• Title/Summary/Keyword: characteristic feature

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Cloches Selection in Accordance with Job Characteristic and Working Place Situation of A Professional Women in Industry (산업체 전문직 여성의 직무특성과 직장상황에 의한 의복선택 연구)

  • 정은숙;이선재
    • Journal of the Korean Society of Costume
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    • v.50 no.5
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    • pp.77-90
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    • 2000
  • The purpose of this study is to disclose the dimension of job characteristic, working place situation. and clothes selection, which are variable on clothes selection, to research the relation of job characteristic, working place situation, and clothes selection and to disclose the feature of consumers by each group in accordance with job characteristic. The follows are summary of this study result : The concept structure of job characteristic is composed by four types. Working place situation related with clothes selection are consisted of five types. Professional women selected clothes in accordance with nine feature. Job characteristic is related with working palace situation and influences on clothes selection. The persons influenced by activity state regarded personality as important when select clothes. The persons influenced by duty state regarded harmony and control as important, instead of, they ignored conformity. People select occupation according to individual feature, so the feature of consumers, working place environment, working place situation are different in accordance with job characteristic, as a result we can find differences in clothes selection suitable for working palace and purchasing.

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Image Watermarking Based on Feature Points of Scale-Space Representation (스케일 스페이스 특징점을 이용한 영상 워터마킹)

  • Seo, Jin-S.;Yoo, Chang-D.
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.367-370
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    • 2005
  • This paper proposes a novel method for content-based watermarking based on feature points of an image. At each feature point, watermark is embedded after affine normalization according to the local characteristic scale and orientation. The characteristic scale is the scale at which the normalized scale-space representation of an image attains a maximum value, and the characteristic orientation is the angle of the principal axis of an image. By binding watermarking with the local characteristics of an image, resilience against affine transformations can be obtained. Experimental results show that the proposed method is robust against various image processing steps including affine transformations, cropping, filtering, and JPEG compression.

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Local Linear Transform and New Features of Histogram Characteristic Functions for Steganalysis of Least Significant Bit Matching Steganography

  • Zheng, Ergong;Ping, Xijian;Zhang, Tao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.840-855
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    • 2011
  • In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

A Study on the Fractal Attractor Creation and Analysis of the Printed Korean Characters

  • Shon, Young-Woo
    • Journal of information and communication convergence engineering
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    • v.1 no.1
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    • pp.53-57
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    • 2003
  • Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

Feature Visualization and Error Rate Using Feature Map by Convolutional Neural Networks (CNN 기반 특징맵 사용에 따른 특징점 가시화와 에러율)

  • Jin, Taeseok
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.1
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    • pp.1-7
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    • 2021
  • In this paper, we presented the experimental basis for the theoretical background and robustness of the Convolutional Neural Network for object recognition based on artificial intelligence. An experimental result was performed to visualize the weighting filters and feature maps for each layer to determine what characteristics CNN is automatically generating. experimental results were presented on the trend of learning error and identification error rate by checking the relevance of the weight filter and feature map for learning error and identification error. The weighting filter and characteristic map are presented as experimental results. The automatically generated characteristic quantities presented the results of error rates for moving and rotating robustness to geometric changes.

A Study on Secondary School Student's Recognition of Vision-dependent Jump in the Geometry Proof (기하 증명에서 중학생들의 시각의존적 비약 인식에 대한 연구)

  • Kang, JeongGi
    • East Asian mathematical journal
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    • v.30 no.2
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    • pp.223-248
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    • 2014
  • Although a figure expression has a role of mediator in the geometry proof, it is not admitted to prove based on a vision-dependent feature. This study starts from the problem that although a figure expression has an important role in the geometry proof, a lot of students don't understand the limit of vision-dependent feature in the figure expression. We will investigate this problem to understand cognitive characteristic of students. Moreover, we try to get the didactical implications. To do this, we investigate the cognitive ability for a limit of vision-dependent feature, targeting a class of middle school seniors And we will have a personal interview with four students who show a lack of sense of limit of vision-dependent feature in the figure expression and two students for who it is difficult to judge that they don't understand the limit of vision-dependent feature in the figure expression. We will observe and analyzed the cognitive characteristic of six students. Based on the analysis, we will finally discuss on the didactical implications to help students understand the limit of vision-dependent feature in the figure expression.

Content-Based Image Retrieval Algorithm Using HAQ Algorithm and Moment-Based Feature (HAQ 알고리즘과 Moment 기반 특징을 이용한 내용 기반 영상 검색 알고리즘)

  • 김대일;강대성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.113-120
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    • 2004
  • In this paper, we propose an efficient feature extraction and image retrieval algorithm for content-based retrieval method. First, we extract the object using Gaussian edge detector for input image which is key frames of MPEG video and extract the object features that are location feature, distributed dimension feature and invariant moments feature. Next, we extract the characteristic color feature using the proposed HAQ(Histogram Analysis md Quantization) algorithm. Finally, we implement an retrieval of four features in sequence with the proposed matching method for query image which is a shot frame except the key frames of MPEG video. The purpose of this paper is to propose the novel content-based image retrieval algerian which retrieves the key frame in the shot boundary of MPEG video belonging to the scene requested by user. The experimental results show an efficient retrieval for 836 sample images in 10 music videos using the proposed algorithm.

Silhouette-based Gait Recognition for Variable Viewpoint (시점 변화에 강인한 실루엣 기반 게이트 인식)

  • 나진영;강성숙;정승도;최병욱
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1883-1886
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    • 2003
  • Gait is defined as "a manor of walking". It can used as a biometric measure to recognize known persons. Gait is an idiosyncratic feature determined by an individual's weight, stride length, and posture combined with characteristic motion. but its feature extracted from images varies with the viewpoint. In this paper, we propose a gait recognition method using a planer homography, which is robust for viewpoint variation. We represent an individual as key-silhouettes. And we endow key-silhouettes with weight calculated using the characteristic of PCA. Experimental result shows that proposed method is robust for viewpoint variation as images synthesised same viewpoint.

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Reliability improvement of nonlinear ultrasonic modulation based fatigue crack detection using feature-level data fusion

  • Lim, Hyung Jin;Kim, Yongtak;Sohn, Hoon;Jeon, Ikgeun;Liu, Peipei
    • Smart Structures and Systems
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    • v.20 no.6
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    • pp.683-696
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    • 2017
  • In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

Optical Head Tracker using Pattern Matching for Initial Attitude (초기자세 획득을 위한 패턴 매칭을 이용한 광학 방식 헤드 트랙커)

  • Kim, Young-Il;Park, Chan-Gook
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.5
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    • pp.470-475
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    • 2009
  • This paper is the study which is head tracker using pattern matching. Proposal algorithm obtains initial attitude of head tracker using pattern matching. Optical head tracker consists of infrared LEDs(features) which are attached helmet as pattern, stereo infrared cameras. Proposal algorithm analyzes patterns by error rate of feature distance and estimates feature characteristic number. Initial attitude of head tracker is obtained to compare map data and feature characteristic number.