• Title/Summary/Keyword: pixel distance

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A study of Landcover Classification Methods Using Airborne Digital Ortho Imagery in Stream Corridor (고해상도 수치항공정사영상기반 하천토지피복지도 제작을 위한 분류기법 연구)

  • Kim, Young-Jin;Cha, Su-Young;Cho, Yong-Hyeon
    • Korean Journal of Remote Sensing
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    • v.30 no.2
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    • pp.207-218
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    • 2014
  • The information on the land cover along stream corridor is important for stream restoration and maintenance activities. This study aims to review the different classification methods for mapping the status of stream corridors in Seom River using airborne RGB and CIR digital ortho imagery with a ground pixel resolution of 0.2m. The maximum likelihood classification, minimum distance classification, parallelepiped classification, mahalanobis distance classification algorithms were performed with regard to the improvement methods, the skewed data for training classifiers and filtering technique. From these results follows that, in aerial image classification, Maximum likelihood classification gave results the highest classification accuracy and the CIR image showed comparatively high precision.

Bilateral Approach for Fast Stero Matching (빠른 스테레오 매칭을 위한 Bilateral 접근 방법)

  • Ju, Myung-Ho;Kang, Hang-Bong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.1
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    • pp.136-143
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    • 2009
  • Typically, local methods for stereo matching are fast but have relatively low degree of accuracy while global ones, though costly, can achieve a higher degree of accuracy in retrieving disparity information. Recently, some local methods like the ones based on segmentation or adaptive weights are suggested which achieve more accuracy than global ones. These newly suggested local methods that can estimate more accurate disparity information cannot be easily used since they require more computational costs which increase in proportion to the window size they use. In this paper, we propose the method by using distance weights and pixel difference weights similar to those of the bilateral filter. Specifically, we present constant time O(1) algorithm for the case the distance weights are equal. The suggested method requires constant time for computation regardless of the used window size. Furthermore, experiments show that the matching performance of our method is as good as the ones of other recent methods.

Forensic Classification of Median Filtering by Hough Transform of Digital Image (디지털 영상의 허프 변환에 의한 미디언 필터링 포렌식 분류)

  • RHEE, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.5
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    • pp.42-47
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    • 2017
  • In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

Improvement of Analytic Reconstruction Algorithms Using a Sinogram Interpolation Method for Sparse-angular Sampling with a Photon-counting Detector

  • Kim, Dohyeon;Jo, Byungdu;Park, Su-Jin;Kim, Hyemi;Kim, Hee-Joung
    • Progress in Medical Physics
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    • v.27 no.3
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    • pp.105-110
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    • 2016
  • Sparse angular sampling has been studied recently owing to its potential to decrease the radiation exposure from computed tomography (CT). In this study, we investigated the analytic reconstruction algorithm in sparse angular sampling using the sinogram interpolation method for improving image quality and computation speed. A prototype of the spectral CT system, which has a 64-pixel Cadmium Zinc Telluride (CZT)-based photon-counting detector, was used. The source-to-detector distance and the source-to-center of rotation distance were 1,200 and 1,015 mm, respectively. Two energy bins (23~33 keV and 34~44 keV) were set to obtain two reconstruction images. We used a PMMA phantom with height and radius of 50.0 mm and 17.5 mm, respectively. The phantom contained iodine, gadolinium, calcification, and lipid. The Feld-kamp-Davis-Kress (FDK) with the sinogram interpolation method and Maximum Likelihood Expectation Maximization (MLEM) algorithm were used to reconstruct the images. We evaluated the signal-to-noise ratio (SNR) of the materials. The SNRs of iodine, calcification, and liquid lipid were increased by 167.03%, 157.93%, and 41.77%, respectively, with the 23~33 keV energy bin using the sinogram interpolation method. The SNRs of iodine, calcification, and liquid state lipid were also increased by 107.01%, 13.58%, and 27.39%, respectively, with the 34~44 keV energy bin using the sinogram interpolation method. Although the FDK algorithm with the sinogram interpolation did not produce better results than the MLEM algorithm, it did result in comparable image quality to that of the MLEM algorithm. We believe that the sinogram interpolation method can be applied in various reconstruction studies using the analytic reconstruction algorithm. Therefore, the sinogram interpolation method can improve the image quality in sparse-angular sampling and be applied to CT applications.

Efficient Implementation of Synthetic Aperture Imaging with Virtual Source Element in B-mode Ultrasound System Based on Sparse Array (희박 어레이 기반의 효율적인 양방향 화소단위 집속 기법의 구현)

  • 김강식;송태경
    • Journal of Biomedical Engineering Research
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    • v.23 no.6
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    • pp.419-430
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    • 2002
  • In this paper. we propose an efficient method for implementing hi-directional pixel-based focusing(BiPBF) based on a sparse array imaging technique. The proposed method can improve spatial resolution and frame rate of ultrasound imaging with reduced hardware complexity by synthesizing transmit apertures with a small number of sparsely distributed subapertures. As the distance between adjacent subapertures increases, however. the image resolution tends to decrease due to the elevation of grating lobes. Such grating lobes can be eliminated in conventional synthetic aperture imaging techniques. On the contrary, grating lobes arisen from employing sparse synthetic transmit apertures can not be eliminated, which has been shown analytically in this paper. We also propose the condition and method for suppressing the grating lobes below -40dB, which is generally required in practical imaging. by placing the transmit focal depth at a near depth and properly selecting the subaperture distance in Proportion to receive aperture size. The results of both the Phantom and in vivo experiments show that the proposed method implements two-wav dynamic focusing using a smaller number of subapertures, resulting in reduced system complexity and increased frame rate.

