• Title/Summary/Keyword: 고해상도 카메라

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Fast Human Detection Algorithm for High-Resolution CCTV Camera (고해상도 CCTV 카메라를 위한 빠른 사람 검출 알고리즘)

  • Park, In-Cheol
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.8
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    • pp.5263-5268
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    • 2014
  • This paper suggests a fast human detection algorithm that can be applied to a high-resolution CCTV camera. Human detection algorithms, which used a HOG detector show high performance in the region of image processing. On the other hand, it is difficult to apply to real-time high resolution imaging because of its slow processing speed in the extracting figures of HOG. To resolve this problems, we suggest how to detect humans into two stages. First, candidates of a human region are found using background subtraction, and humans and non-humans are distinguished using a HOG detector only. This process increases the detection speed by approximately 2.5 times without any degradation in performance.

A Robust Depth Map Upsampling Against Camera Calibration Errors (카메라 보정 오류에 강건한 깊이맵 업샘플링 기술)

  • Kim, Jae-Kwang;Lee, Jae-Ho;Kim, Chang-Ick
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.6
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    • pp.8-17
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    • 2011
  • Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

The comparative algorithm of the design data in the photomask inspection machine with high resolution (Photomask 고해상도 검사기에서 설계 데이터 비교 알고리즘)

  • Kim, Hoi-Sub;Oh, Chang-Seog;Ahn, Tae-Wan
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.10 no.1
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    • pp.1-9
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    • 2006
  • Three categories such as the design of a machine, control and software are necessary in the development of the photomask inspection machine with high resolution. Among them, the design of a software detects inferiority through the comparison of CAD data and real data read by camera from photomask. The block matching algorithm is used since the domain is large and the comparison of data by pixel is accomplished. To correct the error arising from the assembly of a machine, calibration algorithm is used and prefocusing algorithm is suggested to correct the surface of the photomask.

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Bomb Impact Point Location Acquisition by Image Transformation using High-Resolution Commercial Camera (고해상도 상용카메라를 사용하는 영상변환을 이용한 탄착점 좌표획득)

  • Park, Sang-Jae;Ha, Seok-Wun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.6 no.1
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    • pp.1-7
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    • 2011
  • In the bomb impact test, to acquire the bomb impact point location the high-priced embedded equipments such as the Bomb Scoring System or the EOTS are needed. Recently, a high-resolution image processing could be possible since the resolution of the commercial camera is growing rapidly. In this paper we first propose an image transformation method for acquiring the real bomb impact image using a high-resolution commercial camera, and then present the process calculating the real bomb impact point location coordinate from the transformed image. Based on the experimental results we found the possibilities that the real bomb impact point information could be effectively earned just using the commercial camera.

A Development of Interactive Tabletop Display System Using Infrared Camera based Tangible Interface (적외선 카메라 기반의 탠저블 인터페이스를 활용한 인터랙티브 테이블탑 디스플레이 시스템 개발)

  • Kim, Minyoung;Park, Kyoung Shin;Cho, Yongjoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.238-241
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    • 2009
  • 정보 과학 기술의 발전과 생활 수준의 향상이 가속화되면서 주변 환경을 구성하는 가구나 공간조차도 정보 통신과 컴퓨터 기능이 내재된 인간과 상호작용할 수 있는 개념으로 확장되고 있다. 또한 비즈니스의 규모가 방대해지면서 협업이 필요성이 증가되는 가운데 단일 사용자에게 맞춰진 표준 데스크탑을 대체할 새로운 기기와 인터페이스에 대한 요구가 증가하고 있다. 본 연구에서는 이런 패러다임에 맞춰 선호되고 있는 테이블탑 컴퓨팅을 다수의 LCD와 PC를 포함하는 분산 하드웨어 방식의 고해상도 대형 디스플레이로 구성하고, 다중 사용자의 입력을 동시적으로 처리할 수 있는 적외선 카메라를 활용한 마커 인식 기반의 탠저블 인터페이스를 개발하였다. 그리고 이 시스템에서 동작하는 고해상도 이미지 뷰어와 퍼베이스브 블록 격파 게임 응용프로그램을 구현하였다.

A Study on the Restoration of a Low-Resoltuion Iris Image into a High-Resolution One Based on Multiple Multi-Layered Perceptrons (다중 다층 퍼셉트론을 이용한 저해상도 홍채 영상의 고해상도 복원 연구)

  • Shin, Kwang-Yong;Kang, Byung-Jun;Park, Kang-Ryoung;Shin, Jae-Ho
    • Journal of Korea Multimedia Society
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    • v.13 no.3
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    • pp.438-456
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    • 2010
  • Iris recognition uses a unique iris pattern of user to identify person. In order to enhance the performance of iris recognition, it is reported that the diameter of iris region should be greater than 200 pixels in the captured iris image. So, the previous iris system used zoom lens camera, which can increase the size and cost of system. To overcome these problems, we propose a new method of enhancing the accuracy of iris recognition on low-resolution iris images which are captured without a zoom lens. This research is novel in the following two ways compared to previous works. First, this research is the first one to analyze the performance degradation of iris recognition according to the decrease of the image resolution by excluding other factors such as image blurring and the occlusion of eyelid and eyelash. Second, in order to restore a high-resolution iris image from single low-resolution one, we propose a new method based on multiple multi-layered perceptrons (MLPs) which are trained according to the edge direction of iris patterns. From that, the accuracy of iris recognition with the restored images was much enhanced. Experimental results showed that when the iris images down-sampled by 6% compared to the original image were restored into the high resolution ones by using the proposed method, the EER of iris recognition was reduced as much as 0.133% (1.485% - 1.352%) in comparison with that by using bi-linear interpolation