• 제목/요약/키워드: Image Sets

검색결과 700건 처리시간 0.038초

Direction Information Concerned Algorithm for Removing Gaussian Noise in Images

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • 제9권6호
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    • pp.758-762
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    • 2011
  • In this paper an efficient algorithm is proposed to remove additive white Gaussian noise(AWGN) with edge preservation. A function is used to separate the filtering mask to two sets according to the direction information. Then, we calculate the mean and standard deviation of the pixels in each set. In order to preserve the details, we also compare standard deviations between the two sets to find out smaller one. Corrupted pixel is replaced by the mean of the filtering window's median value and the smaller set's mean value that the rate of change is faster than the other one. Experiment results show that the proposed algorithm outperforms with significant improvement in image quality than the conventional algorithms. The proposed method removes the Gaussian noise very effectively.

Landmark Detection Based on Sensor Fusion for Mobile Robot Navigation in a Varying Environment

  • Jin, Tae-Seok;Kim, Hyun-Sik;Kim, Jong-Wook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권4호
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    • pp.281-286
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    • 2010
  • We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

머리전달함수를 이용한 공간 음상 정위의 문제점 고찰 (Issues in Localising 3D Sound in Space Using Head- Related Transfer Functions)

  • 정완섭;황신;이정훈;권휴상
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1999년도 학술발표대회 논문집 제18권 1호
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    • pp.149-152
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    • 1999
  • This paper addresses major issues in localising sound sources in space using the experimental data set of head-related responses in the time or frequency domain. They come from the technical realisation steps for implementing the convolution of HRIR's with sound sources, the cross-talk cancellation for transaural filtering, the matched time delay compensation, etc. in real, those technical matters seem to be minor because they can be realised in off-line signal processing schemes. This paper puts much emphasis on what we misunderstood about the sets of HRTF's or HRIR's, More specifcaily, the sets of HRTF's or HRIR's of course supply relevant information to sound localisation but include much useless 'rubbish' that have made for us to fail to put spatial image into real souno signals such as voices and music's. This paper proposes possible reasons for such failure and, furthermore, introduces detained subjects that should be challenged so as to resolve them.

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2쌍의 초음파센서를 이용한 측정면의 위치 측정 및 종류 분류 기법 (Localization and Classification of Target Surfaces using Two fairs of Ultrasonic Sensors)

  • 한영준;한헌수
    • 제어로봇시스템학회논문지
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    • 제4권6호
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    • pp.747-752
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    • 1998
  • Ultrasonic sensors have been widely used to recognize the working environment for a mobile robot. However, their intrinsic problems, such as specular reflection, wide beam angle, and slow propagation velocity, require an excessive number of sensors to be integrated for achieving the sensing goal. This paper proposes a new measurement scheme which uses only two sets of ultrasonic sensors to determine the location and the type of a target surface. By measuring the time difference between the returned signals from the target surface, which are generated by two transmitters with 1 ㎳ difference, it classifies the type and determines the size of the target surface. Since the proposed sensor system uses only two sets of ultrasonic sensors to recognize and localize the target surface, it significantly simplifies the sensing system and reduces the signal processing time so that the working environment can be recognized in real time.

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Multi-gigabyte Multimedia Collections Using Qis Visualization Spreadsheet

  • 지승현
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2004년도 춘계 종합학술대회 논문집
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    • pp.207-214
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    • 2004
  • Qis 이미지 스프래드쉬트(Qis Image Spreadsheet) 환경은 멀티기가 바이트-다차원 멀티 미디어 데이터집합(multi-dimensional multimedia datasets)들의 비쥬얼라이제이션(visualization)을 수행하는데 매우 효과적이다. Qis는 프레임스택(framestack)을 이용하여 많은 양의 멀티미디어 데이터들을 집약적으로 압축하고 3차원 구조로 빠르게 구성할 수 있을 뿐 아니라 효과적으로 관리할 수 있다. 과학분야의 다양한 실험을 통해서도, Qis가 각 프레임 (frame)의 빠른 랜더링(rendering), 2-D 및 3-D그래픽 디스플레이, 다차원 데이터집합의 분석 등을 수행할 수 있는 우수한 상호작용 비쥬얼 툴(interactive visual browsing tool)임을 입증하였다.

