• Title/Summary/Keyword: Correlation Image Sensor

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Correlation analysis between rotation parameters and attitude parameters in simulated satellite image

  • Yun, Young-Bo;Park, Jeong-Ho;Yoon, Geun-Won;Park, Jong-Hyun
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.553-558
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    • 2002
  • Physical sensor model in pushbroom satellite images can be made from sensor modeling by rotation parameters and attitude parameters on the satellite track. These parameters are determined by the information obtained from GPS, INS, or star tracker. Provided from satellite image, an auxiliary data error is connected directly with an error of rotation parameters and attitude parameters. This paper analyzed how obtaining satellite images influenced errors of rotation parameters and attitude parameters. furthermore, for detailed analysis, this paper generated simulated satellite image, which was changed variously by rotation parameters and attitude parameters of satellite sensor model. Simulated satellite image is generated by using high-resolution digital aerial image and DEM (Digital Elevation Model) data. Moreover, this paper determined correlation of rotation parameter and attitude parameters through error analysis of simulated satellite image that was generated by various rotation parameters and attitude parameters.

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Automatic Image Registration Based on Extraction of Corresponding-Points for Multi-Sensor Image Fusion (다중센서 영상융합을 위한 대응점 추출에 기반한 자동 영상정합 기법)

  • Choi, Won-Chul;Jung, Jik-Han;Park, Dong-Jo;Choi, Byung-In;Choi, Sung-Nam
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.4
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    • pp.524-531
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    • 2009
  • In this paper, we propose an automatic image registration method for multi-sensor image fusion such as visible and infrared images. The registration is achieved by finding corresponding feature points in both input images. In general, the global statistical correlation is not guaranteed between multi-sensor images, which bring out difficulties on the image registration for multi-sensor images. To cope with this problem, mutual information is adopted to measure correspondence of features and to select faithful points. An update algorithm for projective transform is also proposed. Experimental results show that the proposed method provides robust and accurate registration results.

Visual Tracking using Weighted Discriminative Correlation Filter

  • Song, Tae-Eun;Jang, Kyung-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.11
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    • pp.49-57
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    • 2016
  • In this paper, we propose the novel tracking method which uses the weighted discriminative correlation filter (DCF). We also propose the PSPR instead of conventional PSR as tracker performance evaluation method. The proposed tracking method uses multiple DCF to estimates the target position. In addition, our proposed method reflects more weights on the correlation response of the tracker which is expected to have more performance using PSPR. While existing multi-DCF-based tracker calculates the final correlation response by directly summing correlation responses from each tracker, the proposed method acquires the final correlation response by weighted combining of correlation responses from the selected trackers robust to given environment. Accordingly, the proposed method can provide high performance tracking in various and complex background compared to multi-DCF based tracker. Through a series of tracking experiments for various video data, the presented method showed better performance than a single feature-based tracker and also than a multi-DCF based tracker.

Research of Phase Correlation Method for Identifying Quantitative Similarity in Adjacent Real-time Streaming Frame

  • Cho, Yongjin;Yun, Yeji;Lee, Kyou-seung;Oh, Jong-woo;Lee, DongHoon
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.157-157
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    • 2017
  • To minimize the damage by wild birds and acquire the benefits such as protection against weeds and maintenance of water content in soil, the mulching black color vinyl after seeding should be carried out. Non-contact and non-destructive methods that can continuously determine the locations are necessary. In this study, a crop position detection method was studied that uses infrared thermal image sensor to determine the cotyledon position under vinyl mulch. The moving system for acquiring image arrays has been developed for continuously detecting crop locations under plastic mulching on the field. A sliding mechanical device was developed to move the sensor, which were arranged in the form of a linear array, perpendicular to the array using a micro-controller integrated with a stepping motor. The experiments were conducted while moving 4.00 cm/s speed of the IR sensor by the rotational speed of the stepping motor based on a digital pulse width modulation signal from the micro-controller. The acquired images were calibrated with the spatial image correlation. The collected data were processed using moving averaging on interpolation to determine the frame where the variance was the smallest in resolution units of 1.02 cm. Non-linear integral interpolation was one of method for analyzing the frequency using the normalization image and then arbitrarily increasing the limited data value of $16{\times}4pixels$ in one frame. It was a method to relatively reduce the size of overlapping pixels by arbitrarily increasing the limited data value. The splitted frames into 0.1 units instead of 1 pixel can propose more than 10 times more accurate and original method than the existing correction method. The non-integral calibration method was conducted by applying the subdivision method to the pixels to find the optimal correction resolution based on the first reversed frequency. In order to find a correct resolution, the expected location of the first crop was indicated on near pixel 4 in the inversion frequency. For the most optimized resolution, the pixel was divided by 0.4 pixel instead of one pixel to find out where the lowest frequency exists.

