• The Optical Journal
• /
• s.121
• /
• pp.66-70
• /
• 2009

지난 3월 3일부터 5일까지 사흘간의 일정으로 미국 라스베거스에서 사진영상기기전시회 'PMA(Photo Marketing Association)2009'이 열렸다. 이미 작년 포토키나에서 관련 신상품들이 대거 쏟아져 나온지라 솔직히 이번 PMA에서 특별한 트랜드를 읽어낼 것이라는 기대는 하지도 않았다. 그러나 필자가 꼭 PMA에 가보고 싶었던 이유가 있었다. 사진 영상 시장에 종사하는 이들이라면 모두가 한결같이 '매우 어려운 시기'인 이때에 도대체 미국 시장에서는 어떠한 방법으로 시장을 헤쳐나가고 있는 지, 그리고 혹시나 한국 시장에서 미쳐 발견하지 못한 탈출구라도 있지는 않을까 하는 작은 희망이 필자의 발길을 그곳까지 이끌고 가 주었다. 이미 인터넷을 통해 대부분의 정보를 수집한터라 DSLR부분에서 특별한 신제품이 없을 것이며 출력시장은 대부분이 포토북을 중심으로 한 솔루션들을 소개할 것이라는 것쯤은 이해하고 있었다. 그런데 이 큰 흐름에서 한국의 우리는 어떠한 상품으로 고객에게 새로운 가치를 전달할 수 있을까? 출력 시장에서 포토북이 정답이라고 하는데 그것이 공급자의 논리인지 아니면 정말 일반소비자들의 니즈가 있는 것인지 확인하기 위해 PMA를 참관했다. 입력장비인 카메라의 트랜드에 대해 잠깐 언급하기는 하겠지만 그중에서도 출력 시장의 방향성에 초점을 맞추어 작성한 것임을 밝혀둔다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.7-10
• /
• 2008

정보기술과 디지털 기술의 발전에 힘입어 디지털 콘텐츠에 대한 수요가 증가하였다. 디지털 콘텐츠 중 비디오 콘텐츠는 순차적인 특성을 가지며, 시간과 공간정보가 결합된 3차원 데이타로써 처리시간이 높은 작업이기 때문에 검색이나 브라우징이 대단히 어렵다. 이러한 문제의 해결을 위하여 비디오 데이타를 구조화하는 동영상 내용 편집 도구(Authoring Tool for Video Contents)를 제안했었다. 본 논문에서는 동영상 내용 편집 도구의 연구를 확장하여, 이러한 구조화된 데이타를 이용하여 원하는 부분을 쉽게 볼 수 있을 뿐만 아니라, 검색을 위한 주석의 내용까지 보여줌으로써 사용자에게 효율적으로 제공할 수 있는 브라우징을 제안한다. 메타데이타가 저장된 XML파일을 이용하여 플렉스 솔루션으로 구현하였다. 즉, 웹 어플리케이션에 플래시를 도입시킨 것으로 플래시 플레이어(Flash Player)가 동작한다면 운영체제, 브라우저, 디바이스에 대해 독립적으로 실행될 수 있으며, 인터넷 익스플로어, 파이어 폭스, PDA, 핸드폰, 위성 단말기 등 어디에서든지 인터넷으로 같은 어플리케이션을 공유할 수 있는 환경을 제공할 수 있다.

• Annual Conference of KIPS
• /
• 2011.04a
• /
• pp.97-99
• /
• 2011

본 논문에서는 안전주행지원 솔루션인 스마트폰용 차선이탈경보 애플리케이션의 실행 속도 향상 방법을 연구하였다. 이전 연구에서 스마트폰(iPhone 3GS) 기반의 차선이탈경보 어플리케이션을 개발하였는데 입력 영상의 처리 속도가 1.52fps였다. 본 연구에서는 영상 처리 속도를 향상시키기 위한 최적화 작업을 진행하였으며 기존의 차선이탈경보 어플리케이션의 차선인식 속도보다 프레임당 평균 0.4초 정도 단축되어 약 4fps 속도로 성능을 보였다. 향후 추가 연구를 통해 처리 속도를 좀 더 향상시킬 것이다.

