• Title/Summary/Keyword: Shape Classification

Search Result 842, Processing Time 0.03 seconds

글꼴 분류를 위한 한글 글꼴의 모양 특성 연구 (Shape Property Study of Hangul Font for Font Classification)

  • 김현영;임순범
    • 한국멀티미디어학회논문지
    • /
    • 제20권9호
    • /
    • pp.1584-1595
    • /
    • 2017
  • Each cultural community has developed a variety of fonts to express their own language and characters. Hangul has also diversified its font shapes through changing the composition ratio and look of the consonants and vowels. Rather, thanks to the variety of these fonts, a considerable amount of time and effort must be devoted to the selection of a specific font shape. This is related to the fact that the current Hangul service and classification system process the font only with its name or the name of the manufacturer. It means that there is no consensus about the font shape classification system for Hangul. In this study, we propose a shape property set that can be a basis for classifying Hangul fonts. The font shape property set was generated by performing statistical analysis with features which have been studied by the font design experts and was verified through questionnaire using representative fonts based on the classification scheme defined by the Hangul font design classification system standard. This study is meaningful in that it is a study on shape classification properties of K-means and PCA statistical techniques based on font data rather than design field study.

노년여성의 족저 형태에 따른 인솔 패턴 개발 연구 (Development of Insole Pattern Depending on the Footprint Shape of Elder Women)

  • 이지은;권영아
    • 한국감성과학회:학술대회논문집
    • /
    • 한국감성과학회 2008년도 추계학술대회
    • /
    • pp.122-125
    • /
    • 2008
  • Even though many researchers studied the foot shape and dimension, those applications lacked. The purpose of this study was to develop insole pattern of elderly women according to footprint. Discrepancy in the classification criteria among of foot parameters complicates attempts for elderly women classification of foot sole. To develop a footprint-based classification technique for the classification of foot sole types by allowing simultaneous use of several parameters. Foot sole data from static standing footprints were recorded from 48 elderly women. The factors of footprint shape were determined. Cluster analysis was applied to obtain individual foot sole classifications. The classification model of foot insole is proposed for a classification of footprint in elderly women. An application of ANOVA, Duncan's analysis, frequency analysis, factor analysis, and cluster analysis have been made to footprint data. In order to make clear foot sole characteristics, the factors of footprint shape have been discussed. The results are as follows. The factors of footprint shape have been classified into four types: foot length, sole slope, outside sole slope, and foot width. The types of foot sole shape have been classified into four types: longed, shortened, outside sloped, and toes sloped.

  • PDF

Shape-Based Classification of Clustered Microcalcifications in Digitized Mammograms

  • Kim, J.K.;Park, J.M.;Song, K.S.;Park, H.W.
    • 대한의용생체공학회:의공학회지
    • /
    • 제21권2호
    • /
    • pp.137-144
    • /
    • 2000
  • Clustered microcalcifications in X-ray mammograms are an important sign for the diagnosis of breast cancer. A shape-based method, which is based on the morphological features of clustered microcalcifications, is proposed for classifying clustered microcalcifications into benign or malignant categories. To verify the effectiveness of the proposed shape features, clinical mammograms were used to compare the classification performance of the proposed shape features with those of conventional textural features, such as the spatial gray-leve dependence method and the wavelet-based method. Image features extracted from these methods were used as inputs to a three-layer backpropagation neural network classifier. The classification performance of features extracted by each method was studied by using receiver operating-characteristics analysis. The proposed shape features were shown to be superior to the conventional textural features with respect to classification accuracy.

  • PDF

Shape Recognition and Classification Based on Poisson Equation- Fourier-Mellin Moment Descriptor

  • Zou, Jian-Cheng;Ke, Nan-Nan;Lu, Yan
    • International Journal of CAD/CAM
    • /
    • 제8권1호
    • /
    • pp.69-72
    • /
    • 2009
  • In this paper, we present a new shape descriptor, which is named Poisson equation-Fourier-Mellin moment Descriptor. We solve the Poisson equation in the shape area, and use the solution to get feature function, which are then integrated using Fourier-Mellin moment to represent the shape. This method develops the Poisson equation-geometric moment Descriptor proposed by Lena Gorelick, and keeps both advantages of Poisson equation-geometric moment and Fourier-Mellin moment. It is proved better than Poisson equation-geometric moment Descriptor in shape recognition and classification experiments.

한글 글꼴 등록 시스템을 위한 글꼴 모양 분류체계 표준화 연구 (Standardization Study of Font Shape Classification for Hangul Font Registration System)

  • 김현영;임순범
    • 한국멀티미디어학회논문지
    • /
    • 제20권3호
    • /
    • pp.571-580
    • /
    • 2017
  • Recently, there are many communication softwares based on text on various smart devices. Unlike traditional print publishing, mobile publishing and SNS tools tends to utilize more decorative or more emotional fonts so that users can pass some feelings from contents. So font providers have released new fonts which deal with the requirements of the market. Nevertheless being released lots of new fonts, general users have not used them because they searched only by font name or font provider's name. It means that there is no way for users to know and find new things. In this study, we suggest font shape classification rules for font registration system based on font design features. We proved the validity of classification standard study through some experiments with 50 commercial fonts. Also the result of this study was provided for Korea Telecommunication Technology Association and adopted by the Korea industrial standard.