Design of a Real-time Algorithm Using Block-DCT for the Recognition of Speed Limit Signs (Block-DCT를 이용한 속도 제한 표지판 실시간 인식 알고리듬의 설계)

  • Han, Seung-Wha;Cho, Han-Min;Kim, Kwang-Soo;Hwang, Sun-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.12B
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    • pp.1574-1585
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    • 2011
  • This paper proposes a real-time algorithm for speed limit sign recognition for advanced safety vehicle system. The proposed algorithm uses Block-DCT in extracting features from a given ROI(Region Of Interest) instead of using entire pixel values as in previous works. The proposed algorithm chooses parts of the DCT coefficients according to the proposed discriminant factor, uses correlation coefficients and variances among ROIs from training samples to reduce amount of arithmetic operations without performance degradation in classification process. The algorithm recognizes the speed limit signs using the information obtained during training process by calculating LDA and Mahalanobis Distance. To increase the hit rate of recognition, it uses accumulated classification results computed for a sequence of frames. Experimental results show that the hit rate of recognition for sequential frames reaches up to 100 %. When compared with previous works, numbers of multiply and add operations are reduced by 69.3 % and 67.9 %, respectively. Start after striking space key 2 times.

Tracking of Golf Ball Using High-speed Cameras (고속카메라를 이용한 골프공 추적)

  • Choi, Seo-hyuk;Kim, Chang-dae;Kim, Dong-woo;Ryu, Sung-pil;Ahn, Jae-hyeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.827-829
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    • 2016
  • In this paper, in order to achieve the user's convenience in golf putting during practice, to provide a method of tracking the golf ball using a high speed camera. This is recently, it is to analyze so that you can hit a golf putting part of the leisure sport to enjoy a lot of people accurately. The proposed method, the pixel when using a common USB camera is blurred, since the golf ball detection rate is low and using a high-speed camera capable of measuring up to per second 380 frames. First, by using the Hough transform after pretreatment, to detect a golf ball. Movement path by using the information subsequently detected golf ball, calculating the moving distance and angle. The proposed method result of applying, improved travel route detection rate of the golf ball is improved, the accuracy of the moving distance and angle.

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Change Area Detection using Color and Edge Gradient Covariance Features (색상과 에지 공분산 특징을 이용한 변화영역 검출)

  • Kim, Dong-Keun;Hwang, Chi-Jung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.1
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    • pp.717-724
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    • 2016
  • This paper proposes a change detection method based on the covariance matrices of color and edge gradient in a color video. The YCbCr color format was used instead of RGB. The color covariance matrix was calculated from the CbCr-channels and the edge gradient covariance matrix was calculated from the Y-channels. The covariance matrices were effectively calculated at each pixel by calculating the sum, squared sum, and sum of two values' multiplication of a rectangle area using the integral images from a background image. The background image was updated by a running the average between the background image and a current frame. The change areas in a current frame image against the background were detected using the Mahalanobis distance, which is a measure of the statistical distance using covariance matrices. The experimental results of an expressway color video showed that the proposed approach can effectively detect change regions for color and edge gradients against the background.

The Font Recognition of Printed Hangul Documents (인쇄된 한글 문서의 폰트 인식)

  • Park, Moon-Ho;Shon, Young-Woo;Kim, Seok-Tae;Namkung, Jae-Chan
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.8
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    • pp.2017-2024
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    • 1997
  • The main focus of this paper is the recognition of printed Hangul documents in terms of typeface, character size and character slope for IICS(Intelligent Image Communication System). The fixed-size blocks extracted from documents are analyzed in frequency domain for the typeface classification. The vertical pixel counts and projection profile of bounding box are used for the character size classification and the character slope classification, respectively. The MLP with variable hidden nodes and error back-propagation algorithm is used as typeface classifier, and Mahalanobis distance is used to classify the character size and slope. The experimental results demonstrated the usefulness of proposed system with the mean rate of 95.19% in typeface classification. 97.34% in character size classification, and 89.09% in character slope classification.

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Vision-based Target Tracking for UAV and Relative Depth Estimation using Optical Flow (무인 항공기의 영상기반 목표물 추적과 광류를 이용한 상대깊이 추정)

  • Jo, Seon-Yeong;Kim, Jong-Hun;Kim, Jung-Ho;Lee, Dae-Woo;Cho, Kyeum-Rae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.3
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    • pp.267-274
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    • 2009
  • Recently, UAVs (Unmanned Aerial Vehicles) are expected much as the Unmanned Systems for various missions. These missions are often based on the Vision System. Especially, missions such as surveillance and pursuit have a process which is carried on through the transmitted vision data from the UAV. In case of small UAVs, monocular vision is often used to consider weights and expenses. Research of missions performance using the monocular vision is continued but, actually, ground and target model have difference in distance from the UAV. So, 3D distance measurement is still incorrect. In this study, Mean-Shift Algorithm, Optical Flow and Subspace Method are posed to estimate the relative depth. Mean-Shift Algorithm is used for target tracking and determining Region of Interest (ROI). Optical Flow includes image motion information using pixel intensity. After that, Subspace Method computes the translation and rotation of image and estimates the relative depth. Finally, we present the results of this study using images obtained from the UAV experiments.