• Title/Summary/Keyword: 탑-뷰 변환

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Vision-based Walking Guidance System Using Top-view Transform and Beam-ray Model (탑-뷰 변환과 빔-레이 모델을 이용한 영상기반 보행 안내 시스템)

  • Lin, Qing;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.12
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    • pp.93-102
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    • 2011
  • This paper presents a walking guidance system for blind pedestrians in an outdoor environment using just one single camera. Unlike many existing travel-aid systems that rely on stereo-vision, the proposed system aims to get necessary information of the road environment by using just single camera fixed at the belly of the user. To achieve this goal, a top-view image of the road is used, on which obstacles are detected by first extracting local extreme points and then verified by the polar edge histogram. Meanwhile, user motion is estimated by using optical flow in an area close to the user. Based on these information extracted from image domain, an audio message generation scheme is proposed to deliver guidance instructions via synthetic voice to the blind user. Experiments with several sidewalk video-clips show that the proposed walking guidance system is able to provide useful guidance instructions under certain sidewalk environments.

Vision-based Food Shape Recognition and Its Positioning for Automated Production of Custom Cakes (주문형 케이크 제작 자동화를 위한 영상 기반 식품 모양 인식 및 측위)

  • Oh, Jang-Sub;Lee, Jaesung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.10
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    • pp.1280-1287
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    • 2020
  • This paper proposes a vision-based food recognition method for automated production of custom cakes. A small camera module mounted on a food art printer recognizes objects' shape and estimates their center points through image processing. Through the perspective transformation, the top-view image is obtained from the original image taken at an oblique position. The line and circular hough transformations are applied to recognize square and circular shapes respectively. In addition, the center of gravity of each figure are accurately detected in units of pixels. The test results show that the shape recognition rate is more than 98.75% under 180 ~ 250 lux of light and the positioning error rate is less than 0.87% under 50 ~ 120 lux. These values sufficiently meet the needs of the corresponding market. In addition, the processing delay is also less than 0.5 seconds per frame, so the proposed algorithm is suitable for commercial purpose.