• Journal of the Society of Cosmetic Scientists of Korea
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• v.41 no.3
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• pp.279-285
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• 2015

Hyperpigmentation on face is a highly anxiety-producing symptom, especially for women from the aspect of beauty. Pigmentation of the skin is related to the amount of melanin that provides protection against UV radiation. In vivo reflectance confocal microscopy is a non-invasive imaging tool allowing visualization of the skin without tissue alteration, by placing a microscopy directly on the living skin. The aim of this study was to develop the new evaluation method of whitening effects using in vivo reflectance confocal microscopy and to validate other instruments for measuring skin colors, and UV-induced hyperpigmentation was elicited on the inside skin of the forearm. It suggested that the new method for whitening effects using the confocal microscopy was useful to evaluate the de-pigmentation products and to easy for understanding to customers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2961-2967
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• 2014

Nowadays, a private protection act has come into effect which demands for the protection of personal image information obtained by the CCTV. According to this act, the object out of interest has to be mosaicked such that it can not be identified before the image is sent to the investigation office. Meanwhile, the demand for digital videos obtained by CCTV is also increasing for digital forensic. Therefore, due to the two conflicting demands, the demand for a solution which can automatically mask an object in the CCTV video is increasing and related IT industry is expected to grow. The core technology in developing a target masking solution is the object tracking technique. In this paper, we propose an object tracking technique which suits for the application of CCTV video object masking as a postprocess. The proposed method simultaneously uses the motion and the color information to produce a stable tracking result. Furthermore, the proposed method is based on the centroid shifting method, which is a fast color based tracking method, and thus the overall tracking becomes fast.

• Journal of the Korean Society of Costume
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• v.61 no.10
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• pp.42-54
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• 2011

The study was focused on surveying the cultural identity and the origin of T-shirts, and examining their functions. Six cities were selected to categorize the design motifs of cultural identity appearing in the design of contemporary T-shirts. These cities include a city in France, United Kingdom, Italy, United States and Japan where collections are currently presented at, and also a city in China that has shown a high economic growth as one of the most popular sightseeing cities. Cultural identity was presented in the T-shirts that were examined in this study through diversified design motifs. Motifs used in T-shirt designs to reflect cultural identity included national flags, notable places, letters, names of geographic places, and individuals. A national flag is a motif that signifies national identity and it was used in the front of T-shirts as it is or was just partially used. Also, many world-renowned structures or architectural buildings were applied to T-shirt design. Noted places such as the White House, the Statue of Liberty in the U.S., Tienanmen Square in China and the Eiffel Tower in France were used. The unique characters of language, such as Hangeul in Korea were used as design elements to reflect the structural characteristics of letters. Names of geographic places were used as design elements through the disclosure of the name of a symbolic city or a tourist site in each country. In terms of figures, not only the historical figures or celebrities from each country were used, but the image of bodies and faces that represent each culture were used as well. In addition, this study was used to develop T-shirt designs that reveal the cultural identity of Korea.

• Fashion & Textile Research Journal
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• v.7 no.5
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• pp.527-534
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• 2005

The purpose of this research is to study face images according to color of make-up was made by computer graphic simulation. The various facial images can be helpful for choosing suitable make-up color planning. In order to find out the differences of face images by make-up color, three different foundations and seven eye-shadows, six lips were applied on the round face model. Make-up Image Scale was used the scale of seven point modified the S-D method. Data were analyzed by Varimax perpendicular rotation method, Duncan's Multiple Range Test, Three-way ANOVA. As the result of make-up image perception analysis, a factor structure was divided into mildness, modernness, elegance, unique. The factor of mildness, modernness, unique affected on the foundation color. Foundation color was found out to be influential variable to distinguish color perception abilities. Also, the foundation, eye-shadow, lip color were influenced interactively on the perception of elegance factor. Pink color was important color, influenced on the mildness factor. Gray and purple color were influenced on the modernness factor. Mildness factor was perceived as the most bright foundation but unique factor was perceived as the most dark foundation. Then, the foundation, eye-shadow, lip color were influenced interactively on the perception of facial images. The results can be effectively applied to today's marketing and color design management which is focused on the product's emotional image in customer's mind.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.47-56
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• 2005

