• Title/Summary/Keyword: Optical feature

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Patent Document Similarity Based on Image Analysis Using the SIFT-Algorithm and OCR-Text

  • Park, Jeong Beom;Mandl, Thomas;Kim, Do Wan
    • International Journal of Contents
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    • v.13 no.4
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    • pp.70-79
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    • 2017
  • Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.

Video Expression Recognition Method Based on Spatiotemporal Recurrent Neural Network and Feature Fusion

  • Zhou, Xuan
    • Journal of Information Processing Systems
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    • v.17 no.2
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    • pp.337-351
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    • 2021
  • Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

Deep Learning based Visual-Inertial Drone Odomtery Estimation (딥러닝 기반 시각-관성을 활용한 드론 주행기록 추정)

  • Song, Seung-Yeon;Park, Sang-Won;Kim, Han-Gyul;Choi, Su-Han
    • Annual Conference of KIPS
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    • 2020.11a
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    • pp.842-845
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    • 2020
  • 본 연구는 시각-관성 기반의 딥러닝 학습으로 자유분방하게 움직이는 드론의 주행기록을 정확하게 추정하는 것을 목표로 한다. 드론의 비행주행은 드론의 온보드 센서와 조정값을 이용하는 것이 일반적이다. 본 연구에서는 이 온보드 센서 데이터를 학습에 사용하여 비행주행의 위치추정을 실험하였다. 선행연구로써 DeepVO[1]룰 구현하여 KITTI[3] 데이터와 Midair[4] 데이터를 비교, 분석하였다. 3D 좌표면에서의 위치 추정에 선행연구 모델의 한계가 있음을 확인하고 IMU를 Feature로써 사용하였다. 본 모델은 FlowNet[2]을 모방한 CNN 네트워크로부터 Optical Flow Feature에 IMU 데이터를 더해 RNN으로 학습을 진행하였다. 본 연구를 통해 주행기록 예측을 다소 정확히 했다고 할 수 없지만, IMU Feature를 통해 주행기록의 예측이 가능함을 볼 수 있었다. 본 연구를 통해 시각-관성 분야에서 사람의 지식이나 조정이 들어가는 센서를 융합하는 기존의 방식에서 사람의 제어가 들어가지 않는 End-to-End 방식으로 인공지능을 학습했다. 또한, 시각과 관성 데이터를 통해 주행기록을 추정할 수 있었고 시각적으로 그래프를 그려 정답과 얼마나 차이 있는지 확인해보았다.

Two dimensional tin sulfide for photoelectric device

  • Patel, Malkeshkumar;Kim, Joondong
    • Proceedings of the Korean Vacuum Society Conference
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    • 2016.02a
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    • pp.389.1-389.1
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    • 2016
  • The flexible solid state device has been widely studied as portable and wearable device applications such as display, sensor and curved circuits. A zero-bias operation without any external power consumption is a highly-demanding feature of semiconductor devices, including optical communication, environment monitoring and digital imaging applications. Moreover, the flexibility of device would give the degree of freedom of transparent electronics. Functional and transparent abrupt p/n junction device has been realized by combining of p-type NiO and n-type ZnO metal oxide semiconductors. The use of a plastic polyethylene terephthalate (PET) film substrate spontaneously allows the flexible feature of the devices. The functional design of p-NiO/n-ZnO metal oxide device provides a high rectifying ratio of 189 to ensure the quality junction quality. This all transparent metal oxide device can be operated without external power supply. The flexible p-NiO/n-ZnO device exhibit substantial photodetection performances of quick response time of $68{\mu}s$. We may suggest an efficient design scheme of flexible and functional metal oxide-based transparent electronics.

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A Study on Seam Tracking and Weld Defects Detecting for Automated Pipe Welding by Using Double Vision Sensors (파이프 용접에서 다중 시각센서를 이용한 용접선 추적 및 용접결함 측정에 관한 연구)

  • 송형진;이승기;강윤희;나석주
    • Journal of Welding and Joining
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    • v.21 no.1
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    • pp.60-65
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    • 2003
  • At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

Handled in real-time tracking of moving object occlusion (가림현상에 대처한 실시간 이동 물체 추적)

  • Kim, Hag-Hee;Yun, Han-Kyung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.3
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    • pp.158-166
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    • 2011
  • Generally, moving object tracking used Lucas-Kanade feature tracking method which is strong in movement, rotation and size. But this method is very weak of occlusion by background or another object and so on. In this case, this method tracks backgrounds or another objects instead a moving object, or a tracking is finished. In order to solve this problem, we proposes Lucas-Kanade feature tracking method which introduce a destimation function and prediction function.

Sub-pixel Multiplexing for Autostereoscopic Full Parallax 3D (무안경 완전시차 입체 재현을 위한 서브픽셀 다중화)

  • Eum, Homin;Lee, Gwangsoon
    • Journal of Korea Multimedia Society
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    • v.20 no.12
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    • pp.2009-2015
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    • 2017
  • A two-dimensional lens is required to reproduce both the horizontal and vertical parallax through an autostereoscopic 3D display. Among the two-dimensional lenses, a hexagonal micro lens array (MLA) having good optical efficiency is mainly used. However, the hexagonal MLA has complex geometric features. The first feature is that the lens cells are zigzagged in the vertical direction, which should be reflected in the view number calculation for each sub-pixel. The second feature is that the four sides of a hexagonal lens cell are tilted, requiring a more careful view index assignment to the lens cell. In this paper, we propose a sub-pixel multiplexing scheme suitable for the features of the hexagonal MLA. We also propose a view-overlay algorithm based on a two-dimensional lens and compare subjective image quality with existing view-selection through autostereoscopic 3D display implementation.

PC Based Drawing Using Wii Remote (Wii Remote를 이용한 PC 기반 드로잉)

  • Oh, eun-byeol;Ryoo, seung-taek
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.70-73
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    • 2009
  • Wii Remote is the primary controller for Nintendo's Wii console. A main feature of the Wii Remote is its motion sensing capability, which allows the user to interact with and manipulate items on screen via movement and pointing through the use of accelerometer and optical sensor technology. Another feature is its expandability through the use of Bluetooth. In this Study, use of motion sensors and Bluetooth capabilities. The user holding the remote on the screen, pointing to receive information about the values of the coordinates on the screen indicating the drawing of the implementation.

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REGISTRATION OF MICROSCOPIC SECTION IMAGES BASED ON A RADIAL DISTORTION MODEL

  • Lee, Hoo-Sung;Yun, Il-Dong;Kim, Dong-Sik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.303-306
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    • 2009
  • Registration of microscopic section images from an organism is of importance in analyzing and understanding the function of an organism. Microscopes usually suffer from the radial distortion due to the spherical aberration. In this paper, a correction scheme for the intra-section registration is proposed. The correction scheme uses two corresponding feature points under the radial distortion model. Proposing several variations of the proposed scheme, we extensively conducted experiments for real microscopic images. Iterative versions of the correction from multiple feature points provide good performance for the registration of the optical and scanning electron microscopic images.

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Computer Vision System for Automatic Grading of Ginseng - Development of Image Processing Algorithms - (인삼선별의 자동화를 위한 컴퓨터 시각장치 - 등급 자동판정을 위한 영상처리 알고리즘 개발 -)

  • 김철수;이중용
    • Journal of Biosystems Engineering
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    • v.22 no.2
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    • pp.227-236
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    • 1997
  • Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

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