• Title/Summary/Keyword: k-mean segmentation

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Relationships between lifestyle and clothing shopping orientation of Chinese female college students (중국 여대생의 라이프스타일과 의복 쇼핑성향과의 관계 연구)

  • Lee Ok-Hee
    • Korean Journal of Human Ecology
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    • v.9 no.2
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    • pp.33-42
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    • 2006
  • The purpose of this study was to identify the relationship between lifestyles and clothing shopping orientation. A questionnaire was developed to measure the lifestyle and shopping orientation of Chinese female college students. The questionnaire was distributed and collected from 217 college female students in China. The data was analyzed by mean, standard deviation, factor analysis, reliability test, MANOVA and ANOVA by SPSS package. The lifestyles of the respondents were classified into four types such as Open-mindedness, Accomplishment, Sociability, and Activities. And shopping orientation was classified into five types such as Recreational shopping, Speediness, Economic shopping, Shop and brand royalty, and Self-confidence. The result of this study were as follows; Consumers of open-minded lifestyle tended to economic and self-confident shopping. The higher accomplishment was, the higher speediness and economic shopping were. Consumers of sociable lifestyle tended to recreational, speediness, and self-confidence. The higher activities was, the higher economic shopping was. The shop and brand royalty was not shown to have the significant differences according to all of lifestyle groups. It is the factor that lifestyle were important in the clothing market segmentation of Chinese female college students

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Welding Bead Detection Inspection Using the Brightness Value of Vertical and Horizontal Direction (수직 및 수평 방향의 밝깃값을 이용한 용접 비드 검출 검사)

  • Jae Eun Lee;Jong-Nam Kim
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.241-248
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    • 2022
  • Shear Reinforcement of Dual Anchorage(SRD) is used to reinforce the safety of reinforced concrete structures at construction sites. Welding is used to make shear reinforcement, and welding plays an important role in determining productivity and competitiveness of products. Therefore, a weld bead detection inspection is required. In this paper, we suggest an algorithm for inspecting welding beads using image data of welding beads. First, the proposed algorithm calculates a brightness value in a vertical direction in an image, and then divides a welding bead in a vertical direction by finding a position corresponding to a 50% height point of the brightness value distribution in the image. The welding bead area is also divided in the same way for the horizontal direction, and then the segmentation image is analyzed if there is a welding bead. The proposed algorithm reduced the amount of computation by performing analysis after specifying the region of interest. In addition, accuracy could be improved by using all brightness values in the vertical and horizontal directions using the difference of brightness between the base metal and the welding bead region in the SRD image. The experiment compared the analysis results using five algorithms, such as K-mean and K-neighborhood, as a method to detect if there is a welding bead, and the experimental result proved that the proposed algorithm was the most accurate.

Fracture Characteristics and Segmentation of Yangsan Fault around Mt. Namsan, Gyeongju City, Korea (경주 남산 일대의 단열구조 특성과 양산단층의 분절)

  • Kim, Heon-Joo;Chang, Tae-Woo
    • The Journal of Engineering Geology
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    • v.19 no.1
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    • pp.51-61
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    • 2009
  • Fractures and segmentation in association with the activities of the Yangsan fault are studied around Mt. Namsan, Gyengju city in the southeastern part of Korea. It is believed that the higher values of joint density and fractal dimension with the approach of the center of the Yangsan fault mean intense fracturing due to the fault activity. The boundary between fault damage zone and host rock is inferred to be placed at about 2.7 km from the center of the Yangsan fault where the values of joint density and fractal dimension abruptly decrease and the orientations of joint are also much dispersed. The small faults within the damage zone of the Yangsan fault are definitely divided into right-lateral and left-lateral strike-slip faults. The former is considered to be formed during the right-lateral movement of the Yangsan fault and the latter during the left-lateral movement. The Yangsan fault is segmented in the study area with obvious evidences as follows: (1) the difference of fault strike between northern and southern segments, (2) The geometry of contractional imbricate fans and syncline plunging $9^{\circ}$, $S85^{\circ}E$ at the end of northern segment, and (3) anticline plunging $28^{\circ}$, $N4^{\circ}W$ at the end of southern segment.

Color image segmentation by level set method (레벨셋 기법을 이용한 컬러 이미지 분할)

  • Yoo, Ju-Han;Jung, Moon-Ryul
    • Journal of the Korea Computer Graphics Society
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    • v.18 no.2
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    • pp.9-15
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    • 2012
  • In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

Real-Time Lane Detection Based on Inverse Perspective Transform and Search Range Prediction (역 원근 변환과 검색 영역 예측에 의한 실시간 차선 인식)

  • Jeong, Seung-Gweon;Kim, In-Soo;Kim, Sung-Han;Lee, Dong-Hwoal;Yun, Kang-Sup;Lee, Man-Hyung
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.3
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    • pp.68-74
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    • 2001
  • A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.

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A Hybrid Proposed Framework for Object Detection and Classification

  • Aamir, Muhammad;Pu, Yi-Fei;Rahman, Ziaur;Abro, Waheed Ahmed;Naeem, Hamad;Ullah, Farhan;Badr, Aymen Mudheher
    • Journal of Information Processing Systems
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    • v.14 no.5
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    • pp.1176-1194
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    • 2018
  • The object classification using the images' contents is a big challenge in computer vision. The superpixels' information can be used to detect and classify objects in an image based on locations. In this paper, we proposed a methodology to detect and classify the image's pixels' locations using enhanced bag of words (BOW). It calculates the initial positions of each segment of an image using superpixels and then ranks it according to the region score. Further, this information is used to extract local and global features using a hybrid approach of Scale Invariant Feature Transform (SIFT) and GIST, respectively. To enhance the classification accuracy, the feature fusion technique is applied to combine local and global features vectors through weight parameter. The support vector machine classifier is a supervised algorithm is used for classification in order to analyze the proposed methodology. The Pascal Visual Object Classes Challenge 2007 (VOC2007) dataset is used in the experiment to test the results. The proposed approach gave the results in high-quality class for independent objects' locations with a mean average best overlap (MABO) of 0.833 at 1,500 locations resulting in a better detection rate. The results are compared with previous approaches and it is proved that it gave the better classification results for the non-rigid classes.

