• 제목/요약/키워드: Average image ratio

검색결과 268건 처리시간 0.18초

광촉각 센서와 힘/역학센서의 퍼지융합을 통한 접촉면의 인식 (Recognition of contact surfaces using optical tactile and F/T sensors integrated by fuzzy fusion algorithm)

  • 고동환;한헌수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.628-631
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    • 1996
  • This paper proposes a surface recognition algorithm which determines the types of contact surfaces by fusing the information collected by the multisensor system, consisted of the optical tactile and force/torque sensors. Since the image shape measured by the optical tactile sensor system, which is used for determining the surface type, varies depending on the forces provided at the measuring moment, the force information measured by the f/t sensor takes an important role. In this paper, an image contour is represented by the long and short axes and they are fuzzified individually by the membership function formulated by observing the variation of the lengths of the long and short axes depending on the provided force. The fuzzified values of the long and short axes are fused using the average Minkowski's distance. Compared to the case where only the contour information is used, the proposed algorithm has shown about 14% of enhancement in the recognition ratio. Especially, when imposing the optimal force determined by the experiments, the recognition ratio has been measured over 91%.

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농산물 및 미립자의 기하학적 특성 분석을 위한 컴퓨터 시각 시스템(I) -자동(自動) 문턱값 설정(設定) 알고리즘- (Computer Vision System for Analysis of Geometrical Characteristics of Agricultural Products and Microscopic Particles (I) -Algorithms for Automatic Threshold Selection-)

  • 이종환;노상하
    • Journal of Biosystems Engineering
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    • 제17권2호
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    • pp.132-142
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    • 1992
  • The main objective of this paper is to evaluate and modify the existing algorithms for the automatic threshold selection. Four existing algorithms were evaluated quantitatively using test images of coffee droplets and an apple. The images had the different area ratio of the object to the image size, different average gray values between the object and the background, and different S/N ratio of the Gaussian noise. The result showed that Histogram Clustering Method and Maximum Entropy Method were better than Moment Preserving Method and Simple Image Statistic Method in automatic thresholding.

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흉부 전·후방향 검사 시 고관전압 및 산란선 후처리 소프트웨어 적용이 화질과 선량에 미치는 영향 (Effect of High Tube Voltage and Scatter Ray Post-processing Software on Image Quality and Radiation Dose During Chest Anteroposterior Radiography)

  • 김종석;주영철;이승근
    • 대한방사선기술학회지:방사선기술과학
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    • 제44권4호
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    • pp.295-300
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    • 2021
  • This study aims to present new chest AP examination exposure conditions through a study on the effect on image quality and patient dose by applying high tube voltage and scatter ray post-processing software during chest AP examination in digital radiography equipment. This study was used a human body phantom and in the chest AP position, the dosimeter was placed horizontally at the thoracic spine 6. The experiment was conducted by dividing into a low tube voltage (70 kVp, 400 mA, 3.2 mAs) group and a high tube voltage (100 kVp, 400 mA, 1.2 mAs) group. The collimation size (14″× 17″) and the source to image receptor distance(110 cm) were same applied to both groups. Radiation dose was presented to dose area product and entrance surface dose. Image quality was compared and analyzed by comparing the difference between the signal-to-noise ratio and the contrast-to-noise ratio of the image according to the application of the scatter ray post-processing software under each condition. The average value of the entrance surface dose in the low and high tube voltage conditions was 93.04±0.45 µGy and 94.25±1.51 µGy, which was slightly higher in the high tube voltage condition, but the dose area product was 0.97±0.04 µGy and 0.93±0.01 µGy. There was a statistically significant difference in the group mean value(p<0.01). In terms of image quality, the values of the signal-to-noise ratio and the contrast noise ratio were higher in the high tube voltage than in the low tube voltage, and decreased when the scattering line post-processing function was used, but the contrast resolution was improved. If there is a scatter ray post-processing function during chest AP examination, it is helpful to actively utilize it to improve the image quality. However, when this function is not available, I thought that applying a higher tube voltage state than a low tube voltage state will help to realize images with a large amount of information without changing the dose.

