• Title/Summary/Keyword: image data

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Generation of Simulated Geospatial Images from Global Elevation Model and SPOT Ortho-Image

  • Park, Wan Yong;Eo, Yang Dam
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.3
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    • pp.217-223
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    • 2014
  • With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

Implementation Of Moving Picture Transfer System Using Bluetooth (Bluetooth를 이용한 동영상 전송 시스템 구현)

  • 조경연;이승은;최종찬
    • Proceedings of the IEEK Conference
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    • 2001.06a
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    • pp.25-28
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    • 2001
  • In this paper we implement moving picture transfer system using bluetooth Development Kit (DK). To reduce the size of the image data, we use M-JPEG compression. We use bluetooth Synchronous Connection-Oriented (SCO) link to transfer voice data. Server receive image data from camera and compress the image data in M-JPEG format, and then transmit the image data to client using bluetooth Asynchronous connection-less (ACL) link. Client receive image data from bluetooth ACL link and decode the compressed image and then display the image to screen. Sever and Client can transmit and receive voice data simultaneously using bluetooth SCO link. In this paper bluetooth HCI commands and events generated by host controller to return the results of HCI commands are explained and the flow of bluetooth connection procedure is presented.

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Qualification Test of ROCSAT -2 Image Processing System

  • Liu, Cynthia;Lin, Po-Ting;Chen, Hong-Yu;Lee, Yong-Yao;Kao, Ricky;Wu, An-Ming
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1197-1199
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    • 2003
  • ROCSAT-2 mission is to daily image over Taiwan and the surrounding area for disaster monitoring, land use, and ocean surveillance during the 5-year mission lifetime. The satellite will be launched in December 2003 into its mission orbit, which is selected as a 14 rev/day repetitive Sun-synchronous orbit descending over (120 deg E, 24 deg N) and 9:45 a.m. over the equator with the minimum eccentricity. National Space Program Office (NSPO) is developing a ROCSAT-2 Image Processing System (IPS), which aims to provide real-time high quality image data for ROCSAT-2 mission. A simulated ROCSAT-2 image, based on Level 1B QuickBird Data, is generated for IPS verification. The test image is comprised of one panchromatic data and four multispectral data. The qualification process consists of four procedures: (a) QuickBird image processing, (b) generation of simulated ROCSAT-2 image in Generic Raw Level Data (GERALD) format, (c) ROCSAT-2 image processing, and (d) geometric error analysis. QuickBird standard photogrammetric parameters of a camera that models the imaging and optical system is used to calculate the latitude and longitude of each line and sample. The backward (inverse model) approach is applied to find the relationship between geodetic coordinate system (latitude, longitude) and image coordinate system (line, sample). The bilinear resampling method is used to generate the test image. Ground control points are used to evaluate the error for data processing. The data processing contains various coordinate system transformations using attitude quaternion and orbit elements. Through the qualification test process, it is verified that the IPS is capable of handling high-resolution image data with the accuracy of Level 2 processing within 500 m.

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Embedding Method of Secret Data using Error-Diffusion (오차 확산법을 이용한 기밀 데이터 합성법)

  • 박영란;이혜주;박지환
    • Journal of Korea Multimedia Society
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    • v.2 no.2
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    • pp.155-165
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    • 1999
  • Because the encrypted data is random, there is a possibility of threat that attacker reveals the secret data. On the other hand, as the image steganogrphy is to embed the secret data into cover image and to transmit the embedded image to receiver, an attacker could not know the existence of secret data even though he/she sees the embedded image, therefore the sender may reduce the threat of attack. In the image steganography, the secret data is embedded by modifying value of pixels as a form of noise. If the secret data is embedded into gray image, the degradation of image quality results from the modifications of image due to noise. Therefore many methods have been proposed to embed the secret data while dethering the gray image, but the existing method using error-diffusion has a problem that any patterns such as a diagonal lines or vertical take place due to embedding the secret data at the fixed interval. To solve this problem and to improve the existing method, we proposed the new method that embeds the secret data at changed point with respect to 1's run-length or at the position where has the minimum difference with the original dithered value. We evaluated the performance of the proposed method by computer simulation.

