• 제목/요약/키워드: Extreme Contour Point

검색결과 2건 처리시간 0.015초

고해상 영상의 회전된 각도를 검출하기 위한 Extreme Contour Point 알고리즘의 FPGA 설계 (FPGA Implementation of Extreme Contour Point Algorithm to detect rotated angle of High Definition Image)

  • 정민우;박찬수;김희석
    • 전기전자학회논문지
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    • 제20권4호
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    • pp.344-350
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    • 2016
  • 본 논문에서는 움직이는 영상에 대해 물리적인 회전이 발생하였을 때, 빠른 보정을 처리하기 위해 회전된 영상의 회전 각도를 고속으로 처리하기 위한 ECP (Extreme Contour Point) 알고리즘의 FPGA (Field Programmable Gate Array) 하드웨어 설계를 최적화하였고, XC7Z020 xc7z020-3clg400 FPGA 보드와 xilinx 14.2 툴을 사용하여 검증하였다. 잘 알려진 각도 산출 알고리즘인 CORDIC (Coordinate Rotation Digital Integrated Computation)과 비교하여 4ns의 유사한 동작 속도 안에서 CORDIC 대비 Registers는 108%, Look Up Tables (LUTs)는 91% 감소하는 등 하드웨어 비용이 우수함을 확인하였다.

A Novel Implementation of Rotation Detection Algorithm using a Polar Representation of Extreme Contour Point based on Sobel Edge

  • Han, Dong-Seok;Kim, Hi-Seok
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제16권6호
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    • pp.800-807
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    • 2016
  • We propose a fast algorithm using Extreme Contour Point (ECP) to detect the angle of rotated images, is implemented by rotation feature of one covered frame image that can be applied to correct the rotated images like in image processing for real time applications, while CORDIC is inefficient to calculate various points like high definition image since it is only possible to detect rotated angle between one point and the other point. The two advantages of this algorithm, namely compatibility to images in preprocessing by using Sobel edge process for pattern recognition. While the other one is its simplicity for rotated angle detection with cyclic shift of two $1{\times}n$ matrix set without complexity in calculation compared with CORDIC algorithm. In ECP, the edge features of the sample image of gray scale were determined using the Sobel Edge Process. Then, it was subjected to binary code conversion of 0 or 1 with circular boundary to constitute the rotation in invariant conditions. The results were extracted to extreme points of the binary image. Its components expressed not just only the features of angle ${\theta}$ but also the square of radius $r^2$ from the origin of the image. The detected angle of this algorithm is limited only to an angle below 10 degrees but it is appropriate for real time application because it can process a 200 degree with an assumption 20 frames per second. ECP algorithm has an O ($n^2$) in Big O notation that improves the execution time about 7 times the performance if CORDIC algorithm is used.