• Title/Summary/Keyword: Image Use

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An Empirical Study of Two-Way Effects on Country Image of KOREA and Corporate Image - A Focus on Chinese Consumer of SAMSUNG Electronics - (한국 국가이미지와 기업이미지간의 상호효과에 대한 실증연구 -삼성전자의 중국소비자를 중심으로-)

  • Lee, Chun-Su;Lee, Jang-Rho;Seo, Min-Kyo
    • International Commerce and Information Review
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    • v.8 no.4
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    • pp.323-341
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    • 2006
  • IThis research meets with empirical results in pursuit of aim as below mentioned. Firstly, it gets a line on two-way effects which have an effect on both (the country image and corporate image) by using the corporate image for the study of the country image. After making an analysis of the empirical test, found out that the corporate image has influence upon the country image significantly. Also found out that the country image has an effect on the corporate image powerfully. Therefore, it effects an inspection of evidence that the country image and corporate image have significantly positive concern, each other. Secondly, it is offering the way to use the culture marketing as grasping the mediating effects, which culture difference has influence upon the country image and the corporate image. The mediating effects show that the country image has influence on the corporate image more as culture difference is bigger.

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Image restoration based on wavelet filter bank (웨이블렛 필터 뱅크를 이용한 영상복원)

  • 김주헌;이종수
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1387-1390
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    • 1997
  • In this paper we propose a novel way to restore degraded image using wavelet transform & filterbank. First, we devide a degraded image into 4-suband images using UDWT(Undecimated Wavelet Transform), and then use a proper CLS (Constrained Least Square) filter in each subband. Using a proper CLS filter ineach subband, we can save high grequency components of original image. We reconstruct a restored image from the downsampled subband images using wavelet tansform. Even though there is a trade-off between ISNR and calculation loads, we reduce the calculation loads by using wavelet transform in reconstruction with a negligible degradatiion in ISNR.

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Fast iterative image restoration algorithms based on preconditioning (전처리기를 사용한 반복적 영상복원의 고속화 기법)

  • 백준기;문준일;김상구
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.12
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    • pp.62-70
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    • 1996
  • Image restoration is the process which estimates the original image form the blurred image observed by the non-ideal imaging system with additivenoise. According to the regularized approach, the resotred image can be obtained by iterative methods or the constrained least square error(CLS) filter. Among those retoratin methods, despite of many advantages, iterative iamge restoration is limited in use because of slow convergence. In the present paper, fast iterative image restoration algorithms based on preconditoning are proposed. The preconditioner can be obtained by using the characteristics finite impulse response (FIR) filter structure.

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Enhanced Image Magnification Using Edge Information (에지정보를 이용한 개선된 영상확대기법)

  • Je, Sung-Kwan;Cho, Jae-Hyun;Cha, Eui-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.12
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    • pp.2343-2348
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    • 2006
  • Image magnification is among the basic image processing operations. The most commonly used technique for image magnification are based on interpolation method(such as nearest neighbor, bilinear and cubic interpolation). However, the magnified images produced by the techniques that often appear a variety of undesirable image artifacts such as 'blocking' and 'blurring' or too takes the processing time into the several processing for image magnification. In this paper, we propose image magnification method which uses input image's sub-band information such as edge information to enhance the image magnification method. We use the whole image and not use the one's neighborhood pixels to detect the edge information of the image that isn't occurred the blocking phenomenon. And then we emphasized edge information to remove the blurring phenomenon which incited of edge information. Our method, which improves the performance of the traditional image magnification methods in the processing time, is presented. Experiment results show that the proposed method solves the drawbacks of the image magnification such as blocking and blurring phenomenon, and has a higher PSNR and Correlation than the traditional methods.

