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of the skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value (255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking coefficient of Pulse-Coupled Neural Network.

Mate Selection Preferences Among African American College Students

All cultures have rules regarding mate selection. Many societies encourage either homogamy or heterogamy. Homogamy refers to marriage between individuals with similar social and personal characteristics, whereas heterogamy refers to marriage between individuals with different social or personal characteristics. Although there is some freedom in mate selection in American society, the United States is still basically a society whose norms encourage homogamy. Some of the major factors that influence mate selection include socioeconomic status, race, age, and parental and peer pressures. The purpose of this article is to examine the attitudes and preferences of African American college students toward physical and social status related variables regarding dating and future mate selection. Several social status and attractiveness related variables, along with selected background variables (including gender), were analyzed to note relationship patterns. Of particular interest was the importance of skin color or skin tone and social status as mate selection preferences among African American college students. There may be vast differences between attitudes toward mate selection and actual behaviors when selecting mates for marriage. Attitudinal research on skin color and social status preferences as they relate to mate selection on African American populations is lacking.

女性顔面の肌色及び色ムラ評価の新しい試み 偏光画像解析システムの開発と色ムラ評価への応用

To evaluate skin color and skin tone exactly, we developed a new instrument, Skin Tone Analyzer (STA), which applys an image-processing system on the polarized images of skin.The insertion of two polarized filters into the CCD camera in STA made the observation of clear images without interference from the diffuse reflections originating on the surface of the skin. The 20 times magnified images of the skin surface (1×1cm) are resolved into 400×400 points and transfered to a digital computer. To measure the color difference value, calculate the L, a and b values of each point from their respective R, G and B values, using conversion equations determined from the measurement of two hundred pieces of standard color papers with the STA and general spectrophotometric colorimeter (CMS-1200). Then, the color differences determined by STA are indicated as average values of L, a and b values for a finite set of points. Further, their standard deviation values (s. d.) which may represent the degree of skin tone (irregularity in the lavel of skin color) are obtained. In fact, we found that the s. d. of b values (s. d. b) among the three components, L, a and b, reflects appropriately the degree of skin tone caused by delocalization of melanin. Thus we now propose that the s. d. b is a good parameter for the evaluation of skin tone. Moreover, a designated part of images can be analyzed and STA will be a useful tool for the study of pigmentation spots.Based on the above assumption, we examined the effect of seasons and aging on the skin color and skin tone of the cheek (exposed skin) and the inside of the upper arm (non-exposed skin) in healthy Japanese females (N=62, 19-75y) with STA. From the analyses of skin tone during periodical measurements, the degree of skin tone in the cheek was found to be worse than the arm's. The former becoming worse owing to aging, but the later exhibiting no change. Also the degree of skin tone in the cheek in October (after the summer) was worse than in February (in the winter). In addition, L and b values for the cheek also increased owing to aging, but these values for the arm did not so change.It is known that daily exposure to ultraviolet rays (UV) can influence colory skin. We now also confirm that UV promotes a change for the worse in the skin tone. Next, we propose to study the effects of UV on localized pigmentation using STA.