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Shadow Effects Correction of Aerial Color Image Using Multi-Source Data Sets

  • Sohn, Hong-Gyoo;Yun, Kong-Hyun;Song, Yeong-Sun;Park, Hyo-Keun
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2004년도 추계학술발표회 논문집
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    • pp.285-290
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    • 2004
  • 그림자효과 보정은 도심지역에서 영상 해석 또는 지상의 인공지물을 추출하는데 있어서 상당히 중요한 처리과정이다. 본 연구에서는 다중자료원(Multi-Source Data Sets)을 이용하여 컬러항공사진에 발생한 그림자의 효과를 효율적으로 처리 및 보정 할 수 있는 알고리즘을 제시하였으며 시각적인 비교뿐만 아니라 도로추출의 시도로 그림자 보정효과의 입증하였다. 또한 다중자료원인 컬러항공사진, LiDAR 고도자료 그리고 1:1000 수치지도를 이용하여 각 센서 및 기존 자료가 가지고 있는 장점을 최대한 살려 시너지 효과를 나타낼 수 있도록 적절한 융합과정을 시도하여 성공적인 예를 보여주었다.

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딥러닝 인공지능 기법을 이용한 화재인식 알고리즘에 관한 연구 (A Study on Fire Recognition Algorithm Using Deep Learning Artificial Intelligence)

  • 류진규;곽동걸;김재중;최정규
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2018년도 전력전자학술대회
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    • pp.275-277
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    • 2018
  • Recently, the importance of an early response has been emphasized due to the large fire. The most efficient method of extinguishing a large fire is early response to a small flame. To implement this solution, we propose a fire detection mechanism based on a deep learning artificial intelligence. In this study, a small amount of data sets is manipulated by an image augmentation technique using rotating, tilting, blurring, and distorting effects in order to increase the number of the data sets by 5 times, and we study the flame detection algorithm using faster R-CNN.

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디지츨 영상의 복사 방지를 위한 적응 워터마킹 방법 (An Adaptive Watermarking Method for Copy Protectionof Digital Images)

  • 김덕령;박성한
    • 전자공학회논문지S
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    • 제35S권4호
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    • pp.85-95
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    • 1998
  • In this paper, a new watermarking method for a copy protectionof images is proposed. The proposed method adaptively embeds a watermark in the frequency domain of images using human visual system model. For this purpose, the Just Noticeable Differences(JNDs) of each frequency coeffeicient value of a luminance plane is first found using Watson and Solomon's visual system model. An invisible maximum watermark value with is different in every position according to the characteristics of images is determined usig JND and Minkowski metric. A low frequency domain is divided into two sets based on a PN-sequence to protect thewatermark from the attack. The watermarks are added to one set of coefficients and detecting a watermark, the difference between the mean values of absolute coefficient values of both sets is calculated. The embedded watermark is tested using statistical hypothesis based on test static dertermined by the ean difference. To demonstrate the perfromance of the proposed method, the new watermarking method is applied to a high frequency image and low frequency images. Experimenatal results show the watermark is invisible and robust to JPEGlossy compression and noise.

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On a Novel Way of Processing Data that Uses Fuzzy Sets for Later Use in Rule-Based Regression and Pattern Classification

  • Mendel, Jerry M.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권1호
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    • pp.1-7
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    • 2014
  • This paper presents a novel method for simultaneously and automatically choosing the nonlinear structures of regressors or discriminant functions, as well as the number of terms to include in a rule-based regression model or pattern classifier. Variables are first partitioned into subsets each of which has a linguistic term (called a causal condition) associated with it; fuzzy sets are used to model the terms. Candidate interconnections (causal combinations) of either a term or its complement are formed, where the connecting word is AND which is modeled using the minimum operation. The data establishes which of the candidate causal combinations survive. A novel theoretical result leads to an exponential speedup in establishing this.

Feature Extraction and Multisource Image Classification

  • Amarsaikhan, D.;Sato, M.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1084-1086
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    • 2003
  • The aim of this study is to assess the integrated use of different features extracted from spaceborne interferometric synthetic aperture radar (InSAR) data and optical data for land cover classification. Special attention is given to the discriminatory characteristics of the features derived from the multisource data sets. For the evaluation of the features , the statistical maximum likelihood decision rule and neural network classification are used and the results are compared. The performance of each method was evaluated by measuring the overall accuracy. In all cases, the performance of the first method was better than the performance of the latter one. Overall, the research indicated that multisource data sets containing different information about backscattering and reflecting properties of the selected classes of objects can significantly improve the classification of land cover types.

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