• 제목/요약/키워드: Task Extraction

검색결과 208건 처리시간 0.028초

Visual Attention Detection By Adaptive Non-Local Filter

  • Anh, Dao Nam
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권1호
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    • pp.49-54
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    • 2016
  • Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

Online Digit Recognition using Start and End Point

  • Shim, Jae-chang;Ansari, Md Israfil
    • Journal of Multimedia Information System
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    • 제4권1호
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    • pp.39-42
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    • 2017
  • Communication between human and machine is having been researched from last few decades and still it's a challenging task because human behavior is unpredictable. When it comes on handwritten digits almost each human has their own writing style. Handwritten digit recognition plays an important role, especially in the courtesy amounts on bank checks, postal code on mail address etc. In our study, we proposed an efficient feature extraction system for recognizing single digit number drawn by mouse or by a finger on a screen. Our proposed method combines basic image processing and reading the strokes of a line drawn. It is very simple and easy to implement in various platform as compare to the system which required high system configuration. This system has been designed, implemented, and tested successfully.

Sculptured 포켓 가공을 위한 가공특징형상 추출 (Manufacturing Feature Extraction for Sculptured Pocket Machining)

  • 주재구;조현보
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 춘계학술대회 논문집
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    • pp.455-459
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    • 1997
  • A methodology which supports the feature used from design to manufacturing for sculptured pocket is newly devlored and present. The information contents in a feature can be easily conveyed from one application to another in the manufacturing domain. However, the feature generated in one application may not be directly suitable for another whitout being modified with more information. Theobjective of the paper is to parsent the methodology of decomposing a bulky feature of sculptured pocket to be removed into compact features to be efficiently machined. In particular, the paper focuses on the two task: 1) to segment horizontally a bulky feature into intermediate features by determining the adequate depth of cut and cutter size and to generate the temporal precedence graph of the intermediate features and 2)to further decompose each intermediate feature vertical into smaller manufacturing features and to apply the variable feed rate to each small feature. The proposed method will provid better efficiency in machining time and cost than the classical method which uses a long string of NC codes necessary to remove a bulky fecture.

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AUTOMATIC SELECTION AND ADJUSTMENT OF FEATURES FOR IMAGE CLASSIFICATION

  • Saiki, Kenji;Nagao, Tomoharu
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.525-528
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    • 2009
  • Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".

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A Matlab and Simulink Based Three-Phase Inverter Fault Diagnosis Method Using Three-Dimensional Features

  • Talha, Muhammad;Asghar, Furqan;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권3호
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    • pp.173-180
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    • 2016
  • Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

영역분할 기법을 이용한 염색체 표본 자동추출 (Automated Chromosome Samples Extraction using Region Splitting Method)

  • 엄상희;전계록;이권순;장용훈;이상렬
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 춘계학술대회
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    • pp.127-130
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    • 1995
  • Chromosome analysis is an important and difficult task for clinical diagnosis, for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts lo automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

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핵형분석을 위한 염색체 영상 표본의 자동 추출 (Automatic Extraction of Chromosome Image Samples for the Karyotype Analysis)

  • 장용훈;이권순;전계록
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.661-663
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    • 1995
  • Chromosome analysis is an important and difficult task for clinical diagnosis for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts to automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

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Organizing Lidar Data Based on Octree Structure

  • Wang, Miao;Tseng, Yi-Hsing
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.150-152
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    • 2003
  • Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

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Mean-Shift Blob Clustering and Tracking for Traffic Monitoring System

  • Choi, Jae-Young;Yang, Young-Kyu
    • 대한원격탐사학회지
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    • 제24권3호
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    • pp.235-243
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    • 2008
  • Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.

한의학적 유전병변 바이오 마커 추출 알고리즘 (Biomarker Extraction Algorithm for Oriental Genetic Lesion)

  • 김민경;우성희;조영복
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2019년도 춘계학술대회
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    • pp.367-371
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    • 2019
  • 한의학의 '과학화'는 세계 속의 K-MEDI를 위해 선행되야 할 과제로 한약의 효능을 과학적으로 입증하는 작업을 통해 유효성 및 안전성이 확보하고자 노력하고 있다. 본 논문은 한의학적 유전병변 판독을 위한 바이오마커 추출 알고리즘을 제안함으로 한의학적 관점에서 응용되있는 다양한 한의학적 치료법의 진단 및 치료 효과의 객관화에 근거를 제시하였다.

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