• Title/Summary/Keyword: Multiple images

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Images Grouping Technology based on Camera Sensors for Efficient Stitching of Multiple Images (다수의 영상간 효율적인 스티칭을 위한 카메라 센서 정보 기반 영상 그룹핑 기술)

  • Im, Jiheon;Lee, Euisang;Kim, Hoejung;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.713-723
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    • 2017
  • Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

Improvement of Gibb's Phenomena in Fast Spin Echo Imaging Using Symmetric Echo Arrangement and Filtering (대칭적 에코 배치 및 필터링을 통한 Fast Spin Echo 영상에서의 Gibb's 현상 개선)

  • 안창범;김치영;오창현;신진교
    • Investigative Magnetic Resonance Imaging
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    • v.1 no.1
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    • pp.79-85
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    • 1997
  • Fast spin echo imaging utilizes multiple spin echoes to encode multiple k-space lines instead of multiple $T_2-weighted$ images. As results, intensities in k-space data are varying according to T2 decay, which generates Gibb's artifact in the reconstructed image. The echo time for e encoding dc block determines contrast, as is specified by the effective echo time, however, all location of other echoes to different k-space frequency blocks in fast spin echo imaging is not f fully investigated. In this study, symmetric arrangement of multiple echoes in k-space is investigated to reduce Gibb's artifact. Design of filters based on the measurement of multiple e echo intensities is also proposed in two stage manner, i.e., equalization and filtering. From s simulation and experiment, it was observed that Gibb's phenomena were substantially reduced b by the proposed methods.

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A Fast Snake Algorithm for Tracking Multiple Objects

  • Fang, Hua;Kim, Jeong-Woo;Jang, Jong-Whan
    • Journal of Information Processing Systems
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    • v.7 no.3
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    • pp.519-530
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    • 2011
  • A Snake is an active contour for representing object contours. Traditional snake algorithms are often used to represent the contour of a single object. However, if there is more than one object in the image, the snake model must be adaptive to determine the corresponding contour of each object. Also, the previous initialized snake contours risk getting the wrong results when tracking multiple objects in successive frames due to the weak topology changes. To overcome this problem, in this paper, we present a new snake method for efficiently tracking contours of multiple objects. Our proposed algorithm can provide a straightforward approach for snake contour rapid splitting and connection, which usually cannot be gracefully handled by traditional snakes. Experimental results of various test sequence images with multiple objects have shown good performance, which proves that the proposed method is both effective and accurate.

Joint-transform Correlator Multiple-image Encryption System Based on Quick-response Code Key

  • Chen, Qi;Shen, Xueju;Cheng, Yue;Huang, Fuyu;Lin, Chao;Liu, HeXiong
    • Current Optics and Photonics
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    • v.3 no.4
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    • pp.320-328
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    • 2019
  • A method for joint-transform correlator (JTC) multiple-image encryption based on a quick-response (QR) code key is proposed. The QR codes converted from different texts are used as key masks to encrypt and decrypt multiple images. Not only can Chinese text and English text be used as key text, but also symbols can be used. With this method, users have no need to transmit the whole key mask; they only need to transmit the text that is used to generate the key. The correlation coefficient is introduced to evaluate the decryption performance of our proposed cryptosystem, and we explore the sensitivity of the key mask and the capability for multiple-image encryption. Robustness analysis is also conducted in this paper. Computer simulations and experimental results verify the correctness of this method.

Adaptive Transform Image Coding by Fuzzy Subimage Classification

  • Kong, Seong-Gon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.2 no.2
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    • pp.42-60
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    • 1992
  • An adaptive fuzzy system can efficiently classify subimages into four categories according to image activity level for image data compression. The system estimates fuzzy rules by clustering input-output data generated from a given adaptive transform image coding process. The system encodes different images without modification and reduces side information when encoding multiple images. In the second part, a fuzzy system estimates optimal bit maps for the four subimage classes in noisy channels assuming a Gauss-Markov image model. The fuzzy systems respectively estimate the sampled subimage classification and the bit-allocation processes without a mathematical model of how outputs depend on inputs and without rules articulated by experts.

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3-D Reconstruction of Buildings using 3-D Line Grouping for Urban Modeling

  • Jung, Young-Kee
    • Journal of information and communication convergence engineering
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    • v.7 no.1
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    • pp.1-6
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    • 2009
  • In order to obtain a 3-D urban model, an abstraction of the surface model is required. This paper describes works on the 3D reconstruction and modeling by the grouping 3D line segments extracted from the stereo matching of edges, which is derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

Magnetic Resonance Imaging with Intermolecular Double Quantum Coherences

  • Ahn, Sang-Doo
    • Journal of the Korean Magnetic Resonance Society
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    • v.8 no.2
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    • pp.108-114
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    • 2004
  • Recently a new method for magnetic resonance imaging based on the detection of relatively strong signal from intermolecular multiple quantum coherences (iMQCs) is reported. Such a signal would not be observable in the conventional framework of magnetic resonance; it originates in long-range dipolar couplings that are traditionally ignored. In this paper, we present the results of experimental studies to assess the feasibility of intermolecular double quantum coherences (iDQCs) imaging in humans. We show that the iDQC images are readily observable at 4T and that they do indeed provide different contrast than appears in conventional images.

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3D image mosaicking technique using multiple planes for urban visualization (복수 투영면을 사용한 도심지 가시화용 3 차원 모자이크 기술)

  • CHON Jaechoon;KIM Hyongsuk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.41-50
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    • 2005
  • A novel image mosaicking technique suitable for 3D urban visualization is proposed. It is not effective to apply 2D image mosaicking techniques for urban visualization when, for example, one is filming a sequence of images from a side-looking video camera along a road in an urban area. The proposed method presents the roadside scene captured by a side-looking video camera as a continuous set of textured planar faces, which are termed 'multiple planes' in this paper. The exterior parameters of each frame are first calculated through automatically selected matching feature points. The matching feature points are also used to estimate a plane approximation of the scene geometry for each frame. These planes are concatenated to create an approximate model on which images are back-projected as textures. Here, we demonstrate algorithm that creates efficient image mosaics in 3D space from a sequence of real images.

Multiple TIP Images Blending for Wide Virtual Environment (넓은 가상환경 구축을 위한 다수의 TIP (Tour into the Picture) 영상 합성)

  • Roh, Chang-Hyun;Lee, Wan-Bok;Ryu, Dae-Hyun;Kang, Jung-Jin
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.42 no.1
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    • pp.61-68
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    • 2005
  • Image-based rendering is an approach to generate realistic images in real-time without modeling explicit 3D geometry. Especially, owing to its simplicity, TIP(Tour Into the Picture) is preferred to constructing a 3D background scene. Because existing TIP methods have a limitation in that they lack geometrical information, we can not expect a accurate scene if the viewpoint is far from the origin of the TIP. In this paper, we propose the method of constructing a virtual environment of a wide area by blending multiple TIP images. Firstly, we construct multiple TIP models of the virtual environment. Then we interpolate foreground and background objects respectively, to generate a smooth navigation image. The method proposed here can be applied to various industry applications, such as computer game, 3D car navigation, and so on.

Relating Hyperspectral Image Bands and Vegetation Indices to Corn and Soybean Yield

  • Jang Gab-Sue;Sudduth Kenneth A.;Hong Suk-Young;Kitchen Newell R.;Palm Harlan L.
    • Korean Journal of Remote Sensing
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    • v.22 no.3
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    • pp.183-197
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    • 2006
  • Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.