Real-time moving object tracking and distance measurement system using stereo camera (스테레오 카메라를 이용한 이동객체의 실시간 추적과 거리 측정 시스템)

  • Lee, Dong-Seok;Lee, Dong-Wook;Kim, Su-Dong;Kim, Tae-June;Yoo, Ji-Sang
    • Journal of Broadcast Engineering
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    • v.14 no.3
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    • pp.366-377
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    • 2009
  • In this paper, we implement the real-time system which extracts 3-dimensional coordinates from right and left images captured by a stereo camera and provides users with reality through a virtual space operated by the 3-dimensional coordinates. In general, all pixels in correspondence region are compared for the disparity estimation. However, for a real time process, the central coordinates of the correspondence region are only used in the proposed algorithm. In the implemented system, 3D coordinates are obtained by using the depth information derived from the estimated disparity and we set user's hand as a region of interest(ROI). After user's hand is detected as the ROI, the system keeps tracking a hand's movement and generates a virtual space that is controled by the hand. Experimental results show that the implemented system could estimate the disparity in real -time and gave the mean-error less than 0.68cm within a range of distance, 1.5m. Also It had more than 90% accuracy in the hand recognition.

Surficial Sediment Classification using Backscattered Amplitude Imagery of Multibeam Echo Sounder(300 kHz) (다중빔 음향 탐사시스템(300 kHz)의 후방산란 자료를 이용한 해저면 퇴적상 분류에 관한 연구)

  • Park, Yo-Sup;Lee, Sin-Je;Seo, Won-Jin;Gong, Gee-Soo;Han, Hyuk-Soo;Park, Soo-Chul
    • Economic and Environmental Geology
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    • v.41 no.6
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    • pp.747-761
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    • 2008
  • In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.

Intra-Rater and Inter-Rater Reliability of Brain Surface Intensity Model (BSIM)-Based Cortical Thickness Analysis Using 3T MRI

  • Jeon, Ji Young;Moon, Won-Jin;Moon, Yeon-Sil;Han, Seol-Heui
    • Investigative Magnetic Resonance Imaging
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    • v.19 no.3
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    • pp.168-177
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    • 2015
  • Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis does not require complicated 3D segmentation of brain gray/white matters. Instead, this technique uses the local intensity profile to compute cortical thickness. The aim of the present study was to evaluate intra-rater and inter-rater reliability of BSIM-based cortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years) were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo (SPGR) images were obtained using 3T MRI. BSIM-based processing steps included an inhomogeneity correction, intensity normalization, skull stripping, atlas registration, extraction of intensity profiles, and calculation of cortical thickness. Processing steps were automatic, with the exception of semiautomatic skull stripping. Individual cortical thicknesses were compared to a database indicating mean cortical thickness of healthy adults, in order to produce Z-score thinning maps. Intra-class correlation coefficients (ICCs) were calculated in order to evaluate inter-rater and intra-rater reliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 in brain regions except the right occipital, left anterior cingulate, and left and right cerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fair to excellent in most regions, poor inter-rater correlations were observed for the cingulate and occipital regions. Processing time, including manual skull stripping, was $17.07{\pm}3.43min$. Z-score maps for all participants indicated that cortical thicknesses were not significantly different from those in the comparison databases of healthy adults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intra-rater and inter-rater reliability. We therefore suggest BSIM-based cortical thickness analysis as an adjunct clinical tool to detect cortical atrophy.

PIV System for the Flow Pattern Anaysis of Artificial Organs ; Applied to the In Vitro Test of Artificial Heart Valves

  • Lee, Dong-Hyeok;Seh, Soo-Won;An, Hyuk;Min, Byoung-Goo
    • Journal of Biomedical Engineering Research
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    • v.15 no.4
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    • pp.489-497
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    • 1994
  • The most serious problems related to the cardiovascular prothesis are thrombosis and hemolysis. It is known that the flow pattern of cardiovascular prostheses is highly correlated with thrombosis and hemolysis. Laser Doppler Anemometry (LDA) is a usual method to get flow pattern, which is difficult to operate and has narrow measure region. Particle Image Velocimetry (PIV) can solve these problems. Because the flow speed of valve is too high to catch particles by CCD camera, high-speed camera (Hyspeed : Holland-Photonics) was used. The estimated maximum flow speed was 5m/sec and maximum trackable length is 0.5 cm, so the shutter speed was determined as 1000 frames per sec. Several image processing techniques (blurring, segmentation, morphology, etc) were used for the preprocessing. Particle tracking algorithm and 2-D interpolation technique which were necessary in making gridrized velocity pronto, were applied to this PIV program. By using Single-Pulse Multi-Frame particle tracking algorithm, some problems of PIV can be solved. To eliminate particles which penetrate the sheeted plane and to determine the direction of particle paths are these solving methods. 1-D relaxation fomula is modified to interpolate 2-D field. Parachute artificial heart valve which was developed by Seoul National University and Bjork-Shiely valve was testified. For each valve, different flow pattern, velocity profile, wall shear stress and mean velocity were obtained.

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