• Title/Summary/Keyword: Pixel error

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Generation of Error corrector for Holographic Data Storage system Used The Extended Kalman filter (확장 칼만필터를 이용한 홀로그래픽 에러 보정 알고리즘)

  • Kim Janghyun;Yang Hyunseok;Park Jinbae;Park Youngpil
    • 정보저장시스템학회:학술대회논문집
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    • 2005.10a
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    • pp.44-46
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    • 2005
  • Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part therefore fast data transfer rate and high storage capacity about $1Tb/cm^3$ can be realized. In this paper, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. We proposal Algorithm use The Extended Kalman filter. The Kalman filter reduce measurement noise. Therefore, By using this error reduction method following results are obtained; the effect of measurement nois of Pixel is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

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Design error corrector of binary data in holographic dnta storage system using fuzzy rules (근접 픽셀 에러 감소를 위한 홀로그래픽 데이터 스토리지 시스템의 퍼지 규칙 생성)

  • Kim Jang-hyun;Kim Sang-hoon;Yang Hyun-seok;Park Jin-bae;Park Young-Pil
    • 정보저장시스템학회:학술대회논문집
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    • 2005.10a
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    • pp.129-133
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    • 2005
  • Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part therefore fast data transfer rate and high storage capacity about $1Tb/cm^3$ can be realized. In this paper, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. First, find cluster centers using subtractive clustering algorithm then reduce intensities of pixels around cluster centers and fuzzy rules. Therefore, By using this error reduction method following results are obtained ; the effect of Inter Pixel Interference noise is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

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Image Processing Algorithm for Weight Estimation of Dairy Cattle (젖소 체중추정을 위한 영상처리 알고리즘)

  • Seo, Kwang-Wook;Kim, Hyeon-Tae;Lee, Dae-Weon;Yoon, Yong-Cheol;Choi, Dong-Yoon
    • Journal of Biosystems Engineering
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    • v.36 no.1
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    • pp.48-57
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    • 2011
  • The computer vision system was designed and constructed to measure the weight of a dairy cattle. Its development involved the functions of image capture, image preprocessing, image algorithm, and control integrated into one program. The experiments were conducted with the model dairy cattle and the real dairy cattle by two ways. First experiment with the model dairy cattle was conducted by using the indoor vision experimental system, which was built to measure the model dairy cattle in the laboratory. Second experiment with real dairy cattle was conducted by using the outdoor vision experimental system, which was built for measuring 229 heads of cows in the cattle facilities. This vision system proved to a reliable system by conducting their performance test with 15 heads of real cow in the cattle facilities. Indirect weight measuring with four methods were conducted by using the image processing system, which was the same system for measuring of body parameters. Error value of transform equation using chest girth was 30%. This error was seen as the cause of accumulated error by manually measurement. So it was not appropriate to estimate cow weight by using the transform equation, which was calculated from pixel values of the chest girth. Measurement of cow weight by multiple regression equation from top and side view images has relatively less error value, 5%. When cow weight was measured indirectly by image surface area from the pixel of top and side view images, maximum error value was 11.7%. When measured cow weight by image volume, maximum error weight was 57 kg. Generally, weight error was within 30 kg but maximum error 10.7%. Volume transform method, out of 4 measuring weight methods, was minimum error weight 21.8 kg.

Improved measurement uncertainty of photon detection efficiency for single pixel Silicon photomultiplier

  • Yang, Seul Ki;Lee, Hye-Young;Jeon, Jina;Kim, Sug-Whan;Lee, Jik;Park, Il H.
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.2
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    • pp.210.1-210.1
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    • 2012
  • We report technique used for improved measurement uncertainties for Photon detection efficiency(PDE) of $1mm^2$ single pixel SiPM. It consists of 470nm LED light source, two 2-inch integrating sphere and two NIST calibrated silicon photodiodes that have ${\pm}2.4%$ calibration error. With raytracing simulation of our experimental setup, we predict number of photon into SiPM and measurement uncertainty. For MPPC, Hamamatsu suggested PDE(1600 micro pixel) including crosstalk and afterpulse is 23.5% at 470 nm. By using new low calibration error photodiode and raytracing simulation, our simulation result has ${\pm}3%$ measurement uncertainty. The technical detail of measurement, simulation are presented with the results and implication.

