• Journal of Information Processing Systems
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• 제13권6호
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• pp.1431-1435
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• 2017

• 한국멀티미디어학회논문지
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• 제19권12호
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• pp.1936-1942
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• 2016

This paper presents a mobile color-compensating application using a RGB color compensation algorithm. The proposed application enables color vision deficiencies to differentiate images which cannot be distinguished by them. The suggested mobile application has two functions: converting images taken by camera and converting contents in the device screen. The proposed application is computationally inexpensive, since it does not require color space transformation. Simulation results show that the proposed application enables color vision deficiencies to receive information expressed by colors such as subway line maps.

• 센서학회지
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• 제12권6호
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• pp.231-240
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• 2003

고해상도의 윤곽검출 시각칩을 제작하기 위해 윤곽검출 회로의 수를 증가시킬 경우 소비전력 문제 및 회로를 탑재할 칩의 크기를 고려하지 않으면 안된다. 칩을 구성하는 단위회로의 수적 증가는 소비전력의 증가와 더불어 대면적을 요구하게 된다. 소비전력의 증가와 CMOS 생산 회사에서 제공하는 칩의 크기가 수 십 $mm^2$이라는 조건은 결국 단위회로의 수적 증가를 제한하게 된다. 따라서 본 연구에서는, 고해상도의 윤곽검출 시각칩 구현을 위한 윤곽검출 회고의 수적 증가에 따른 전력소비의 최소화 방법으로 전자스위치(electronic switch)가 내장된 윤곽검출 회로를 제안하고, 제한된 칩의 면적에 더 많은 윤곽검출 회로를 넣기 위해 시세포 역할의 광검출 회로와 윤곽검출 회로를 분리하여 구성하는 방법을 적용하였다. $128{\times}128$ 해상도를 갖는 광검출 회고가 $1{\times}128$의 윤곽검출 회고를 공유하여 동일한 칩 면적에 향상된 해상도를 갖는 칩을 설계하였다. 설계된 칩의 크기는 $4mm{\times}4mm$이고, 소비전력은 SPICE 모의실험을 통해 약 20mW가 됨을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.211-212
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• 2008

본 논문에서는 LCD 구동 모들 PCB의 기능 검사를 위한 자동 검사시스템인 EVT(Emulated Vision Tester)를 제안하고 구현하였다. 기존의 대표적인 자동검사 방법으로는 전기적 검사나 영상기반 검사방식이 있으나 전기적 검사만으로는 Timing이 주요한 변수가 되는 LED 장비에서는 검출할 수 없는 구동불량이 존재하며 영상기반 검사는 영상획득에 일관성이 결여되거나 Gray Scale의 구분이 불명확하며 검출결과의 재현성이 떨어진다. EVT 시스템은 Pattern Generator에서 인가된 입력 패턴 신호라 구동모듈을 통한 후 출력되는 디지털 신호를 직접 비교하여 패턴을 검사하고 아날로그 신호 (전압, 저항, 파형)의 이상 여부도 신속 정확하게 검사할 수 있는 H/W적인 방법이다. 높은 검출 신뢰도와 빠른 처리 속도 뿐만 아니라 간결한 시스템 구성으로 원가절감 실현 등 많은 장점을 가진다.

• Smart Structures and Systems
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• 제23권4호
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.776-779
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• 1987

This paper describes a technique for measuring the volume of a pile of powder in a visual way. The volume of a fragile object whose shape is easily transformed by a slight touch of another object must be measured without any contact with it. This can be achieved by applying a three-dimensional shape reconstruction technique employed in computer vision. We have developed a measurement system that finds the volume of a pile of powder by employing a range finder, and performed an experiment of determining the volume of PVC powder piled on a table. The result of the experiment was satisfactory.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.63-66
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• 2021

The technological advancement in computer vision has made system like grab-and-go grocery a reality. Now all the shoppers have to do now is to walk in grab the items and go out without having to wait in the long queues. This paper presents an intelligent retail environment system that is capable of monitoring and tracking customer's activity during shopping based on their interaction with the shelf. It aims to develop a system that is low cost, easy to mount and exhibit adequate performance in real environment.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.261-266
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• 2021

The spread of cloud computing, digital computing, and the popular social media platforms have led to increased growth of data. That growth of data results in what is known as big data (BD), which seen as one of the most strategic resources. The analysis of these BD has allowed generating value from massive raw data that helps in making effective decisions and providing quality of service. With Vision 2030, Saudi Arabia seeks to invest in BD technologies, but many challenges and barriers have led to delays in adopting BD. This research paper aims to search in the state of Big Data Analytics (BDA) in Saudi higher education sector, identify the barriers by reviewing the literature, and then to apply the design-reality gap model to assess these barriers that prevent effective use of big data and highlights priority areas for action to accelerate the application of BD to comply with Vision 2030.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

• Smart Structures and Systems
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• 제34권2호
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• pp.117-127
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• 2024

A novel approach that the smart control of robotics can be realized by a fuzzy controller and an appropriate Runge-Kutta scheme in this paper. A recently proposed integral inequality is selected based on the free weight matrix, and the less conservative stability criterion is given in the form of linear matrix inequalities (LMIs). We demonstrate that this target information obtained through image processing is subjected to smart control with computer-vision robotic to Arduino, and the infrared beacon was utilized for the operation of practical illustrations. A fuzzy controller derived with a fuzzy Runge-Kutta type functions is injected into the system and then the system is stabilized asymptotically. In this study, a fuzzy controller and a fuzzy observer are proposed via the parallel distributed compensation technique to stabilize the system. This paper achieves the goal of real-time following of three vehicles and there are many areas where improvements were made. Finally, each information is transmitted to Arduino via I2C to follow the self-propelled vehicle. The proposed calculation is approved in reproductions and ongoing smart control tests.