• Title/Summary/Keyword: image stitching

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Luminance-adaptive Image Stitching by Using Deep learning based Feature Detection and Matching (딥러닝 기반 특징점 추출 및 매칭 기술을 활용한 밝기 적응형 영상 스티칭)

  • Kim, Minyoung;Kim, Geonho;Lee, Minseok;Rhee, Seongbae;Kim, Kyuhyeon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.847-850
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    • 2022
  • 최근 가상 현실(Virtual Reality), 파노라마(Panorama) 영상 등에 관한 관심과 수요가 증가함에 따라 고해상도 영상을 얻기 위한 영상 스티칭(Image Stitching)에 관한 연구가 활발하게 진행되고 있다. 영상 스티칭은 다수의 영상을 하나의 영상으로 합성해 카메라의 좁은 시야각 문제를 해결함으로써 사용자에게 몰입감과 현장감을 제공할 수 있는 기술이다. 영상 스티칭에 있어 특징점 추출 및 매칭 과정의 정확도는 스티칭 영상의 품질을 결정짓는 핵심적인 요소이지만, 기존의 특징점 추출 및 매칭 방법은 밝기가 어둡고 선명도가 낮은 영상의 스티칭에서 정확도가 저하될 수 있고 생성된 스티칭 영상의 품질 또한 저하될 수 있다는 제한 사항이 있다. 이에 본 논문에서는 앞선 제한적 영상에 대하여 특징점 추출 및 매칭의 정확도를 높여 스티칭 영상의 품질을 높이기 위하여 SuperPoint와 SuperGLUE를 활용한 입력 영상의 밝기 적응형 영상 스티칭 방법을 제안하고자 한다.

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Prostate MR and Pathology Image Fusion through Image Correction and Multi-stage Registration (영상보정 및 다단계 정합을 통한 전립선 MR 영상과 병리 영상간 융합)

  • Jung, Ju-Lip;Jo, Hyun-Hee;Hong, Helen
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.9
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    • pp.700-704
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    • 2009
  • In this paper, we propose a method for combining MR image with histopathology image of the prostate using image correction and multi-stage registration. Our method consists of four steps. First, the intensity of prostate bleeding area on T2-weighted MR image is substituted for that on T1-weighted MR image. And two or four tissue sections of the prostate in histopathology image are combined to produce a single prostate image by manual stitching. Second, rigid registration is performed to find the affine transformations that to optimize mutual information between MR and histopathology images. Third, the result of affine registration is deformed by the TPS warping. Finally, aligned images are visualized by the intensity intermixing. Experimental results show that the prostate tumor lesion can be properly located and clearly visualized within MR images for tissue characterization comparison and that the registration error between T2-weighted MR and histopathology image was 0.0815mm.

Fast Stitching Algorithm by using Feature Tracking (특징점 추적을 통한 다수 영상의 고속 스티칭 기법)

  • Park, Siyoung;Kim, Jongho;Yoo, Jisang
    • Journal of Broadcast Engineering
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    • v.20 no.5
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    • pp.728-737
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    • 2015
  • Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

Development of Automatic Crack Detection System for Concrete Structure Using Image Processing Method (이미지 분석기법을 이용한 콘크리트 구조물의 균열 검출 시스템 개발)

  • Lee, Ho Beom;Kim, Jong Woo;Jang, Il Young
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.16 no.1
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    • pp.64-77
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    • 2012
  • In this study, the crack detecting system with digital image processing techniques based on the mathematical morphology method was developed to detect cracks in concrete structures. In the developed system, the image combining technique of reconstructing multiple images as an entire single image considering efficient management of analysis results was applied as an additional module. The developed system was verified through a field test with the cracked concrete culvert and the crack width of 0.2 mm was able to be detected in the 40m span. In the image analysis, the difference between calculated crack width and actual crack width were less than 0.08mm. For image combination in the stitching test of pattern images, the stitched image was identical with the original picture of entire subject in the visual perception level.

Three-Dimensional Rotation Angle Preprocessing and Weighted Blending for Fast Panoramic Image Method (파노라마 고속화 생성을 위한 3차원 회전각 전처리와 가중치 블랜딩 기법)

  • Cho, Myeongah;Kim, Junsik;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.235-245
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    • 2018
  • Recently panoramic image overcomes camera limited viewing angle and offers wide viewing angle by stitching plenty of images. In this paper, we propose pre-processing and post-processing algorithm which makes speed and accuracy improvements when making panoramic images. In pre-processing, we can get camera sensor information and use three-dimensional rotation angle to find RoI(Region of Interest) image. Finding RoI images can reduce time when extracting feature point. In post-processing, we propose weighted minimal error boundary cut blending algorithm to improve accuracy. This paper explains our algorithm and shows experimental results comparing with existing algorithms.

