• Title/Summary/Keyword: Low-contrast Image

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An Efficient BLU Inspection Using Noise-Tolerant Context-free Attention Operator (잡음에 강건한 주목 연산자를 이용한 효과적인 BLU 얼룩 검사)

  • Park, Chang-Jun;Choe, Heung-Mun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.640-647
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    • 2001
  • In this paper, a noise-tolerant generalized symmetry transform(NTGST) is proposed as an effective attention operator for the spot detection in BLU inspection, in which various spots with variable sizes, shapes, gray levels, and low contrast, should be detected from the complex, noisy background with lattice shaped shading. The proposed NTGST takes into account the polarity of convergence and divergence of the radial orientation of the intensity gradient as well as it's magnitude and symmetry, and thereby can detect only the BLU spots from the noisy and lattice shaped shadows of background. Experiments are conducted on the BLU inspection image obtained by CCD camera, and the proposed NTGST is Proved to be effectively used in BLU inspection.

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Analysis of Driving Characteristics by Putting Voltage of Charged Particle Type Display Device (대전입자형 디스플레이 소자의 충전전압에 따른 구동특성 분석)

  • Kim, Jin-Sun;Kim, Young-Cho
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.25 no.1
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    • pp.48-52
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    • 2012
  • The charged particle type display device is a kind of the reflectivity type display and shows an image by absorption and reflection of external light source. The charged particle is important factor for driving of the display and quantity of charge per mass of the charged particle determines the driving voltage, contrast ratio, response time, etc. But it is easy for the charged particles to be damaged in the putting process of the display and the damages cause lumping phenomenon of the charged particles. Because the lumping phenomenon makes high driving voltage, low quality of optical properties, short life time, etc, so the charged particles must be filled by stable putting methods. In this paper, we filled the charged particles into the panels by electric fields to improve the electrical and optical characteristics of the display. Also, we analyzed the driving characteristics of the charged particles according to the applied putting voltages.

Knowledge Based Automated Boundary Detection for Quantifying of Left Ventricular Function in Low Contrast Angiographic Images (저대조 혈관 조영상에서 좌심실 기능의 정량화를 위한 지식 기반의 경계선 자동검출)

  • 전춘기;권용무
    • Journal of Biomedical Engineering Research
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    • v.17 no.1
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    • pp.109-120
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    • 1996
  • Cardiac function is evaluated quantitatively using angiographic images via the analysis of the shape change or the heart wall boundaries. To kin with, boundary defection or ESLV(End Systolic Lert Ventricular) and EDLV(End Diastolic Left Ventricular) is essential for the quantitative analysis of cardiac function. The boundary detection methods proposed in the past were almost semi-automatic. Intervention by a knowledgeable human operator was still required Of con, manual tracing of the boundaries is currently used for subsequent analysis and diagnosis. This method would not cut excessive time, labor, and subjectivity associated with manual intervention by a human operator. EDLV images have noncontiguous and ambiguous edge signal on some boundary regions. In this paper, we propose a new method for automated detection of boundaries in noncontiguous and ambiguous EDLV images. The boundary detection scheme which based on a priori knowledge information is divided into two steps. The first step is to detect the candidate edge points of EDLV using ESLV boundaries. The second step is to correct detected boundaries of EDLV using the LV shape. We developed the algorithm of modifying EDLV boundaries defined adaptive modifier. We experimented the method proposed in this paper and compared our proposed method with the manual method in detecting boundaries of EDLV. In the areas within estimated boundaries of EDLV, the percentage of error was about 1.4%. We verified the useflilness and obtained the satisfying results througll the experiments of the proposed method.

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Analysis of the Koreanity Expression Properties found in the Modern Commercial Spaces from a Design Coordination Viewpoint (현대 상업공간에 표현된 디자인코디네이션 관점의 한국성 특성 분석)

  • Yim, Sun-Hee;Park, Young-Soon;Jung, Eui-Chul
    • Korean Institute of Interior Design Journal
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    • v.21 no.5
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    • pp.135-144
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    • 2012
  • Since Seoul was selected as the world design capital at the end of 2007, the endeavors to modernize the Korean unique beauty is becoming more tangible. Especially, the commercial spaces to be used by the general public and tourists have the value for study in the respect that such spaces for the national iconic images and have a large and far-reaching effect to transmit the national identity. Therefore, this study analyzed the design coordination properties in the Koreanity expression found in the modern commercial spaces. the foundation for the analysis was based on Leonard Koren's work on the arrrangement rhetoric theory, 'Arranging things(2003), and the contents of Korean expression were reviewed with professional jounals. the results are as follows: First, the design coordination properties in the Koreanity expression shown in modern commercial spaces are black-white contrast, natural materials, curved shapes, brevity, and simple beauty. Especially, some elements such as wood, traditional Korean papers, stones, mid-to-low chroma natural colors, checked patterns, and crazy patterns are used with overlapping and it is viewed that it is necessay to more aggressively seek for the disappeared traditional elements in the Korean modeling properties. Second, the concrete images of Korean expressions could be summarized as four adjective image groups, Natural, Subtitle, Gentle and Magnificent.

