• 한국위성정보통신학회논문지
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• 제8권4호
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• pp.117-123
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• 2013

최근 스마트폰의 감정인식 기술과 멀티미디어 기술의 발전은 전통적인 방송방식의 새로운 변화를 요구하고 있다. 기존 지상파방송사업자 중심의 단방향 방송은 인터넷, 모바일 그리고 스마트 TV의 결합으로 시청자 중심의 감성방송을 제공하는 양방향 방송매체로의 변환이 불가피하다. 그러므로 본 논문에서는 사용자의 감정(슬픔, 분노, 우울)을 측정할 수 있는 스마트폰 애플리케이션을 개발하고 스마트 TV와 융합함으로써 함께 시청하는 사용자 그룹간의 감성적인 상호 유대감을 높이는 서비스를 제공한다. 만약 사용자 그룹 중에 우울증에 빠진 친구가 있다면, 감정인식 기반의 스마트폰과 TV와의 융합을 통해 시청중인 방송에 초대하여 친구 아바타(이모티콘)의 표정을 보면서 진솔한 대화를 나눔으로써 인간적인 위로를 줄 수 있다. 제안하는 스마트폰 연동의 감성방송 서비스를 통해 외로움과 우울증으로 고통 받는 친구에게 인간적인 유대감과 행복감을 제공함으로써 개인의 극단적인 결정으로부터 구출할 수 있다. 추가적으로, 제안하는 양방향 방송서비스는 시청자의 감성에 따른 프로그램 추천서비스, 감성조명 서비스를 통한 실재감 극대화 및 시청자의 기분을 활용한 홈쇼핑 서비스로 확장이 가능하다.

• 한국전자거래학회지
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• 제17권3호
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• pp.1-14
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• 2012

전자 정보 기술이 발전함에 따라, 스마트폰의 계산 능력은 더욱 막강해지고 저장장치의 용량은 더욱 거대해지고 있다. 이에 따라, 유용한 새로운 스마트폰 서비스가 많이 등장하고 있는데, 상황인지 서비스와 모바일 증강 현실이 근래에 가장 많이 연구되고 있는 대표적인 주제이다. 이러한 새로운 서비스에서 스마트폰에 장착된 카메라로 촬영한 사진 속의 개체를 인지하는 것은 매우 중요한 역할을 수행한다. 그래서 사진을 인지하는 연구가 많이 출판되었는데, 대부분은 처리 시간이 매우 긴 이미지 인지 기술 기반이다. 이와 반대로, 본 논문은 스마트폰의 센서로부터 수집한 데이터와 전자지도를 이용하여 사진 속의 개체를 인지하는 매우 빠르고 효율적인 방법을 제안한다. 제안하는 방법은 스마트폰이 제공하는 현재 위치와 방향각으로 카메라의 시선을 구하고, 카메라 시선과 교차하는 전자지도의 요소들을 찾는다. 그리고 교차하는 요소들을 조사하여 사진 속의 개체를 인지한다.

• 한국공작기계학회논문집
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• 제15권3호
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• pp.73-81
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• 2006

This paper describes our primary study for a new method of recognizing materials, which is need for precision work system. This is a study of dynamic characteristics of smart sensors, new method$(R_{SAI})$ has the sensing ability of distinguishing materials. Experiment and analysis are executed for finding the proper dynamic sensing condition. First, we developed advanced smart sensor. We made smart sensors for experiment. The type of smart sensor is HH type. The smart sensor was developed for recognition of material. Second, we develop new estimation methods that have a sensing ability of distinguish materials. Dynamic characteristics of sensor are evaluated through new recognition index$(R_{SAI})$ that ratio of sensing ability index. Distinguish of object is executed with $R_{SAI}$ method relatively. We can use the $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object (auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• 한국융합학회논문지
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• 제10권11호
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• pp.33-39
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• 2019

교육업계에 교육과 정보기술(IT)을 융합한 '에듀테크' 바람이 불고 있다. 4차 산업혁명 핵심 기술이 최근 교육 분야에 적극 활용되고 있는데 학습자들은 인공지능 기반 학습 플랫폼을 이용해 자신이 부족한 부분을 스스로 진단하고, 클라우드 학습 플랫폼으로 온라인상에서 개인 맞춤형 교육을 받는다. 최근 인공지능 기술과 음성인식 기술을 접목한 스마트 스피커와 같은 새로운 교육 매체가 등장하게 되어 다양한 교육서비스가 시도되고 있다. 본 연구에서는 기존 교육의 한계를 극복하기 위해 스마트 스피커를 교육적으로 활용하는 방안을 제시하고자 하였다. 이를 위해 스마트 스피커의 개념 및 특성을 알아보고 스마트 스피커에서 제공하는 콘텐츠를 분석하여 시사점을 도출하였다. 또한 스마트 스피커이용의 문제점에 대해서도 고찰하였다.