Real-time multiple face recognition system based on one-shot panoramic scanning (원샷 파노라믹 스캐닝 기반 실시간 다수 얼굴 인식 시스템)

  • Kim, Daehwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.553-555
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    • 2022
  • This paper is about a real-time automatic face recognition system based on one-shot panoramic scanning. It detects multiple faces in real time through a single panoramic scanning process and recognizes pre-registered faces. Instead of recognizing multiple faces within a single panoramic image, multiple faces are recognized using multiple images obtained in the scanning process. This reduces the panorama image creation time and stitching error, and at the same time can improve the face recognition performance by using the accumulated information of multiple images. It is expected that it can be used in various applications such as a multi-person smart attendance system with only a simple image acquisition device.

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A Study on the Seamline Estimation for Mosaicking of KOMPSAT-3 Images (KOMPSAT-3 영상 모자이킹을 위한 경계선 추정 방법에 대한 연구)

  • Kim, Hyun-ho;Jung, Jaehun;Lee, Donghan;Seo, Doochun
    • Korean Journal of Remote Sensing
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    • v.36 no.6_2
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    • pp.1537-1549
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    • 2020
  • The ground sample distance of KOMPSAT-3 is 0.7 m for panchromatic band, 2.8 m for multi-spectral band, and the swath width of KOMPSAT-3 is 16 km. Therefore, an image of an area wider than the swath width (16 km) cannot be acquired with a single scanning. Thus, after scanning multiple areas in units of swath width, the acquired images should be made into one image. At this time, the necessary algorithm is called image mosaicking or image stitching, and is used for cartography. Mosaic algorithm generally consists of the following 4 steps: (1) Feature extraction and matching, (2) Radiometric balancing, (3) Seamline estimation, and (4) Image blending. In this paper, we have studied an effective seamline estimation method for satellite images. As a result, we can estimate the seamline more accurately than the existing method, and the heterogeneity of the mosaiced images was minimized.

Image Mosaicking Considering Pairwise Registrability in Structure Inspection with Underwater Robots (수중 로봇을 이용한 구조물 검사에서의 상호 정합도를 고려한 영상 모자이킹)

  • Hong, Seonghun
    • The Journal of Korea Robotics Society
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    • v.16 no.3
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    • pp.238-244
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    • 2021
  • Image mosaicking is a common and useful technique to visualize a global map by stitching a large number of local images obtained from visual surveys in underwater environments. In particular, visual inspection of underwater structures using underwater robots can be a potential application for image mosaicking. Feature-based pairwise image registration is a commonly employed process in most image mosaicking algorithms to estimate visual odometry information between compared images. However, visual features are not always uniformly distributed on the surface of underwater structures, and thus the performance of image registration can vary significantly, which results in unnecessary computations in image matching for poor-conditioned image pairs. This study proposes a pairwise registrability measure to select informative image pairs and to improve the overall computational efficiency of underwater image mosaicking algorithms. The validity and effectiveness of the image mosaicking algorithm considering the pairwise registrability are demonstrated using an experimental dataset obtained with a full-scale ship in a real sea environment.

An X-ray Image Panorama System Using Robust Feature Matching and Per ception-Based Image Enhancement

  • Wang, Weiwei;Gwun, Oubong
    • Journal of Korea Multimedia Society
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    • v.15 no.5
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    • pp.569-576
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    • 2012
  • This paper presents an x-ray medical image panorama system which can overcome the smallness of the images that exist on a source computer during remote medical processing. In the system, after the standard medical image format DICOM is converted to the PC standard image format, a MSR algorithm is used to enhance X-ray images of low quality. Then SURF and Multi-band blending are applied to generate a panoramic image. Also, this paper evaluates the proposed SURF based system through the average gray value error and image quality criterion with X-ray image data by comparing with a SIFT based system. The results show that the proposed system is superior to SIFT based system in image quality.

Panoramic Video Generation Method Based on Foreground Extraction (전경 추출에 기반한 파노라마 비디오 생성 기법)

  • Kim, Sang-Hwan;Kim, Chang-Su
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.2
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    • pp.441-445
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    • 2011
  • In this paper, we propose an algorithm for generating panoramic videos using fixed multiple cameras. We estimate a background image from each camera. Then we calculate perspective relationships between images using extracted feature points. To eliminate stitching errors due to different image depths, we process background images and foreground images separately in the overlap regions between adjacent cameras by projecting regions of foreground images selectively. The proposed algorithm can be used to enhance the efficiency and convenience of wide-area surveillance systems.