• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.21-26
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• 2017

In this paper, an USB-OTG (Uiversal Serial Bus On-the-go) interface module was designed with the iris information for personal identification. The image recognition algorithm which was searching face and iris areas, was proposed with pixel differences from eye blinking after several facial images were captured and then detected without any activities like as pressing the button of smart phone. The region of pupil and iris could be fast involved with the proper iris area segmentation from the pixel value calculation of frame difference among the images which were detected with two adjacent open-eye and close-eye pictures. This proposed iris recognition could be fast processed with the proper grid size of the eye region, and designed with the frame difference between the adjacent images from the USB-OTG interface with this camera module with the restrict of searching area in face and iris location. As a result, the detection time of iris location can be reduced, and this module can be expected with eliminating the standby time of eye-open.

• Journal of KIISE
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• v.45 no.1
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• pp.15-21
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• 2018

Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.118-126
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• 2000

동양의학에서 인체의 주된 생리 정보는 체질과 맥진에서 얻어질 수 있다 체질은 선천적인 오장 육부 기능에 대한 정보를 제공한다. 체질에 대한 판단은 얼굴형상, 맥진, 사주 등의 방법에 의한다. 반면에 진맥은 현재의 오장육부의 건강 상태를 나타낸다. 오장육부의 생체정보는 인체경락의 전기 전도도를 측정하는 방법에 의해서도 얻어질 수 있으나 본 논문에서는 진맥에의한 방법만을 토론한다. 체질과 진맥 정보는 치병에 있어서 처방의 기간과 강도를 결정 할 수 있는 결정적인 변수이다. 이 두가지 정보 중에서 하나라도 결핍될 경우 병에 대한 효율적인 대응이 어려워진다. 그 이유는 처방의 강약 조절이 어렵고 그 결과 다른 부작용 유발가능성이 크다. 본 논문에서는 진맥이론의 일반적 전개를 위하여 음양오행 성질의 과학적인 정의를 기초로 하였다. 구체적인 맥상의 판단에는 (1) 음의 맥과 양의 맥의 절대적 크기와 상대적 비(즉 음양의 강도와 비), (2) 오행의 성질에 기초한 맥의 형상, 그리고 (3) 맥의 느낌이나 성질등 3가지 정보를 종합한 방법으로 맥상을 파악한다. 이러한 맥진기술 이론은 분류방법이 간단할 뿐만아니라 이론이 일반적이다. 그래서 한의학의 전문가는 물론이고 일반인 모두 쉽게 익혀 덜인의 건강상태를 스스로 파악하는 것이 가능하다. 진맥기 제작의 기년 이론으로서 역할을 할 수 있다. 오행이론에 기초 할 경우 맥상은 5가지 대표적인 맥으로 분류된다. 맥의 이름은 황제내경에 제시된 한의학적인 이름과 함께 맥상을 쉽게 유추 할 수 있는 실생활적인 이름을 병용하였다. 예를 들어 위장이 약할 때 나타나는 홍맥을 진빵같이 부드러운 맥으로, 폐가 나쁠 때 나오는 흩어지는 모맥을 도우너츠형 연기맥으로, 신장이 나쁠 때 나오는 단단한 석맥을 고구마형상의 돌덩어리맥으로, 간이 나쁠 때 나오는 긴장된 현맥을 팽팽한 고무줄맥으로 그리고 심장이 나쁠 때 나오는 작고 연한 구맥을 튀어오르는 물방울맥으로 명명하였다. 이외에 진맥에 의하여 인체의 한열이나 지삭 부침등의 정보가 가능하며, 이러한 정보는 고혈압이나 중풍 확률, 비만 가능성 지수, 골다공증 선행지수 그리고 심장기능 파악(불전맥이나 대맥) 등 다양한 인체 정보를 파악하는 데 응용될 수 있음을 강조한다.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.129-136
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• 2009

