• Title/Summary/Keyword: Image Labeling

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Fast Face Detection in Video Using The HCr and Adaptive Thresholding Method (HCr과 적응적 임계화에 의한 고속 얼굴 검출)

  • 신승주;최석림
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.61-71
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    • 2004
  • Recently, various techniques for face detection are studied, but most of them still have problems on processing in real-time. Therefore, in this paper, we propose novel techniques for real-time detection of human faces in sequential images using motion and chroma information. First, background model is used to find a moving area. In this procmoving area. edure, intensity values for reference images are averaged, then skin-color are detected in We use HCr color-space model and adaptive threshold method for detection. Second, binary image labeling is applied to acquire candidate regions for faces. Candidates for mouth and eyes on a face are obtained using differences between green(G) and blue(B), intensity(I) and chroma-red(Cr) value. We also considered distances between eye points and mouth on a face. Experimental results show effectiveness of real-time detection for human faces in sequential images.

A New Efficient Detection Method in Lane Road Environment (도로 환경에 효율적인 새로운 차선 검출 방법)

  • Lee, Kyung-Min;Lin, Chi-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.1
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    • pp.129-136
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    • 2018
  • In this paper, we propose a new real-time lane detection method that is efficient for road environment. Existing methods have a problem of low reliability under environmental changes. In order to overcome this problem, we emphasize the lane candidate area by using gray level division. And Extracts a straight line component near the lane by using the Hough transform, and generates an ROI for each straight line based on the extracted coordinates. And integrates the generated ROI images. Then, the lane is determined by dividing the object using the dual queue in the ROI image. The proposed method is able to detect lanes even in the environmental change unlike the conventional method. And It is possible to obtain an advantage that the area corresponding to the background such as sky, mountain, etc. is efficiently removed and high reliability is obtained.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation

  • Kang, Sung-Won;Lee, Woo-Jin;Choi, Soon-Chul;Lee, Sam-Sun;Heo, Min-Suk;Huh, Kyung-Hoe;Kim, Tae-Il;Yi, Won-Jin
    • Imaging Science in Dentistry
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    • v.45 no.1
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    • pp.7-13
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    • 2015
  • Purpose: We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). Materials and Methods: The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. Results: VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). Conclusion: It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method.

Automatic Generation of Training Character Samples for OCR Systems

  • Le, Ha;Kim, Soo-Hyung;Na, In-Seop;Do, Yen;Park, Sang-Cheol;Jeong, Sun-Hwa
    • International Journal of Contents
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    • v.8 no.3
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    • pp.83-93
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    • 2012
  • In this paper, we propose a novel method that automatically generates real character images to familiarize existing OCR systems with new fonts. At first, we generate synthetic character images using a simple degradation model. The synthetic data is used to train an OCR engine, and the trained OCR is used to recognize and label real character images that are segmented from ideal document images. Since the OCR engine is unable to recognize accurately all real character images, a substring matching method is employed to fix wrongly labeled characters by comparing two strings; one is the string grouped by recognized characters in an ideal document image, and the other is the ordered string of characters which we are considering to train and recognize. Based on our method, we build a system that automatically generates 2350 most common Korean and 117 alphanumeric characters from new fonts. The ideal document images used in the system are postal envelope images with characters printed in ascending order of their codes. The proposed system achieved a labeling accuracy of 99%. Therefore, we believe that our system is effective in facilitating the generation of numerous character samples to enhance the recognition rate of existing OCR systems for fonts that have never been trained.

Proteomic Analysis of Bovine Pregnancy-specific Serum Proteins by 2D Fluorescence Difference Gel Electrophoresis

  • Lee, Jae Eun;Lee, Jae Young;Kim, Hong Rye;Shin, Hyun Young;Lin, Tao;Jin, Dong Il
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.6
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    • pp.788-795
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    • 2015
  • Two dimensional-fluorescence difference gel electrophoresis (2D DIGE) is an emerging technique for comparative proteomics, which improves the reproducibility and reliability of differential protein expression analysis between samples. The purpose of this study was to investigate bovine pregnancy-specific proteins in the proteome between bovine pregnant and non-pregnant serum using DIGE technique. Serums of 2 pregnant Holstein dairy cattle at day 21 after artificial insemination and those of 2 non-pregnant were used in this study. The pre-electrophoretic labeling of pregnant and non-pregnant serum proteins were mixed with Cy3 and Cy5 fluorescent dyes, respectively, and an internal standard was labeled with Cy2. Labeled proteins with Cy2, Cy3, and Cy5 were separated together in a single gel, and then were detected by fluorescence image analyzer. The 2D DIGE method using fluorescence CyDye DIGE flour had higher sensitivity than conventional 2D gel electrophoresis, and showed reproducible results. Approximately 1,500 protein spots were detected by 2D DIGE. Several proteins showed a more than 1.5-fold up and down regulation between non-pregnant and pregnant serum proteins. The differentially expressed proteins were identified by MALDI-TOF mass spectrometer. A total 16 protein spots were detected to regulate differentially in the pregnant serum, among which 7 spots were up-regulated proteins such as conglutinin precursor, modified bovine fibrinogen and IgG1, and 6 spots were down-regulated proteins such as hemoglobin, complement component 3, bovine fibrinogen and IgG2a three spots were not identified. The identified proteins demonstrate that early pregnant bovine serum may have several pregnancy-specific proteins, and these could be a valuable information for the development of pregnancy-diagnostic markers in early pregnancy bovine serum.