With the development of wearable(ubiquitous) computers, those traditional interfaces between human and computers gradually become uncomfortable to use, which directly leads to a requirement for new one. In this paper, we study on a new interface in which computers try to recognize the gesture of human through a digital camera. Because the method of recognizing hand gesture through camera is affected by the surrounding environment such as lighting and so on, the detector should be a little sensitive. Recently, Viola's detector shows a favorable result in face detection. where Adaboost learning algorithm is used with the Haar features from the integral image. We apply this method to hand area detection and carry out comparative experiments with the classic method using skin color. Experimental results show Viola's detector is more robust than the detection method using skin color in the environment that degradation may occur by surroundings like effect of lighting.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.37-44
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• 2017

While IoT (Internet of Things) industry has been spreading, it becomes very important for object to recognize user's information by itself without any control. Above all, gender (male, female) is dominant factor to analyze user's information on account of social and biological difference between male and female. However since each gender consists of diverse face feature, face-based gender classification research is still in challengeable research field. Also to apply gender classification system to IoT, size of device should be reduced and device should be operated with low power. Consequently, To port the function that can classify gender in real-world, this paper contributes two things. The first one is new gender classification algorithm based on deep learning and the second one is to implement real-time gender classification system in embedded board operated by low power. In our experiment, we measured frame per second for gender classification processing and power consumption in PC circumstance and mobile GPU circumstance. Therefore we verified that gender classification system based on deep learning works well with low power in mobile GPU circumstance comparing to in PC circumstance.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.31-36
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• 2017

In this paper, we try to search and reproduce the image part of a specific cast from a large number of images. The conventional method must manually set the offset value when searching for a scene or viewing a corner. However, in this paper, the proposed method learns the main character 's face, then finds the main character in the image recognition and moves to the scene where the main character appears to reproduce the image. Data for specific performers is extracted and collected using crawl techniques. Based on the collected data, we learn using convolutional neural network algorithm and perform performance evaluation using it. The performance evaluation measures the accuracy by extracting and judging a specific performer learned in the extracted key frame while playing the drama. The performance confirmation of how quickly and accurately the learned scene is searched has obtained about 93% accuracy. Based on the derived performance, it is applied to the image service such as viewing, searching for person and detailed information retrieval per corner

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.105-109
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• 2021

In this paper, we evaluate Boosted 3-D PCA as a Dataset and evaluate its performance. After that, we will analyze the network features and performance. In this paper, the learning was performed using the 300W-LP data set using the same learning method as Boosted 3-D PCA, and the evaluation was evaluated using the AFLW2000 data set. The results show that the performance is similar to that of the Boosted 3-D PCA paper. This performance result can be learned using the data set of face images freely than the existing Landmark-to-Pose method, so that the poses can be accurately predicted in real-world situations. Since the optimization of the set of key points is not independent, we confirmed the manual that can reduce the computation time. This analysis is expected to be a very important resource for improving the performance of network boosted 3-D PCA or applying it to various application domains.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.7-11
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• 2019

Due to diversification and popularization of devices that use rapid transmission, there are many security issues related to radio waves. As the disturbance and interference of the radio wave can cause a direct inconvenience to a life, it is a very important issue. In this paper, as a means to prevent radio disturbance and interference, the projected image of the reference grid and the deformed grid is obtained by measuring the projected $moir{\acute{e}}$ using the white light source, projecting grid and the light source, and a $moir{\acute{e}}$ pattern is generated with an image processing algorithm by applying a phase diagram algorithm, and generated $moir{\acute{e}}$ pattern phase diagram creates a three-dimensional shape. By making an encrypted token using this measured face shape, the transmission of the information through token ring is determined in order to transmit the horizontal transmission having the dynamic security characteristics which includes authentication strength and caller information, etc. And by confirming the uniqueness of the token and by sending and receiving the horizontal transmission using java serialization and deserialization function, a problem solving method is suggested.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.