얼굴 방향에 기반을 둔 컴퓨터 화면 응시점 추적 (A Gaze Tracking based on the Head Pose in Computer Monitor)

  • 오승환;이희영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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    • pp.227-230
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    • 2002
  • In this paper we concentrate on overall direction of the gaze based on a head pose for human computer interaction. To decide a gaze direction of user in a image, it is important to pick up facial feature exactly. For this, we binarize the input image and search two eyes and the mouth through the similarity of each block ( aspect ratio, size, and average gray value ) and geometric information of face at the binarized image. We create a imaginary plane on the line made by features of the real face and the pin hole of the camera to decide the head orientation. We call it the virtual facial plane. The position of a virtual facial plane is estimated through projected facial feature on the image plane. We find a gaze direction using the surface normal vector of the virtual facial plane. This study using popular PC camera will contribute practical usage of gaze tracking technology.

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Implementation of 3D Moving Target-Tracking System based on MSE and BPEJTC Algorithms

  • Ko, Jung-Hwan;Lee, Maeng-Ho;Kim, Eun-Soo
    • Journal of Information Display
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    • 제5권1호
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    • pp.41-46
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    • 2004
  • In this paper, a new stereo 3D moving-target tracking system using the MSE (mean square error) and BPEJTC (binary phase extraction joint transform correlator) algorithms is proposed. A moving target is extracted from the sequential input stereo image by applying a region-based MSE algorithm following which, the location coordinates of a moving target in each frame are obtained through correlation between the extracted target image and the input stereo image by using the BPEJTC algorithm. Through several experiments performed with 20 frames of the stereo image pair with $640{\times}480$ pixels, we confirmed that the proposed system is capable of tracking a moving target at a relatively low error ratio of 1.29 % on average at real time.

이미지 자동배치를 위한 얼굴 방향성 검출 (Detection of Facial Direction for Automatic Image Arrangement)

  • 동지연;박지숙;이환용
    • Journal of Information Technology Applications and Management
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    • 제10권4호
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    • pp.135-147
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    • 2003
  • With the development of multimedia and optical technologies, application systems with facial features hare been increased the interests of researchers, recently. The previous research efforts in face processing mainly use the frontal images in order to recognize human face visually and to extract the facial expression. However, applications, such as image database systems which support queries based on the facial direction and image arrangement systems which place facial images automatically on digital albums, deal with the directional characteristics of a face. In this paper, we propose a method to detect facial directions by using facial features. In the proposed method, the facial trapezoid is defined by detecting points for eyes and a lower lip. Then, the facial direction formula, which calculates the right and left facial direction, is defined by the statistical data about the ratio of the right and left area in facial trapezoids. The proposed method can give an accurate estimate of horizontal rotation of a face within an error tolerance of $\pm1.31$ degree and takes an average execution time of 3.16 sec.

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Fiber orientation distribution of reinforced cemented Toyoura sand

  • Safdar, Muhammad;Newson, Tim;Waseem, Muhammad
    • Geomechanics and Engineering
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    • 제30권1호
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    • pp.67-73
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    • 2022
  • In this study, the fiber orientation distribution (FOD) is investigated using both micro-CT (computerized tomography) and image analysis of physically cut specimens prepared from Polyvinyl Alcohol (PVA) fiber reinforced cemented Toyoura sand. The micro-CT images of the fiber reinforced cemented sand specimens were visualized in horizontal and vertical sections. Scans were obtained using a frame rate of two frames and an exposure time of 500 milliseconds. The number of images was set to optimize and typically resulted in approximately 3000 images. Then, the angles of the fibers for horizontal sections and in vertical section were calculated using the VGStudio MAX software. The number of fibers intersecting horizontal and vertical sections are counted using these images. A similar approach was used for physically cut specimens. The variation of results of fiber orientation between micro-CT scans and visual count were approximately 4-8%. The micro-CT scans were able to precisely investigate the fiber orientation distribution of fibers in these samples. The results show that 85-90% of the PVA fibers are oriented between ±30° of horizontal, and approximately 95% of fibers have an orientation that lies within ±45° of the horizontal plane. Finally, a comparison of experimental results with the generalized fiber orientation distribution function 𝜌(θ) is presented for isotropic and anisotropic distribution in fiber reinforced cemented Toyoura sand specimens. Experimentally, it can be seen that the average ratio of the number of fibers intersecting the finite area on a vertical plane to number of fibers intersecting the finite area on a horizontal plane (NVtot/NHtot) cut through a sample varies from 2.08 to 2.12 (an average ratio of 2.10 is obtained in this study). Based up on the analytical predictions, it can be seen that the average NVtot/NHtot ratio varies from 2.13 to 2.17 for varying n values (an average ratio of 2.15).