표적분할 신뢰도 값 기반의 형태특징과 지역특징을 이용한 차량표적 분류기법 연구 (A Study on Vehicle Target Classification Method Using Both Shape and Local Features with Segmentation Reliability)

  • 양동원;이용헌;곽동민
    • 한국군사과학기술학회지
    • /
    • 제20권1호
    • /
    • pp.40-47
    • /
    • 2017
  • To classify the vehicle targets automatically using thermal images, there are usually two main categories of feature extraction method, local and shape feature extraction methods. Since thermal images have less texture information than color images, the shape feature extraction method is useful when the segmentation results are correct. However, if there are some errors in target segmentation, the shape feature may contain some errors, then the classification accuracy can be decreased. To overcome these problems, in this paper, we propose the segmentation reliability estimation method for target classification. The segmentation reliability can be estimated by using the difference information of average intensities and edge energies between the target and the background area. The estimated segmentation reliability is applied in the decision level fusion method of classification results using both shape and local features. Experiment results using the thermal images of the vehicle targets (main battle tank, armored personnel carrier, military truck, and an estate car) show that the proposed classification method and the segmentation reliability estimation method have a good performance in classification accuracy.

신경회로망을 이용한 고주파 전기 저항 용접 파이프의 비드 형상 분류 (A Bead Shape Classification Method using Neural Network in High Frequency Electric Resistance Welding)

  • Ko, K.W.;Kim, J.H.;Kong, W.I.
    • 한국정밀공학회지
    • /
    • 제12권9호
    • /
    • pp.86-94
    • /
    • 1995
  • Bead shape in high frequency electric resistance (HER) pipe welding gives useful information on judging current welding conditon. In most welding process, heat input is controlled by skilled operators observing color and shape of bead. In this paper, a visual monitoring system is designed to observe bead shape in HERW pipe welding process by using structured light beam and a C.I.D(Charge injection device) camera. To avoid some difficul- ties arising in extracting stable features of stripe pattern and classifying the extracted features, Kohonen neural network is used to classify such bead shapes. The experimental results show accurate classification performance of the proposed method.

  • PDF

사상체질진단툴 2를 활용한 사상체질 분류 인자 연구 (A Study on Sasang Constitutional Classification Factor using Sasang Constitutional Analysis Tool 2)

  • 김은주;서승호;박성은;나창수;손홍석
    • 사상체질의학회지
    • /
    • 제30권3호
    • /
    • pp.40-47
    • /
    • 2018
  • Objectives The purpose of this study is to analyze the factors contributing to the classification of Sasang Constitution using Sasang Constitutional Analysis Tool 2. Methods A total of 99 subjects were assessed for the classification of Sasang Constitution using four measurement factors (face, voice, body shape, and questionnaire information) of Sasang Constitutional Analysis Tool 2. Results Taeeumin had significantly higher body weight and BMI. In the result of the agreement between the judgment of the four measurement factors and the final judgment of Sasang Constitution, the agreement degree of Soeumin was the highest value of 2.6. Taeeumin, Soeumin, and Soyangin showed the highest agreement with the individual judgment of face, body shape and questionnaire, and body shape, respectively. Conclusions It is difficult to conclude that any individual factor contributes significantly to the classification of Sasang Constitution. Further study on Sasang Constitutional Analysis Tool 2 involving more peoples is needed in order to determine the factors contributing to the classification of Sasang Constitution.

영상분류문제를 위한 역전파 신경망과 Support Vector Machines의 비교 연구 (A Comparison Study on Back-Propagation Neural Network and Support Vector Machines for the Image Classification Problems)

  • 서광규
    • 한국산학기술학회논문지
    • /
    • 제9권6호
    • /
    • pp.1889-1893
    • /
    • 2008
  • 본 논문은 영상 분류 문제를 위한 support vector machines (SVMs)의 적용을 통한 분류의 성능을 다루고 있다. 본 연구에서는 영상 분류 문제에서 자연영상을 대상으로 색상, 질감, 형상 특징벡터를 추출하고, 각각의 특징벡터와 이들을 결합한 특징벡터를 사용하여 역전파 신경망과 SVM 기반의 방법을 적용하여 영상 분류의 정확성을 비교한다. 실험결과는 각각의 특징벡터중에는 색상 특징벡터값을 이용한 영상 분류가 그리고 각각의 특징벡터보다는 이들을 결합한 특징벡터를 이용한 영상 분류가 보다 우수함을 보여준다. 그리고 알고리즘간의 비교에서는 정확성과 일반화성능 측면에서 역전파 신경망보다 SVMs이 우수함을 보였다.