• Title/Summary/Keyword: vision-based technology

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Autofocus of Infinity-Corrected Optical Microscopes by Confocal Principle and Fiber Source Modulation Technique (공초점 원리와 광섬유 광원 변조를 이용한 무한보정 현미경 자동초점)

  • Park, Jung-Jae;Kim, Seung-Woo;Lee, Ho-Jae
    • Korean Journal of Optics and Photonics
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    • v.15 no.6
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    • pp.583-590
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    • 2004
  • The autofocus is one of the important processes in the automated vision inspection or measurements using optical microscopes, because it influences the measuring accuracy. In this paper, we used the confocal microscope configuration based on not a pinhole but a single-mode optical fiber. A single mode fiber has the functions of source and detector by applying the reciprocal scheme. As a result, we acquired a simple system configuration and easy alignment of the optical axis. Also, we embodied a fast autofocus system by acquiring the focus error signal through a source modulation technique. The source modulation technique can effectively reduce physical disturbances compared with objective lens modulation, and it is easily applicable to general optical microscopes. The focus error signal was measured with respect to the modulation amplitude, reflectance of the specimen and inclination angle of the measuring surface. The performance of the proposed autofocus system was verified through autofocusing flat mirror surface. In addition, we confirmed that source modulation rarely degrades the depth resolution by the comparison between the FWHMs of axial response curves.

A Study on Performance for Camouflage of Domestic and Foreign Combat Uniforms (국내·외 전투복의 카무플라주(Camouflage) 성능 연구)

  • Kang, Jinwoo;Lee, Minhee;Hong, Seongdon;Moon, Sunjeong
    • Journal of the Korean Society of Clothing and Textiles
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    • v.40 no.6
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    • pp.1025-1033
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    • 2016
  • It is important to compare and analyze digital camouflage from different countries to promote the continuous development of a camouflage combat uniform. This effort should lead to developing a camouflage pattern suitable for the domestic environment and expand its performance of night camouflage. This study investigates digital camouflage by comparing camouflage fabrics sampled from Korea and eight other countries (USA, UK, Singapore, Croatia, Colombia, and Mongolia) in terms of textile, near-infrared reflectivity of colors, and color distribution. First, the fabric construction of camouflage from Korea, UK, US, Singapore, Span, and Croatia were all characterized by derivative plain weaves, while derivative twill weaves were generally used in Croatia and Mongolia. It is assumed that derivative plain weaves are adopted to improve the tearing strength of fine yarns. However, twill weaves enhance the flexibility of coarse yarn fabrics. Next, reflectivity change was analyzed based on camouflage color. The reflectivity of a combat uniform in Korea, Colombia, Croatia, and UK increased before 780nm in the visible light range, but remained consistent from 800nm which falls under the near-infrared range. In contrast, camouflage samples in Mongolia, Span, Singapore and USA showed a gradual increase of reflectivity in the near-infrared range. Finally, the color distribution analysis of digital camouflage found that camouflage of countries with desert or woodland combat settings dominantly contained brown colors. It indicates the color pattern consideration of different geographic regions is important to determine camouflage performance. This research involves basic study that will have implications for developing patterns and colors suitable for the South Korean environment and expand its use as night camouflage that helps achieve continuous improved camouflage performance.

Deep learning based symbol recognition for the visually impaired (시각장애인을 위한 딥러닝기반 심볼인식)

  • Park, Sangheon;Jeon, Taejae;Kim, Sanghyuk;Lee, Sangyoun;Kim, Juwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.3
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    • pp.249-256
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    • 2016
  • Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.

A medium of Art as the Relational Circuit: Paul Ryan's Video Art (관계적 회로로서의 예술 미디어: 폴 라이언의 비디오아트)

  • Lim, Shan
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.3
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    • pp.101-106
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    • 2019
  • This paper considers the historicity and aesthetical implications of in the art world of Paul Ryan(1943-2013) who designed the aestheticization of relational circuit of society by realizing the value of social transformation being inherent in video with cultural practices and suggesting the interdisciplinary method of leaning and research in the early video art history. To do this, in Chapter II, I review the first artwork presented firstly in the art gallery exhibition "TV as a Creative Medium" in 1969, in which Ryan proposed a video medium as a communication system and experimented the concept of 'feedback' in Cybernetics. And Chapter III focuses Ryan's discursive activities contributed to magazine Radical Software and artist-collective Raindance Corporation with growing interest in communication technology. At this time, Ryan regarded video medium as the tool for cybernetic expansion. Finally Chapter IV deals with the development of ecological method based on "a shared perception of environmental realities" and verifies Ryan's vision that video medium would be most effective means of social change and communication.

Key Frame Detection Using Contrastive Learning (대조적 학습을 활용한 주요 프레임 검출 방법)

  • Kyoungtae, Park;Wonjun, Kim;Ryong, Lee;Rae-young, Lee;Myung-Seok, Choi
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.897-905
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    • 2022
  • Research for video key frame detection has been actively conducted in the fields of computer vision. Recently with the advances on deep learning techniques, performance of key frame detection has been improved, but the various type of video content and complicated background are still a problem for efficient learning. In this paper, we propose a novel method for key frame detection, witch utilizes contrastive learning and memory bank module. The proposed method trains the feature extracting network based on the difference between neighboring frames and frames from separate videos. Founded on the contrastive learning, the method saves and updates key frames in the memory bank, witch efficiently reduce redundancy from the video. Experimental results on video dataset show the effectiveness of the proposed method for key frame detection.