Effect of Additive Composition on Mechanical Properties of Silicon Carbide Sintered with Aluminum Nitride and Erbium Oxide

  • Lee, Sung-Hee;Kim, Young-Wook
    • 한국세라믹학회지
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    • 제42권1호
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    • pp.16-21
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    • 2005
  • The effect of additive composition, using AlN and $Er_{2}O_{3}$ as sintering additives, on the mechanical properties of liquid-phase-sintered, and subsequently annealed SiC ceramics was investigated. The microstructures developed were quantitatively analyzed by image analysis. The average thickness of SiC grains increased with increasing the $Er_{2}O_{3}/(AlN + Er_{2}O_{3})$ ratio in the additives whereas the aspect ratio decreased with increasing the ratio. The mechanical properties versus $Er_{2}O_{3}/(AlN + Er_{2}O_{3})$ ratio curve had a maximum; i.e., there was a small composition range at which optimum mechanical properties were realized. The best results were obtained when the ratio ranged from 0.4 to 0.6. The flexural strength and fracture toughness of the SiC ceramics were $550\~650\;MPa$ and $5.5\~6.5$ MPa${\cdot}m^{1/2}$, respectively.

주성분분석(PCA)기반 포유류의 얼굴 비율 연구 - 인간과 동물 20종을 중심으로 (A Study on the Face Ratio of Mammals Based on Principal Components Analysis (PCA) - Focus on 20 Species of Animals and Humans)

  • 이영숙;기대욱
    • 한국멀티미디어학회논문지
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    • 제23권12호
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    • pp.1586-1593
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    • 2020
  • This study was conducted on the face ratio of mammals. It can also be applied to character automation by checking factors about the difference between animal and human face shapes. This paper used the face and face area data generated for Deep Learning learning. In detail, the proportion factors of the area comprising the faces of 20 species of animals and humans were defined and the average ratio was calculated. Next, the proportion of each animal was analyzed using the Principal Component Analysis (PCA). Through this, we would like to propose the golden ratio of mammals.

Deep Learning-Based Low-Light Imaging Considering Image Signal Processing

  • Minsu, Kwon
    • 한국컴퓨터정보학회논문지
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    • 제28권2호
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    • pp.19-25
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    • 2023
  • 이 논문에서는 image signal processing 을 고려하여 저조도에서 촬영된 저품질의 raw 이미지를 딥러닝에 기반하여 개선하는 방법을 제안한다. 스마트폰 카메라의 경우 DSLR 카메라에 비해 렌즈나 센서의 확장에 제약이 있어 저조도 상황에서 이미지에 노이즈가 증가되고 품질이 저하되는 문제점을 보인다. 기존 딥러닝 기반 저조도 이미지 처리 방식은 image signal processing의 주요 요소인 렌즈 쉐이딩 효과와 화이트 밸런스를 고려하지 못하여 부자연스러운 이미지를 생성하기도 한다. 본 논문에서는 렌즈 쉐이딩 효과와 화이트 밸런스를 딥러닝 모델에 적용하기 위해 중심거리와 채널 평균을 활용한다. 스마트폰으로 촬영된 저조도 이미지를 통한 실험에서 제안하는 방법이 기존 방법에 비해 더 높은 peak signal to noise ratio 와 structural similarity index measure를 달성함과 동시에 높은 품질의 저조도 이미지를 생성함을 확인한다.