Unlike former researches, this study for developing the caricature generator began observing the methods that other caricature experts have adopted. According to the observation, it seemed that experts tried to exaggerate characteristics of the target shape from other similar objects. When we are saying "This is similar to that," we give salience to their difference among the identical form groups. This study was to find the most similar geometry form to the target shape and then to transform its form through exaggeration. The research scope was restricted to exaggerate the outline shape of two-dimensional looped curve as a caricature form. For this, the author discussed the following: (a) organization method of four kinds of similar geometry form database, (b) search method to find the pertinent similar geometry form, (c) arrangement method for those searched data, and (d) method to exaggerate the target shape. Human faces and cars were selected as research categories to make the database. According to the survey over the transformed results, it was proved its possibility.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.806-813
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• 2010

Human facial expression shows human's emotion most exactly, so it can be used as the most efficient tool for delivering human's intention to computer. For fast and exact recognition of human's facial expression on a 2D image, this paper proposes a new method which integrates an Discrete Adaboost classification algorithm and a neural network based recognition algorithm. In the first step, Adaboost algorithm finds the position and size of a face in the input image. Second, input detected face image into 5 Adaboost strong classifiers which have been trained for each facial expressions. Finally, neural network based recognition algorithm which has been trained with the outputs of Adaboost strong classifiers determines final facial expression result. The proposed algorithm guarantees the realtime and enhanced accuracy by utilizing fastness and accuracy of Adaboost classification algorithm and reliability of neural network based recognition algorithm. In this paper, the proposed algorithm recognizes five facial expressions such as neutral, happiness, sadness, anger and surprise and achieves 86~95% of accuracy depending on the expression types in real time.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.563-571
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• 2017

The purpose of this paper is to establish an emotional expression factors of digital eye contents that can be applied to digital environments. The emotion which can be applied to the smart doll is derived and we suggest guidelines for expressive factors of each emotion. For this paper, first, we research the concepts and characteristics of emotional expression are shown in eyes by the publications, animation and actual video. Second, we identified six emotions -Happy, Angry, Sad, Relaxed, Sexy, Pure- and extracted the emotional expression factors. Third, we analyzed the extracted factors to establish guideline for emotional expression of digital eyes. As a result, this study found that the factors to distinguish and represent each emotion are classified four categories as eye shape, gaze, iris size and effect. These can be used as a way to enhance emotional communication effects such as digital contents including animations, robots and smart toys.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.89-98
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• 2004

In this paper, we implement a digital holographic security card system that combines digital holographic memory using random phase encoded reference beams with electrical biometrics. Digitally encoded data including a document, a picture of face, and a fingerprint are recorded by multiplexing of holographic memory. A random phase mask encoding reference beams are used as a decoded key to protect illegal counterfeit. As a result, we can achieve a raw BER of 3.6${\times}$10-4 and shift selectivity of 4${\mu}{\textrm}{m}$ using the 2D random phase mask. Also, we develop a recording pattern and image processing which are suitable for a low cost reader without a position sensing photo-detector for real time data extraction and remove danger of fraud from unauthorized person by comparing the reconstructed holographic data with the live fingerprint data.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.349-356
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• 2020

This paper introduces the implementation of a driver's condition warning system using eye aspect ratio to prevent a car accident. The proposed driver's condition warning system using eye aspect ratio consists of a camera, that is required to detect eyes, the Raspberrypie that processes information on eyes from the camera, buzzer and vibrator, that are required to warn the driver. In order to detect and recognize driver's eyes, the histogram of oriented gradients and face landmark estimation based on deep-learning are used. Initially the system calculates the eye aspect ratio of the driver from 6 coordinates around the eye and then gets each eye aspect ratio values when the eyes are opened and closed. These two different eye aspect ratio values are used to calculate the threshold value that is necessary to determine the eye state. Because the threshold value is adaptively determined according to the driver's eye aspect ratio, the system can use the optimal threshold value to determine the driver's condition. In addition, the system synthesizes an input image from the gray-scaled and LAB model images to operate in low lighting conditions.

• 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 the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.339-345
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• 2016

In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.