• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1663-1670
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• 2014

Recently, lots of research works have been actively focused on the DVC (Distributed Video Coding) techniques which provide a theoretical basis for the implementation of light video encoder. However, most of these studies have showed poorer performances than the conventional standard video coding schemes such as MPEG-1/2, MPEG-4, H.264 etc. In order to overcome the performance limits of the conventional approaches, several channel-divided distributed video coding schemes have been designed in such a way that some information are obtained while generating side information at decoder side and then these are provided to the encoder side, resulting in channel-divided video coding scheme. In this paper, the interpolation scheme by weighted sum of multiple motion-compensated interpolation frames is introduced and a new channel-divided DVC scheme is designed to effectively describe noisy channels based on the motion vector and its matching characteristics. Through several simulations, it is shown that the proposed method performs better than the conventional methods at low bit-rate and keeps the reconstructed visual quality constantly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.67-75
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• 2024

Crosswalks play an important role for the safe movement of pedestrians in a complex urban environment. However, for the visually impaired, crosswalks can be a big risk factor. Although assistive tools such as braille blocks and acoustic traffic lights exist for safe walking, poor management can sometimes act as a hindrance to safety. This paper proposes a method to improve accuracy in a deep learning-based real-time crosswalk detection model that can be used in applications for pedestrian assistance for the disabled at the beginning. The image was binarized by utilizing the characteristic that the white line of the crosswalk image contrasts with the road surface, and through this, the crosswalk could be better recognized and the location of the crosswalk could be more accurately identified by using two models that learned the whole and the middle part of the crosswalk, respectively. In addition, it was intended to increase accuracy by creating a boundary box that recognizes crosswalks in two stages: whole and part. Through this method, additional frames that the detection model did not detect in RGB image learning from the crosswalk image could be detected.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.61-70
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• 2020

In this study, the IOT-based desk layout method was proposed to complement the existing seating method and to improve the work efficiency. The IoT system for the desk layout needs determining the function, type and network protocol of the sensor to find out the working status of the desk to reasonably assist the worker's seat placement. A collection method was proposed. The algorithm used in Block Stacking was used when deciding how to allocate seats using the acquired data. As a result, we could suggest an arithmetic basis for rational desk layout in IoT environment and show that it can be applied to an advanced flexible seating system based on working type in addition to the preferences of employees in the future.

• Journal of KIISE
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• v.42 no.6
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• pp.691-698
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• 2015

Application launch time is an important performance metric to user experience in desktop and laptop environment, which mostly depends on the performance of secondary storage. Application launch times can be reduced by utilizing solid-state drive (SSD) instead of hard disk drive (HDD). However, considering a cost-performance trade-off, utilizing SSDs as caches for slow HDDs is a practicable alternative in reducing the application launch times. We propose a new SSD caching scheme which migrates data blocks from HDDs to SSDs. Our scheme operates entirely in the file system level and does not require an extra layer for mapping SSD-cached data that is essential in most other schemes. In particular, our scheme does not incur mapping overheads that cause significant burdens on the main memory, CPU, and SSD space for mapping table. Experimental results conducted with 8 popular applications demonstrate our scheme yields 56% of performance gain in application launch, when data blocks along with metadata are migrated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.39-47
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• 2014

In this study, the epipolar images were created by both methods of resolution adjustment and piecewise approach using RPC(Rational Polynomial coefficients) and ancillary data of IKONOS-2 and SPOT-5 satellite images whose resolutions are different from each other. The stereo geometry of these two satellite images was analyzed and the RPC block modelling was accomplished for generating epipolar images. In order to evaluate the accuracy of created epipolar images, the y-parallaxes were analyzed for the specific points which were apparently identified in mountainous, plain and urban area. Also the RMSEs of the specific points were calculated using the coordinates from the epipolar stereo images and the coordinates from the block triangulation. Y-parallaxes were within one pixel and the RMSEs were within two meters for X, Y and Z each.

• Convergence Security Journal
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• v.12 no.4
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• pp.85-90
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• 2012

DES is a 64-bit binary, and each block is divided into units of time are encrypted through an encryption algorithm. The same key as the symmetric algorithm for encryption and decryption algorithms are used. Conversely, when decryption keys, and some differences may apply. The key length of 64 bits are represented by two ten thousand an d two 56-bit is actually being used as the key remaining 8 bits are used as parity check bits. The 64-bit block and 56-bit encryption key that is based on a total of 16 times 16 modifier and spread through the chaos is completed. DES algorithm was chosen on the strength of the password is questionable because the most widely available commercially, but has been used. In addition to the basic DES algorithm adopted in the future in the field by a considerable period are expected to continue to take advantage of the DES algorithm effectively measures are expected to be in the field note.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.11-20
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• 2019

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.217-222
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• 1994

한글 글꼴을 새롭게 만들려면 지금까지는 기본 글자인 자소를 디자인하든지 아니면 완성된 글자 전체를 디자인해야 했다. 조합형의 글자디자인의 경우, 전체 글자가 아니라 부분적인 한글 전자사전은 많은 양의 데이타를 저장할 수 있어야 하며, 빠른 검색 속도를 제공해야 한다. 기존의 트라이는 공통접두사만을 압축하기 때문에 사전의 크기가 방대하다는 단점이 있다. 본 논문에서는 DAWG(Directed Acyclic Word Graph)를 이용하여 공통접미사까지 압축하였고, 검색과 기억장소의 효율을 위하여, 링크드리스트 구조의 DAWG를 유형별 배열 구조로 바꾸었다. 전국의 각 학교 이름들을 대상으로 실험한 결과, 본 논문에서 제안한 DAWG를 이용한 배열 구조의 사전은 트라이와 비교하여 볼 때, 검색 연산의 성능은 동일하게 유지하면서 기억 장소의 효율과 압축율에서 효과적이었다. 또한, 트라이보다 주기억장치와 보조기억장치와의 블록 입출력횟수를 줄임으로써 전체 검색 시간을 낮출 수 있었다.소를 디자인하기 때문에 전체 글자의 모양이 좋지 않다는 단점이 있었고 완성형의 경우 완성된 글자 전체를 모두 디자인해야하는 단점이 있었다. 본 논문에서는 한글 글꼴 개발의 한 방법으로 제한된 글자의 디자인에 의한 전체 글꼴 생성에 관한 한 방법을 제시한다. 이 방법은 표준으로 설정된 몇 글자를 디자인하면 그 글자를 분석하여 자소들을 위한 글꼴 화일이 만들어지고 자소 글꼴 화일로부터 다른 모든 글자를 만들어 낸다.