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Human Activity Recognition using an Image Sensor and a 3-axis Accelerometer Sensor (이미지 센서와 3축 가속도 센서를 이용한 인간 행동 인식)

  • Nam, Yun-Young;Choi, Yoo-Joo;Cho, We-Duke
    • Journal of Internet Computing and Services
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    • v.11 no.1
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    • pp.129-141
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    • 2010
  • In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

A Simple Mathematical Analysis of Correlation Target Tracker in Image Sequences (영상신호를 이용한 상관방식 추적기에 대한 간단한 수학적인 해석)

  • Cho, Jae-Soo;Park, Dong-Jo
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.485-488
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    • 2003
  • A conventional correlation target tracker is analysed with a simple mathematical approach. And, we will propose a correlation measure with selective attentional property in order to overcome the false-peak problem of the conventional methods. Various experimental results show that the proposed correlation measure is able to reduce considerably the probability of false-peaks degraded by the correlation between background images of a reference block and a distorted and noisy sensor input image.

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Moving Pixel Displacement Detection using Correlation Functions on CIS Image

  • Ryu, Kwang-Ryol;Kim, Young-Bin
    • Journal of information and communication convergence engineering
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    • v.8 no.4
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    • pp.349-354
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    • 2010
  • Moving pixel displacement detection algorithm using correlation functions for making panorama image on the continuous images is presented in this paper. The input images get from a CMOS image sensor (CIS). The camera is maintained by constant brightness and uniform sensing area in test input pattern. For simple navigation and capture image has to 70% overlapped region. A correlation rate in two image data is evaluated by using reference image with first captures, and compare image with next captures. The displacement of the two images are expressed to second order function of x, y and solved with finding the coefficient in second order function. That results in the change in the peak correlation displacement from the reference to the compare image, is moving to pixel length. The navigating error is reduced by varying the path because the error is shown in the difference of the positioning vector between the true pixel position and the navigated pixel position. The algorithm performance is evaluated to be different from the error vector to vary the navigating path grid.

Estimation of Rotation of Camera Direction and Distance Between Two Camera Positions by Using Fisheye Lens System

  • Aregawi, Tewodros A.;Kwon, Oh-Yeol;Park, Soon-Yong;Chien, Sung-Il
    • Journal of Sensor Science and Technology
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    • v.22 no.6
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    • pp.393-399
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    • 2013
  • We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

Study on Improvement of Measurement Precision in Digital Image Correlation Measurement Method by Using Subpixel Algorithms (이미지 상관법의 서브 픽셀 알고리즘을 이용한 측정 분해능 향상에 관한 연구)

  • Kim, Seung Jong;Kang, Young Jun;Choi, In Young;Hong, Kyung Min;Ryu, Won Jea
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.12
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    • pp.1039-1047
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    • 2015
  • Contact type sensors (e.g., displacement sensor and strain gauge) were typically used to evaluate the safety and mechanical properties in machines and construction. However, those contact type sensors have been constrained because of measurement problems such as surface roughness, temperature, humidity, and shape. The Digital Image Correlation (DIC) measurement system is a vision measurement system. This measurement system uses the taken image using a CCD camera and calculates the image correlation between the reference image and the deformed image under external force to measure the displacement and strain rates. In this paper, we discuss methods to improve the measurement precision of the digital image correlation measurement system. A tensile test was conducted to compare the precision improvement effects, by using the universal test machine and the DIC measurement system, with the use of subpixel algorithms, i.e., the Coarse Fine Search (CFS) algorithm and the Peak Finding (PF) algorithm.

Multi-Sensor Image Alignment By Statistical Correlation (통계적 Correlation을 이용한 다중센서 영상 정합)

  • 고진신;박영태
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.586-588
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    • 2003
  • 현재 많이 연구되는 영상융합(Image fusion)에서는 필히 두 영상의 정합(alignment)이 이루어져야만 수행된다. 각기 다른 특징을 갖는 센서(EO.IR.Radar등)로부터 얻는 영상에서는 각각 다른 특징점 정보를 가지므로, 특징점을 이용한 영상 정합 구현에는 전처리 과정이 매우 복잡하고 까다롭게 이루어져야 한다. 본 논문에서는 Correlation에 대한 통계적 상관 관계를 이용하여. 전처리 과정을 단순하게 수행 하여도 매우 강건한 영상 정합이 이루어지도록 구현 하였다. 또한, 통계적 기법에 적합하도록, 효율적인 전처리 과정을 통해 계산량이 적어 지는 방법을 제안 한다.

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