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A Novel Adaptive Histogram Equalization based on Histogram Matching (히스토그램 매칭에 기반한 적응적 히스토그램 균등화)

  • Min, Byong-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1231-1236
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    • 2006
  • The contrast control of images with narrow dynamic range is a simple method among enhancement methods for low intensity of image. Histogram equalization is the most common method for this purpose, which stretches the dynamic range of intensity Conventional methods would fail to enhance images with extremely dark and bright regions, because of not considering the shape of histogram. In this paper, we propose a novel adaptive histogram equalization based on histogram matching with multiple Gaussian transformation function. As a result, output images with a couple of peaks of histogram could be improved and the details such as edges in dark regions could be appeared better than conventional method subjectively.

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Automatic Road Extraction by Gradient Direction Profile Algorithm (GDPA) using High-Resolution Satellite Imagery: Experiment Study

  • Lee, Ki-Won;Yu, Young-Chul;Lee, Bong-Gyu
    • Korean Journal of Remote Sensing
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    • v.19 no.5
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    • pp.393-402
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    • 2003
  • In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

Study of Importance Awareness of Domestic Car Consumer's Product Selection Criteria (국산 자동차 소비자의 제품 선택 기준에 대한 중요도 인식 분석)

  • Lee, Taewon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.3
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    • pp.157-166
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    • 2019
  • The study had subject to find out what factors Korean automobile consumer is considering in their decision to purchase cars in the situation of the growing competition in the domestic automobile market. In order to this end, the previous study was reviewed to select various factors considered in the process of buying cars. Based on this, Analytic Hierarchy Process was used to prioritize which factors were considered more important by consumers. In the result of study, we could find that performance had the highest priority, and the second ranking was the price. In contrast, image of brand and convenience of maintenance were shown to be relatively low in importance, ranking $3^{rd}$ and $4^{th}$, respectively. Beside, we could recognized the ranking of other detailed factors. This study has an academic implication in that it is able to grasp the latest tendency of consumers' purchase choice of car and to make conclusion by applying AHP analysis method to study of related subject. It also have practical significance that can be a basis for make sense what factors should be taken by the automobile industry to uprise the purchase of the consumers through the identification and preparation of the purchase selection criteria of domestic automobile buyers.

Recognition of Characters Printed on PCB Components Using Deep Neural Networks (심층신경망을 이용한 PCB 부품의 인쇄문자 인식)

  • Cho, Tai-Hoon
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.3
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    • pp.6-10
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    • 2021
  • Recognition of characters printed or marked on the PCB components from images captured using cameras is an important task in PCB components inspection systems. Previous optical character recognition (OCR) of PCB components typically consists of two stages: character segmentation and classification of each segmented character. However, character segmentation often fails due to corrupted characters, low image contrast, etc. Thus, OCR without character segmentation is desirable and increasingly used via deep neural networks. Typical implementation based on deep neural nets without character segmentation includes convolutional neural network followed by recurrent neural network (RNN). However, one disadvantage of this approach is slow execution due to RNN layers. LPRNet is a segmentation-free character recognition network with excellent accuracy proved in license plate recognition. LPRNet uses a wide convolution instead of RNN, thus enabling fast inference. In this paper, LPRNet was adapted for recognizing characters printed on PCB components with fast execution and high accuracy. Initial training with synthetic images followed by fine-tuning on real text images yielded accurate recognition. This net can be further optimized on Intel CPU using OpenVINO tool kit. The optimized version of the network can be run in real-time faster than even GPU.

Reaction Times to Predictable Visual Patterns Reflect Neural Responses in Early Visual Cortex

  • Joo, Sung Jun
    • Science of Emotion and Sensibility
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    • v.24 no.2
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    • pp.57-64
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    • 2021
  • It has long been speculated that the visual system should use a coding strategy that takes advantage of statistical redundancies in images. But how such a coding strategy should manifest in neural responses has been less clear. Low-level image structure related to the power spectrum of natural images appears to be captured by a hard-wired efficient code in the retina of the fly and precortical structures like the LGN of cats that maximizes information content through the limited capacity channel of the optic nerve. But visual images are typically filled with higher-order structure beyond that captured by the power spectrum and visual cortex is not constrained by the same capacity limits as the optic nerve. Whether and how visual cortex can flexibly code for higher order redundancies is unknown. Here we show using psychophysical techniques that the neural response in early human visual cortex may be modulated by orientation redundancies in images such that a visual feature that is contained within a predictive pattern results in slower reaction times than a feature that deviates from a pattern, suggesting lower neural responses to predictable stimuli in the visual cortex. Our results point to a neural response in early visual cortex that is sensitive to global patterns and redundancies in visual images and is in marked contrast to standard models of cortical visual processing.

Design of Turbidity Measurement of White Plume using Optical Method (광학기법을 이용한 백색 굴뚝연기 혼탁도 측정의 설계)

  • Son, Hyun-Keun;Ban, Chae-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1195-1200
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    • 2020
  • The DOM (: Digital Optical Method), which measures the turbidity of chimney smoke, is a method of calculating the turbidity by setting the area to be measured and the contrast area using a low-cost digital camera that can be easily obtained. However, it is difficult to measure clouds and white smoke in a cloudy sky. In this paper, we develop a background sky type model that can represent the background sky and classify the type by periodically photographing it with a digital camera to solve this problem. In addition, based on the model, we develop a filter to optimize white smoke image and prove its excellence through experiments.