• International Journal of Contents
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• 제10권4호
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• pp.63-68
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• 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.

• International Journal of Internet, Broadcasting and Communication
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• 제12권2호
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• pp.120-126
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• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• International journal of advanced smart convergence
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• 제8권3호
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• pp.95-101
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• 2019

Recently, there have been many issues related to text recognition using Tesseract. One of these issues is that the text recognition accuracy is significantly lower for smaller fonts. Tesseract extracts text by creating an outline with direction in the image. By searching the Tesseract database, template matching with characters with similar feature points is used to select the character with the lowest error. Because of the poor text extraction, the recognition accuracy is lowerd. In this paper, we compared text recognition accuracy after applying various super-resolution methods to smaller text images and experimented with how the recognition accuracy varies for various image size. In order to recognize small Korean text images, we have used super-resolution algorithms based on deep learning models such as SRCNN, ESRCNN, DSRCNN, and DCSCN. The dataset for training and testing consisted of Korean-based scanned images. The images was resized from 0.5 times to 0.8 times with 12pt font size. The experiment was performed on x0.5 resized images, and the experimental result showed that DCSCN super-resolution is the most efficient method to reduce precision error rate by 7.8%, and reduce the recall error rate by 8.4%. The experimental results have demonstrated that the accuracy of text recognition for smaller Korean fonts can be improved by adding super-resolution methods to the OCR preprocessing module.

• 한국멀티미디어학회논문지
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• 제18권8호
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• pp.943-949
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• 2015

A reader usually spends a lot of time browsing and searching word meaning in a dictionary, internet or smart applications in order to find the unknown words. In this paper, we propose a method to compensate this drawback. The proposed method introduces a vocabulary upon recognizing a word or group of words that was captured by a smart phone camera. Through this proposed method, organizing and editing words that were captured by smart phone, searching the dictionary data using bisection method, listening pronunciation with the use of speech synthesizer, building and editing of vocabulary stored in database are given as the features. A smart phone application for organizing English words was established. The proposed method significantly reduces the organizing time for unknown English words and increases the English learning efficiency.

• International journal of advanced smart convergence
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• 제5권2호
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• pp.66-72
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• 2016

With the growing shift from traditional educational approaches and studying to the more digital classroom, using electronic textbooks and digital native's demand, there is a growing need to develop new methods for learn Kanji characters for children. The purpose of this study is to help children learn the basic Kanji by using stop motion and block methods, and approaching the basic Kanji character education with a more innovative and interactive smart phone APP. In the development of this smart phone App for children's Kanji character education proposed in this study, 100 basic Kanji characters for children are selected. These 100 characters are required for the stop motion animation production, where each selected Kanji is created as a stop-motion animation utilizing a variety of techniques, such as storytelling, to better engage children. The intelligent App is designed with image recognition technology, so that in the learning process children take a picture for the assembled block using their smart phone, the APP then recognizes whether it is assembled correctly, and then plays an animation corresponding to the assembled Kanji character.

• International journal of advanced smart convergence
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• 제11권3호
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• pp.72-78
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• 2022

The aim of this research is to improve the effectiveness of digital media advertising because current advertisements -in digital signage - indiscriminately appeals to the general public rather than to a specific target. In order to deliver efficient and customized advertisement information, an IoT human body detection sensor mounted on digital signage detected human faces and then classified them firstly by gender. The digital signage here is a smart digital signage that can analyze facial signals, discriminate them based on patterns, and apply the extracted data by displaying the corresponding information to the user. In addition, by identifying the customer's location approaching the smart digital signage and displaying the optimized content information for the customer's location through an algorithm, the digital signage can dramatize the advertisement Thus, this is a study meant forimproving information efficiency while reducing noise and driving power waste generated from unnecessary digital information reproduction.