• Journal of Information Technology Services
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• v.6 no.3
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• pp.241-249
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• 2007

This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.

• ETRI Journal
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• v.38 no.4
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• pp.776-786
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• 2016

The fairly recent standard of equipping mobile devices with advanced imaging sensors has opened the possibility of conveniently diagnosing skin conditions, anywhere, anytime. For this application, we attempted to estimate skin conditions from a skin image taken by a mobile handheld camera. To estimate the skin conditions, we specifically identified three skin features (pigmentation, pores, and roughness) that can be measured quantitatively from a skin image. The experimental data indicate that the existing thresholding methods are inappropriate for extracting the pigmentation and pore skin features. Thus, we propose a new line-fitting based thresholding method for skin feature detection. We thoroughly evaluated our proposed skin condition estimation method using our skin image database. The experimental results show that our proposed thresholding method can better determine the threshold leading to the most visually plausible detection, when compared to existing methods. We also confirmed that skin conditions can be feasibly estimated using a common mobile handheld camera (for example, a smartphone).

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.1
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• pp.69-82
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• 2015

This study is conducted to verify out whether any important differences can be made with factors of service qualities by the population statistics and trait of skin care shops. And this study is conducted to find out the relation that service qualities may influence on switching barrier and customer satisfaction. For this study, 396 questionnaires were used which had been returned from the customers of the skin care shops of Seoul, Gyeonggi and Chungchyung provinces from 15th April to fifth May, 2013. To analyze above data, frequency analysis, t-test, ANOVA, factor analysis, regression analysis are carried out by using an SPSS 18.0 statistical package. The results are as follows : The features of services of the skin care shops are analyzed into four factors which were Assurance, Materiality, Responsiveness, Agreeability. The features of switching barrier are analyzed into three factors which are Alternative attractiveness, Interpersonal relationship, Switching cost. There are important differences in the concept four service qualities of skin care shops by the features of the statistics of population according to sex, marriage, monthly income and the types of job. The four features of service qualities of the skin care shops have positive influences on the three features of switching barrier - Assurance, Responsiveness, Agreeability and the three features of customer satisfaction - Assurance, Materiality, Agreeability. Through this study, We can have the conclusion that the switching barrier made by the building up the qualities of service can prevent the customers from dropping away.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4508-4515
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• 2014

Real-time body detection has been researched actively. On the other hand, the detection rate of color distorted images is low because most existing detection methods use static skin color model. Therefore, this paper proposes a new method for detecting the skin color region using a gradient map and saturation features. The basic procedure of the proposed method sequentially consists of creating a gradient map, extracting a gradient feature of skin regions, noise removal using the saturation features of skin, creating a cluster for extraction regions, detecting skin regions using cluster information, and verifying the results. This method uses features other than the color to strengthen skin detection not affected by light, race, age, individual features, etc. The results of the detection rate showed that the proposed method is 10% or more higher than the traditional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.55-61
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• 2015

Today, IT technology provide convenience to many people. Smartphone era is opened, and market environment is changing rapidly. Pornography market is active by using smartphone use free internet. Many people access mobile harmful site of USA and Japan. App store of the apple has been cut off the porn service, but access block to mobile Web page is an impossible situation. In this paper, we proposed the harmful image detection method of using skin and non skin features to detect harmful image. Our proposed method can provide enough performance than previous method.

• Journal of IKEEE
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• v.14 no.4
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• pp.332-338
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• 2010

Usually, mage feature extraction methods are performed as a pre-processing step in many applications including image retrieval, object recognition, and image indexing. Especially, in the image texture analysis, texture feature extraction methods attempt to increase texture contrast to make it easier to extract the texture features from the image. One of the distinct textures in microscopic skin image is the wrinkle, and its features could provide various useful information for the age-related applications. In this paper, we propose a scheme to extract age-related features from the skin images and improve its accuracy in the skin age estimation.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.436-442
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• 2017

A novel method of Skin lesion segmentation based on the combination of Texture and Neural Network is proposed in this paper. This paper combines the textures of different pixels in the skin images in order to increase the performance of lesion segmentation. For segmenting skin lesions, a two-step process is done. First, automatic border detection is performed to separate the lesion from the background skin. This begins by identifying the features that represent the lesion border clearly by the process of Texture analysis. In the second step, the obtained features are given as input towards the Recurrent Echo state neural networks in order to obtain the segmented skin lesion region. The proposed algorithm is trained and tested for 862 skin lesion images in order to evaluate the accuracy of segmentation. Overall accuracy of the proposed method is compared with existing algorithms. An average accuracy of 98.8% for segmenting skin lesion images has been obtained.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.610-619
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• 2015

*In this paper, we propose a real-time face tracking system using an adaptive face detector and a tracking algorithm. An image is divided into the regions of background and face candidate by a real-time updated skin color identifying system in order to accurately detect facial features. The facial characteristics are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted by Principal Component Analysis (PCA), and the interpreted principal components are processed by Support Vector Machine (SVM) that classifies into facial and non-facial areas. The movement of the face is traced by Kalman filter and Mean shift, which use the static information of the detected faces and the differences between previous and current frames. The proposed system identifies the initial skin color and updates it through a real-time color detecting system. A similar background color can be removed by updating the skin color. Also, the performance increases up to 20% when the background color is reduced in comparison to extracting features from the entire region. The increased detection rate and speed are acquired by the usage of Kalman filter and Mean shift.

• Archives of Craniofacial Surgery
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• v.21 no.2
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• pp.123-126
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• 2020

Skin cancer, which often occurs as a result of skin exposure to ultraviolet light radiation, usually presents with characteristic abnormal features, such as ulcerative lesions, irregular morphology, bleeding, and excessive growth. Therefore, skin cancer rarely resembles a benign tumor on visual inspection. Nonetheless, squamous cell carcinoma and basal cell carcinoma with nodular or polypoid features can have a similar appearance to that of benign tumors, meaning that they are sometimes misdiagnosed as benign. As benign and malignant tumors have some overlapping features, clinicians sometimes use additional imaging techniques such as ultrasonography to improve the accuracy of the diagnosis because even a malignant tumor that externally resembles a benign tumor generally has internal morphological features characteristic of malignancy, such as invasion and irregular borders. However, these imaging tools also have limitations, and punch or excisional biopsy can be needed if malignancy cannot be completely ruled out. Herein, we report a case of skin malignancy initially misdiagnosed as a benign epidermal cyst based on external visual inspection and ultrasonography.