• Journal of Internet of Things and Convergence
• /
• v.6 no.2
• /
• pp.51-56
• /
• 2020

In this paper, we developed a mobile new media solution that enables e-commerce shopping mall operators, band operators, and YouTube creators to create synergies in online and offline promotion by posting related video contents on the media in addition to their own videos. By providing videos in the field of the platform without directly searching for them, it is possible to provide users with a new type of marketing means that can promote their platform while providing interest and information. Prospective creators at home and abroad who produce video can upload their own video in addition to YouTube and afreeca TV, such as the open market for video, and use independent and free charging systems to manage independent customer relationship management(CRM), self-branding, and content management. It will be possible to utilize mobile-based new media equipped with a system.

• Journal of the Korean Society of Radiology
• /
• v.17 no.6
• /
• pp.939-945
• /
• 2023

This study analyzes the 'performance efficiency' of AI-based reading assistance systems in the field of radiology by measuring their 'time behavior' properties. Due to the increase in medical images and the limited number of radiologists, the adoption of AI-based solutions is escalating, stimulating a multitude of studies in this area. Contrary to the majority of past research which centered on AI's diagnostic precision, this study underlines the significance of time behavior. Using 50 chest X-ray PA images, the system processed images in an average of 15.24 seconds, demonstrating high consistency and reliability, which is on par with leading global AI platforms, suggesting the potential for significant improvements in radiology workflow efficiency. We expect AI technology to play a large role in the field of radiology and help improve overall healthcare quality and efficiency.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.9
• /
• pp.317-322
• /
• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.5
• /
• pp.97-105
• /
• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Journal of Internet Computing and Services
• /
• v.24 no.1
• /
• pp.49-59
• /
• 2023

Recently, attention to the pandemic situation represented by COVID-19 emerged problems caused by unexpected shortage of medical personnel. In this paper, we present a method for diagnosing the presence or absence of lesional sign on PA chest X-ray images as computer vision solution to support diagnosis tasks. Method for visual anomaly detection based on feature modeling can be also applied to X-ray images. With extracting feature vectors from PA chest X-ray images and divide to patch unit, region-specific abnormality can be detected. As preliminary experiment, we created simulation data set containing multiple objects and present results of the comparative experiments in this paper. We present method to improve both efficiency and performance of the process through hard masking of patch features to aligned images. By summing up regional specificity and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to previous studies. By aggregating region-specific and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to our last study.

• The Journal of the Korea Contents Association
• /
• v.17 no.12
• /
• pp.281-288
• /
• 2017

Financial service commission notified that fingerprint information of their documents should be deleted till 2019 to the financial industry and the public institution. Business solutions for fingerprint detection and masking in document images are introduced. In this paper, a fingerprint information masking algorithm is proposed by using the multiple LBP features to extract fingerprint's intrinsic characteristics for artificial neural network decision whether the candidate is a true fingerprint or not after segmentation of versatile fingerprint candidates from a document image. The experimental results of the proposed fingerprint masking algorithm for 3,497 document images that are saved in a financial industry show that 96.4% of fingerprint information is masked, hence this fingerprint masking algorithm can be used efficiently in real fingerprint masking tasks.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.145-146
• /
• 2021

본 연구에서는 카메라의 촬영 시점에 의해서 발생되는 원근감이 광학 흐름 생성에 어떠한 영향을 주는지 살펴보고 광학 흐름 기반 이상행동 탐지 솔루션의 성능을 고도화하기 위해 기존 광학 흐름 영상으로부터 소실점 기반 가중치 행렬을 계산하여 원근감에 따른 광학 흐름 정도를 평활하는 기법에 대해서 연구한다. 카메라의 뷰포인트에 따라 원근감의 발생 정도나 객체의 크기 및 움직임의 정도가 달라지게 되며, 이는 원본 영상 프레임을 광학 흐름의 크기와 방향성으로 표현하는 영상 변환 네트워크를 가진 생성적 적대 신경망을 학습할 때 정상적인 행동 패턴의 범위를 결정짓는 데 방해가 될 수 있다. 이러한 문제를 해결하기 위하여 데이터셋의 배경으로부터 소실점을 추출하고 원근감에 따라 결정되는 광학 흐름의 크기를 평활하는 기법을 개발하여 기존 모델의 성능과 비교하였으며, 프레임 단위의 정확도 성능이 5.75% 향상된 것으로 확인되었다.