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Key-point detection of fruit for automatic harvesting of oriental melon (참외 자동 수확을 위한 과일 주요 지점 검출)

  • Seung-Woo Kang;Jung-Hoon Yun;Yong-Sik Jeong;Kyung-Chul Kim;Dae-Hyun Lee
    • Journal of Drive and Control
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    • v.21 no.2
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    • pp.65-71
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    • 2024
  • In this study, we suggested a key-point detection method for robot harvesting of oriental melon. Our suggested method could be used to detect the detachment part and major composition of oriental melon. We defined four points (harvesting point, calyx, center, bottom) based on tomato with characteristics similar to those of oriental melon. The evaluation of estimated key-points was conducted by pixel error and PDK (percentage of detected key-point) index. Results showed that the average pixel error was 18.26 ± 16.62 for the x coordinate and 17.74 ± 18.07 for the y coordinate. Considering the resolution of raw images, these pixel errors were not expected to have a serious impact. The PDK score was found to be 89.5% PDK@0.5 on average. It was possible to estimate oriental melon specific key-point. As a result of this research, we believe that the proposed method can contribute to the application of harvesting robot system.

SHADOW EXTRACTION FROM ASTER IMAGE USING MIXED PIXEL ANALYSIS

  • Kikuchi, Yuki;Takeshi, Miyata;Masataka, Takagi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.727-731
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    • 2003
  • ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

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Digital Watermarking Based on Adaptive Threshold and Weighting Factor Decision Method (적응적 임계치와 가중치 결정 방법에 기반한 디지털 워터마킹)

  • Lim, Ho;Kim, Jin-Young
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.123-126
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    • 2000
  • In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

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반사형 강유전성 액정 공간 광 변조기를 이용한 CGH의 양자화 방법에 따른 재생 특성 비교

  • 최한섭
    • Korean Journal of Optics and Photonics
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    • v.10 no.1
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    • pp.32-39
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    • 1999
  • In this paper, we made CGH patterns that had continuous amplitude distribution binary coded patterns with two different methods, and analyzed those patterns by using LCSLM (liquid crystal spatial light modulator). The error diffusion algorithm and direct quantization method were used as the binarization methods. The parameters of overall average brightness, mean square error, and diffraction efficiency were used in the comparison of reconstruction characteristics. The LCSLM which we used in this experiment was a binary reflective ferroelectric liquid crystal spatial light modulator addressed electrically with 256$\times$256 pixels, 87% fill factor and 15$\mu$m pixel pitch.

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Color Image Segmentation by statistical approach (확률적 방법을 통한 컬러 영상 분할)

  • Gang Seon-Do;Yu Heon-U;Jang Dong-Sik
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1677-1683
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    • 2006
  • Color image segmentation is useful for fast retrieval in large image database. For that purpose, new image segmentation technique based on the probability of pixel distribution in the image is proposed. Color image is first divided into R, G, and B channel images. Then, pixel distribution from each of channel image is extracted to select to which it is similar among the well known probabilistic distribution function-Weibull, Exponential, Beta, Gamma, Normal, and Uniform. We use sum of least square error to measure of the quality how well an image is fitted to distribution. That P.d.f has minimum score in relation to sum of square error is chosen. Next, each image is quantized into 4 gray levels by applying thresholds to the c.d.f of the selected distribution of each channel. Finally, three quantized images are combined into one color image to obtain final segmentation result. To show the validity of the proposed method, experiments on some images are performed.

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Sub-pixel image interpolations for PIV

  • Kim Byoung Jae;Sung Hyung Jin
    • 한국가시화정보학회:학술대회논문집
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    • 2004.12a
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    • pp.47-55
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    • 2004
  • Several interpolations for image deformation in PIV were evaluated. The tested interpolation methods are linear, quadratic, truncated sinc, windowed sinc, cubic, Lagrange, Gaussian $2^{nd}\;and\;6^{th}$ interpolators. Bias errors and random errors were evaluated in the range of $0\~3.0$ pixel uniform displacement using synthetic images. We also measured the time cost of each interpolator with respect to kernel size. The cubic interpolator with $6\times6$ kernel showed the best results in terms of the performance and time cost.

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