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Reversible Data Hiding in Permutation-based Encrypted Images with Strong Privacy

  • Shiu, Chih-Wei;Chen, Yu-Chi;Hong, Wien
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.1020-1042
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    • 2019
  • Reversible data hiding in encrypted images (RDHEI) provides some real-time cloud applications; i.e. the cloud, acting as a data-hider, automatically embeds timestamp in the encrypted image uploaded by a content owner. Many existing methods of RDHEI only satisfy user privacy in which the data-hider does not know the original image, but leaks owner privacy in which the receiver can obtains the original image by decryption and extraction. In the literature, the method of Zhang et al. is the one providing weak content-owner privacy in which the content-owner and data-hider have to share a data-hiding key. In this paper, we take care of the stronger notion, called strong content-owner privacy, and achieve it by presenting a new reversible data hiding in encrypted images. In the proposed method, image decryption and message extraction are separately controlled by different types of keys, and thus such functionalities are decoupled to solve the privacy problem. At the technique level, the original image is segmented along a Hilbert filling curve. To keep image privacy, segments are transformed into an encrypted image by using random permutation. The encrypted image does not reveal significant information about the original one. Data embedment can be realized by using pixel histogram-style hiding, since this property, can be preserved before or after encryption. The proposed method is a modular method to compile some specific reversible data hiding to those in encrypted image with content owner privacy. Finally, our experimental results show that the image quality is 50.85dB when the averaged payload is 0.12bpp.

Automatic Classification Method for Time-Series Image Data using Reference Map (Reference Map을 이용한 시계열 image data의 자동분류법)

  • Hong, Sun-Pyo
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.2
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    • pp.58-65
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    • 1997
  • A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

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Bands Classification of Multispectral Image Data using Indiscernibility Relations in Rough Sets (러프 집합에서의 식별 불능 관계를 이용한 다중 분광 이미지 데이터의 밴드 분류)

  • Won Sung-Hyun
    • Management & Information Systems Review
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    • v.1
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    • pp.401-412
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    • 1997
  • Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers have been devoted their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new bands selection method for multispectral bands of remote sensed image data that use rough set theory. Using indiscernibility relations in rough sets, we show that can select the efficient bands of multispectral image data, automatically.

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Classification of Multi Spectral Image Data using Rough Sets (러프 집합을 이용한 다중 분광 이미지 데이터의 분류)

  • 원성현;이병성;정환묵
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.11a
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    • pp.205-208
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    • 1997
  • Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers devote their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new classification method for remote sensed image data that use rough set theory. Using indiscernibility relation of rough sets, we show that can classify image data very easily.

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Development of 32-Channel Image Acquisition System for Thickness Measurement of Retina (망막 두께 측정을 위한 32채널 영상획득장치 개발)

  • 양근호;유병국
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.110-113
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    • 2003
  • In this paper, the multi-channel high speed data acquisition system is implemented. This high speed signal processing system for 3-D image display is applicable to the manipulation of a medical image processing, multimedia data and various fields of digital image processing. In order to convert the analog signal into digital one, A/D conversion circuit is designed. PCI interface method is designed and implemented, which is capable of transmission a large amount of data to computer. In order to, especially, channel extendibility of images acquisition, bus communication method is selected. By using this bus method, we can interface each module effectively. In this paper, 32-channel A/D conversion and PCI interface system for 3-dimensional and real-time display of the retina image is developed. The 32-channel image acquisition system and high speed data transmission system developed in this paper is applicable to not only medical image processing as 3-D representation of retina image but also various fields of industrial image processing in which the multi-point realtime image acquisition system is needed.

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Thermal Image Processing and Synthesis Technique Using Faster-RCNN (Faster-RCNN을 이용한 열화상 이미지 처리 및 합성 기법)

  • Shin, Ki-Chul;Lee, Jun-Su;Kim, Ju-Sik;Kim, Ju-Hyung;Kwon, Jang-woo
    • Journal of Convergence for Information Technology
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    • v.11 no.12
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    • pp.30-38
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    • 2021
  • In this paper, we propose a method for extracting thermal data from thermal image and improving detection of heating equipment using the data. The main goal is to read the data in bytes from the thermal image file to extract the thermal data and the real image, and to apply the composite image obtained by synthesizing the image and data to the deep learning model to improve the detection accuracy of the heating facility. Data of KHNP was used for evaluation data, and Faster-RCNN is used as a learning model to compare and evaluate deep learning detection performance according to each data group. The proposed method improved on average by 0.17 compared to the existing method in average precision evaluation.As a result, this study attempted to combine national data-based thermal image data and deep learning detection to improve effective data utilization.