Vehicle Information Recognition and Electronic Toll Collection System with Detection of Vehicle feature Information in the Rear-Side of Vehicle (차량후면부 차량특징정보 검출을 통한 차량정보인식 및 자동과금시스템)

  • 이응주
    • Journal of Korea Multimedia Society
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    • v.7 no.1
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    • pp.35-43
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    • 2004
  • In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

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Study on the Ship Detection Method Using SAR Imagery (SAR 영상을 이용한 선박탐지에 관한 연구)

  • Kwon, Seung-Joon;Shin, Sung-Woong
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.131-139
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    • 2009
  • The existing vessel monitoring system using the ground surveillance radar has a difficulty in monitoring ships continuously due to the limited range of detecting ships. For resolving this problem, we carry out a research on ship detection which is to be the core technology of vessel monitoring system for ocean monitoring using SAR imagery. There are two different methods of detecting ships in SAR imagery: detection of the ship target itself and detection of the ship wake. In this paper, we mainly focus on algorithms which detect the ship itself, and also present the accuracy test after extracting positional and directional figures of the ships. After rectifying input SAR imagery using polynomial transformation, we use Wiener filter to remove speckle noises. A labeling technique and morphological filtering in conjunction with Otsu's method are used to automatically detect the ships based on the image processing domain. For ground truth data, information from a radar system is used, which allows assessing the accuracy of the proposed method. The results show that the proposed method has the high potential in automatically detecting the ships and its positional/directional figures in a fast way.

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The Experimental Study of Effects of Irradiation on Osseointegration (방사선조사가 임프란트의 골유착에 미치는 영향에 관한 실험적 연구)

  • Park Kwan-Soo;Lee Sang-Rae;Hwang Eui-Hwan
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.29 no.1
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    • pp.119-147
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    • 1999
  • The purpose of this study was to investigate the effects of the Co-60 γ irradiation on the osseointegration. 2.0 mm titanium alloy screw implants(Sankin Industry Co. Ltd., Japan) were placed in the tibial metaphysis of the rabbits, bilaterally. The mean length of the implants was 6.0 mm. The right tibia was irradiated with a single dose of 15Gy from 60Co teletherapic machine at 5th postoperative day. The experimental group was irradiated tibia. The control group was non­irradiated tibia. To observe the phase of bone formation, the bone labeling by intramuscular injection of 20mg/Kg of Tetracycline, Calcein, Alizarin red S, was performed. The rabbits were sacrificed on the 1st, 2nd, 4th, 6th, 8th week and the tibia including implants were taken, and then the specimens were examined by the microradiography, light microscopy, and fluorescent microscopy. The obtained results were as follows: 1. There were connective tissue between bone and titanium at 1st week, in both group. Especially, the many empty lacunae without nucleus and obscure cytoplasm in experimental group, were observed. 2. The osteons were observed at 4th week in control group, and at 6th week in experimental group. The bone formation in experimental group was retarded as compared to the control group. 3. In fluorescent microscopy, bone labelling band was observed as linear, arc or concentric shape. Occasionary interrupted labelling band was observed, which is demonstrated bone remodeling. 4. In microradiographic examination, the radiolucent image was found between bone and implant with widening of bone marrow spaces as compared to the control group.

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Effect of eco-label recognition on corporate association and purchasing intention in fashion business (패션비즈니스에서 소비자의 에코라벨 인지도가 기업연상과 구매의도에 미치는 영향연구)

  • Shin, Sangmoo;Kim, Min Jung
    • The Research Journal of the Costume Culture
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    • v.23 no.3
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    • pp.523-536
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    • 2015
  • Corporate association-which refers to consumers' beliefs, knowledge, perceptions, and evaluations of a corporation -can affect consumers' purchasing intentions. Corporate association consists of corporate ability association and corporate social responsibility association. Corporate ability association refers to a company's product quality, corporate innovation, productivity, consumer orientation, and after service. Corporate social responsibility association, which refers to the social perspective a company has of its responsibility to society, can affect corporate image and consumers' purchasing intentions. Eco-labeling for protecting and sustaining the environment is one of the important green marketing strategies in the fashion business that can influence corporate association and consumers' purchasing intentions. The purpose of this study was to investigate the effect of consumers' eco-label recognition on their corporate association and intentions to purchase eco-friendly fashion products. Questionnaires were distributed to consumers. The 263 usable questionnaires that were returned were analyzed by descriptive statistics, Cronbach's alpha, factor analysis, regression analysis, and t-test. The results were as follows: There was a significant effect of eco-label recognition on corporate association (ability association and social responsibility association). Eco-label recognition and corporate association were found to significantly affect consumers' purchasing intentions. Regarding the eco-friendly fashion product buying experience, there was no significant difference on corporate association and buying intention, but there was significant difference on eco-label recognition.

Super-Pixels Generation based on Fuzzy Similarity (퍼지 유사성 기반 슈퍼-픽셀 생성)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.2
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    • pp.147-157
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    • 2017
  • In recent years, Super-pixels have become very popular for use in computer vision applications. Super-pixel algorithm transforms pixels into perceptually feasible regions to reduce stiff features of grid pixel. In particular, super-pixels are useful to depth estimation, skeleton works, body labeling, and feature localization, etc. But, it is not easy to generate a good super-pixel partition for doing these tasks. Especially, super-pixels do not satisfy more meaningful features in view of the gestalt aspects such as non-sum, continuation, closure, perceptual constancy. In this paper, we suggest an advanced algorithm which combines simple linear iterative clustering with fuzzy clustering concepts. Simple linear iterative clustering technique has high adherence to image boundaries, speed, memory efficient than conventional methods. But, it does not suggest good compact and regular property to the super-pixel shapes in context of gestalt aspects. Fuzzy similarity measures provide a reasonable graph in view of bounded size and few neighbors. Thus, more compact and regular pixels are obtained, and can extract locally relevant features. Simulation shows that fuzzy similarity based super-pixel building represents natural features as the manner in which humans decompose images.