Implementation of A Thin Film Hydroponic Cultivation System Using HMI

  • Gyu-Seok Lee;Tae-Sung Kim;Myeong-Chul Park
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.4
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    • pp.55-62
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    • 2024
  • In this paper, we propose a thin-film hydroponic plant cultivator using HMI display and IoT technology. Existing plant cultivators were difficult to manage due to soil-based cultivation, and it was difficult to optimize environmental conditions due to the open cultivation environment. In addition, there are problems with plant cultivation as immediate control is difficult and growth of plants is delayed. To solve this problem, a cultivation environment was established by connecting the MCU and sensors, and the environment information could be checked and quickly controlled by linking with the HMI display. Additionally, a case was applied to minimize changes in environmental information. Implementation of a thin-film hydroponic cultivation system made soil management easier, improved functionality through operation and control, and made it easy to understand environmental information through the display. The effectiveness of rapid growth was confirmed through crop cultivation experiments in existing growers and hydroponic growers. Future research directions will include optimizing growth information by transmitting and storing cultivation environment information and linking and comparing growth information using vision cameras. It is expected that this will enable efficient and stable plant cultivation.

Investigating Smart TV Gesture Interaction Based on Gesture Types and Styles

  • Ahn, Junyoung;Kim, Kyungdoh
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.2
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    • pp.109-121
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    • 2017
  • Objective: This study aims to find suitable types and styles for gesture interaction as remote control on smart TVs. Background: Smart TV is being developed rapidly in the world, and gesture interaction has a wide range of research areas, especially based on vision techniques. However, most studies are focused on the gesture recognition technology. Also, not many previous studies of gestures types and styles on smart TVs were carried out. Therefore, it is necessary to check what users prefer in terms of gesture types and styles for each operation command. Method: We conducted an experiment to extract the target user manipulation commands required for smart TVs and select the corresponding gestures. To do this, we looked at gesture styles people use for every operation command, and checked whether there are any gesture styles they prefer over others. Through these results, this study was carried out with a process selecting smart TV operation commands and gestures. Results: Eighteen TV commands have been used in this study. With agreement level as a basis, we compared the six types of gestures and five styles of gestures for each command. As for gesture type, participants generally preferred a gesture of Path-Moving type. In the case of Pan and Scroll commands, the highest agreement level (1.00) of 18 commands was shown. As for gesture styles, the participants preferred a manipulative style in 11 commands (Next, Previous, Volume up, Volume down, Play, Stop, Zoom in, Zoom out, Pan, Rotate, Scroll). Conclusion: By conducting an analysis on user-preferred gestures, nine gesture commands are proposed for gesture control on smart TVs. Most participants preferred Path-Moving type and Manipulative style gestures based on the actual operations. Application: The results can be applied to a more advanced form of the gestures in the 3D environment, such as a study on VR. The method used in this study will be utilized in various domains.

Implementation of Hand-Gesture-Based Augmented Reality Interface on Mobile Phone (휴대폰 상에서의 손동작 기반 증강현실 인터페이스 구현)

  • Choi, Jun-Yeong;Park, Han-Hoon;Park, Jung-Sik;Park, Jong-Il
    • Journal of Broadcast Engineering
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    • v.16 no.6
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    • pp.941-950
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    • 2011
  • With the recent advance in the performance of mobile phones, many effective interfaces for them have been proposed. This paper implements a hand-gesture-and-vision-based interface on a mobile phone. This paper assumes natural interaction scenario when user holds a mobile phone in a hand and sees the other hand's palm through mobile phone's camera. Then, a virtual object is rendered on his/her palm and reacts to hand and finger movements. Since the implemented interface is based on hand familiar to humans and does not require any additional sensors or markers, user freely interacts with the virtual object anytime and anywhere without any training. The implemented interface worked at 5 fps on mobile phone (Galaxy S2 having a dual-core processor).

Analysis of Issues Related to Artificial Intelligence Based on Topic Modeling (토픽모델링을 활용한 인공지능 관련 이슈 분석)

  • Noh, Seol-Hyun
    • Journal of Digital Convergence
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    • v.18 no.5
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    • pp.75-87
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    • 2020
  • The present study determined new value that can be created through the convergence between artificial intelligence technology (AIT) and all industries by deriving and thoroughly analyzing major issues related to artificial intelligence (AI). This study analyzes domestic articles related to AI using topic modeling method based on LDA algorithm. Keywords were extracted from 3,889 articles of eleven metropolitan newspapers, eight business newspapers and major broadcasting companies; articles were selected by searching for the keyword "artificial intelligence". Keywords were extracted by optimizing the relevance parameter λ to improve the measure of pointwise mutual information (PMI), which shows the association among the keywords of each topic, and topic names were inferred from keywords based on valid evidence. The extracted topics widely showed changes occurring throughout society, economy, industries, culture, and the support policy and vision of the government.

Automatic Recognition of the Front/Back Sides and Stalk States for Mushrooms(Lentinus Edodes L.) (버섯 전후면과 꼭지부 상태의 자동 인식)

  • Hwang, H.;Lee, C.H.
    • Journal of Biosystems Engineering
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    • v.19 no.2
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    • pp.124-137
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    • 1994
  • Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

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