• Title/Summary/Keyword: correction of rotated object

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Correction of Rotated Region in Medical Images Using SIFT Features (SIFT 특징을 이용한 의료 영상의 회전 영역 보정)

  • Kim, Ji-Hong;Jang, Ick-Hoon
    • Journal of Korea Multimedia Society
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    • v.18 no.1
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    • pp.17-24
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    • 2015
  • In this paper, a novel scheme for correcting rotated region in medical images using SIFT(Scale Invariant Feature Transform) algorithm is presented. Using the feature extraction function of SIFT, the rotation angle of rotated object in medical images is calculated as follows. First, keypoints of both reference and rotated medical images are extracted by SIFT. Second, the matching process is performed to the keypoints located at the predetermined ROI(Region Of Interest) at which objects are not cropped or added by rotating the image. Finally, degrees of matched keypoints are calculated and the rotation angle of the rotated object is determined by averaging the difference of the degrees. The simulation results show that the proposed scheme has excellent performance for correcting the rotated region in medical images.

Efficient Correction of a Rotated Object Using Radon Transform (라돈 변환을 이용한 회전된 물체의 효율적인 보정)

  • Cho, Bo-Ho;Jung, Sung-Hwan
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.3
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    • pp.291-295
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    • 2008
  • In this paper, we propose an input image reduction method to solve the problems of Radon transform which is a line structure analysis tool to correct a rotated object through a vision system. First we extract an object image removed background from the input image. Then we also select a reduced object image as a final input mage of Radon transform from the object image by considering slope. Finally we extract a rotated angle by using Radon transform with the final input image and correct the rotated object with the angle. In experimental results, we could improve the process time of about 64%, reduce the memory space of about 18% and make progress the line detection rate of about 18%.

Correction of Rotated Frames in Video Sequences Using Modified Mojette Transform (변형된 모젯 변환을 이용한 동영상에서의 회전 프레임 보정)

  • Kim, Ji-Hong
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.42-49
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    • 2013
  • The camera motion is accompanied with the translation and/or the rotation of objects in frames of a video sequence. An unnecessary rotation of objects declines the quality of the moving pictures and in addition is a primary cause of the viewers' fatigue. In this paper, a novel method for correcting rotated frames in video sequences is presented, where the modified Mojette transform is applied to the motion-compensated area in each frame. The Mojette transform is one of discrete Radon transforms, and is modified for correcting the rotated frames as follows. First, the bin values in the Mojette transform are determined by using pixels on the projection line and the interpolation of pixels adjacent to the line. Second, the bin values are calculated only at some area determined by the motion estimation between current and reference frames. Finally, only one bin at each projection is computed for reducing the amount of the calculation in the Mojette transform. Through the simulation carried out on various test video sequences, it is shown that the proposed scheme has good performance for correcting the rotation of frames in moving pictures.

Correction of Rotated Objects in Medical Images Using the Mojette Transform (모젯 변환을 이용한 의료 영상의 회전 물체 보정)

  • Jung, Hyang-Mi;Kim, Ji-Hong
    • Journal of Korea Multimedia Society
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    • v.15 no.11
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    • pp.1341-1348
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    • 2012
  • In this paper, an efficient scheme for correcting rotated objects in medical images using the Mojette transform is presented. The Mojette transform is a kind of discrete Radon transform, where the transform domain is represented by a set of projections. The Mojette transform currently studied in the image compression area is modified for detecting the rotation angle of objects in medical images. First, in order to find accurate rotation angle, the projection value in the Mojette transform is determined by using pixels on the projection line and in addition the linear interpolation of pixels adjacent to the line. Second, at each projection angle, only one projection is implemented for reducing the amount of the calculation in the process of the Mojette transform. Finally, the projection in the Mojette transform is carried out at the predetermined ROI(Region Of Interest) at which the objects are not cropped or added by rotating the image. The simulation results show that the proposed method has good performance for correcting the rotation angle in medical images.