ROI Based Real Time Image Stitching Using the Directionality of the Image (영상의 방향성을 이용한 ROI 기반 실시간 파노라마 영상 정합)

  • Nam, Ki-Hun;Choi, Se-Jin
    • Journal of IKEEE
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    • v.20 no.4
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    • pp.420-423
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    • 2016
  • In this paper, we proposed an implementation of panoramic image stitching that operates in real time at the embedded environment by applying ROI based PROSAC algorithm using the directionality of the image. The conventional panoramic image stitching applies SURF or SIFT algorithm which contains unnecessary computation and a lots of data to detect feature points. In this paper, we use the direction of the input image and we proposed the method of reducing the unnecessary computation by using ROI. We use a gyro sensor and an acceleration sensor. Output data from gyro and acceleration sensors can be calibrated by complementary filter. The calibration does not affect the operating time of the proposed image stitching algorithm in embedded environment. Therefore, it is possible to operate in real-time.

Automatic Extraction of Component Window for Auto-Teaching of PCB Assembly Inspection Machines (PCB 조립검사기의 자동티칭을 위한 부품윈도우 자동추출 방법)

  • Kim, Jun-Oh;Park, Tae-Hyoung
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1089-1095
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    • 2010
  • We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

A Study on Refinement Strategy for the National Image-With Emphasis on the Strategic Use of design (국가 이미지의 개선전략에 관한 연구-디자인의 전략적 활용을 중심으로-)

  • 정경원
    • Archives of design research
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    • v.14
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    • pp.221-230
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    • 1996
  • The paper aims to identify how Korean national image can be refined through the strategic use of design. There has been a distinctive need for refining the national image in Korea in recent years in accordance with the rapid growth of the nation's wealth. A comprehensive definition on nation image was prepared through a course of library search. The role of design in the establishment of national image was identified as a result of case study on the United States of America and Japan. Major problems were revealed through an analysis of current states of Korean national image. Finally, strategic suggestions for refining Korean national image have bl'en prepared in relation to the overall direction and specified guidelines.

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The Inner Pipeline Scanning Method by Digital Image Processing and Lens Combination (영상처리기법과 렌즈조합에 의한 관로내 탐사기법)

  • Kim, Won-Dae
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.67-73
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    • 2008
  • The most common method of pipeline inspection is to use a remote-controlled-machine equipped with a CCTV, which, however, has many limitations to accurately inspect pipeline condition. In case of a typical CCTV, since the camera looks at the end point of the pipe, the locations of the defects and distance-readings are often different. In addition, the quality and accuracy of the inspection is highly dependent on the operator's skill and experience. In this research a new system is developed by use of the image processing techniques and the lens combination. The image acquisition system is developed that acquires the front and the side view of the pipe simultaneously. Side view unwrapping and stitching technology using image process techniques are developed which delivers high resolution image data.

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CNN-based Gesture Recognition using Motion History Image

  • Koh, Youjin;Kim, Taewon;Hong, Min;Choi, Yoo-Joo
    • Journal of Internet Computing and Services
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    • v.21 no.5
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    • pp.67-73
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    • 2020
  • In this paper, we present a CNN-based gesture recognition approach which reduces the memory burden of input data. Most of the neural network-based gesture recognition methods have used a sequence of frame images as input data, which cause a memory burden problem. We use a motion history image in order to define a meaningful gesture. The motion history image is a grayscale image into which the temporal motion information is collapsed by synthesizing silhouette images of a user during the period of one meaningful gesture. In this paper, we first summarize the previous traditional approaches and neural network-based approaches for gesture recognition. Then we explain the data preprocessing procedure for making the motion history image and the neural network architecture with three convolution layers for recognizing the meaningful gestures. In the experiments, we trained five types of gestures, namely those for charging power, shooting left, shooting right, kicking left, and kicking right. The accuracy of gesture recognition was measured by adjusting the number of filters in each layer in the proposed network. We use a grayscale image with 240 × 320 resolution which defines one meaningful gesture and achieved a gesture recognition accuracy of 98.24%.

Development of ResNet-based WBC Classification Algorithm Using Super-pixel Image Segmentation

  • Lee, Kyu-Man;Kang, Soon-Ah
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.147-153
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    • 2018
  • In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.