• Title/Summary/Keyword: image assessment

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Linear Feature Extraction from Satellite Imagery using Discontinuity-Based Segmentation Algorithm

  • Niaraki, Abolghasem Sadeghi;Kim, Kye-Hyun;Shojaei, Asghar
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.643-646
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    • 2006
  • This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

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Quantitative Assessment of Joint Roughness Coefficient from Televiewer and Core scan Images (텔레뷰어 및 코어 스캔 이미지를 이용한 절리면 거칠기 계수의 정량적인 평가)

  • Kim, Jung-Yul;Kim, Yoo-Sung
    • Proceedings of the Korean Geotechical Society Conference
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    • 2005.03a
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    • pp.1205-1210
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    • 2005
  • The behavior of rock mass and solute(e.g. groundwater, radioactivity) flow in fractured rock can be directly influenced by joint roughness. The characteristics of joint roughness is also a main factor for the rock classification(e.g. RMR, Q system) which is usually used in tunnel design. Nevertheless, most of JRC estimation has been carried out only by the examination with the naked eye. This JRC estimation has a lack of objectivity because each investigator judges JRC by his subjective opinion. Therefore, it will be desirable that the assessment of JRC is performed by a numerical analysis which can give a quantitative value corresponding to the characteristics of a roughness curve. Meanwhile, roughness curves for joint surfaces which are observed in drill cores have been obtained only along linear profiles. Although roughness curves are measured in the same joint surface, they can frequently show diverse aspects in a standpoint of roughness characteristics. If roughness curves can be measured along the elliptical circumferences of joint surfaces from core scanning images or Televiewer images, they will certainly be more comprehensive than those measured along linear profiles for roughness characteristics of joint surfaces. This study is focus on dealing with (1) extracting automatically roughness curves from core scan image or Televiewer image, (2) improving the accuracy of quantitative assessment of JRC using fractal dimension concept.

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Application of Envisat ASAR Image in Near Real Time Flood monitoring and Assessment in China

  • Huang, Shifeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.2184-2189
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    • 2009
  • China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.

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A Study on Students' Understanding of Figures through Descriptive Assessments (서술형 평가를 통한 학생들의 도형에 대한 이해 고찰)

  • Choi, Su Im;Kim, Sung Joon
    • East Asian mathematical journal
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    • v.29 no.2
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    • pp.207-239
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    • 2013
  • This research is a study on student's understanding fundamental concepts of mathematical curriculum, especially in geometry domain. The goal of researching is to analyze student's concepts about that domain and get the mathematical teaching methods. We developed various questions of descriptive assessment. Then we set up the term, procedure of research for the understanding student's knowledge of geometric figures. And we analyze the student's understanding extent through investigating questions of descriptive assessment. In this research, we concluded that most of students are having difficulty with defining the fundamental concepts of mathematics, especially in geometry. Almost all the students defined the fundamental conceptions of mathematics obscurely and sometimes even missed indispensable properties. And they can't distinguish between concept definition and concept image. Prior to this study, we couldn't identify this problem. Here are some suggestions. First, take time to reflect on your previous mathematics method. And then compile some well-selected questions of descriptive assessment that tell us more about student's understanding in geometric concepts.

No-reference Sharpness Index for Scanning Electron Microscopy Images Based on Dark Channel Prior

  • Li, Qiaoyue;Li, Leida;Lu, Zhaolin;Zhou, Yu;Zhu, Hancheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2529-2543
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    • 2019
  • Scanning electron microscopy (SEM) image can link with the microscopic world through reflecting interaction between electrons and materials. The SEM images are easily subject to blurring distortions during the imaging process. Inspired by the fact that dark channel prior captures the changes to blurred SEM images caused by the blur process, we propose a method to evaluate the SEM images sharpness based on the dark channel prior. A SEM image database is first established with mean opinion score collected as ground truth. For the quality assessment of the SEM image, the dark channel map is generated. Since blurring is typically characterized by the spread of edge, edge of dark channel map is extracted. Then noise is removed by an edge-preserving filter. Finally, the maximum gradient and the average gradient of image are combined to generate the final sharpness score. The experimental results on the SEM blurred image database show that the proposed algorithm outperforms both the existing state-of-the-art image sharpness metrics and the general-purpose no-reference quality metrics.

Evaluation of the City Residents' Images on the Landscape Elements of the Rural Traditional Theme Village (농촌전통 테마마을의 경관구성요소에 대한 도시주민의 이미지평가)

  • Kim, Chun-Il;Kim, Ick-Hwan
    • Journal of the Korean Society of Industry Convergence
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    • v.13 no.4
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    • pp.227-233
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    • 2010
  • This study analyzes the images of city residents on the landscape elements of the rural theme villages. The results of analysis bring the following conclusions. 1) Important factor of rural landscape with worth preserving is natural landscape such as dense forests, trees and creek. 2) Natural landscape such as forests and trees is evaluated high in image-assessment as well. However, it is evaluated low in the image of "Diversity", therefore, various species of trees need to be preserved. 3) In the future, people who spent their life only in the city would be the main stream of Green-tourism, and their structure of image-assessment needs to be reorganized.

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ADAPTABLE ELLIPSE METHOD FOR BRIDGE COATING DEFECT RECOGNITION

  • Po-Han Chen;Ya-Ching Yang;Luh-Maan Chang
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.449-456
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    • 2009
  • Image processing has been applied to steel bridge defect recognition since 1990s. Compare to human visual inspection, image processing provides a more objective and accurate way of assessment. Since shade and shadow may sometimes occur when taking bridge coating images, non-uniform illumination problems should be considered. By means of color image processing, this paper aims to mitigate the illumination effect for bridge coating assessment. Furthermore, the adaptable ellipse method (AEM) is proposed to recognize mild rust colors. Finally, AEM will be compared to the K-Means algorithm, a popular recognition method, to show its advantage.

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Quantitative Assessment of Denticulus by Color Image Analysis (컬러 영상 분석을 통한 치석의 정량적 평가)

  • Shin, Seung-Won;Lee, Sun-Ju;Lee, Seong-Taek;Kim, Kyeong-Seop
    • Proceedings of the KIEE Conference
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    • 2008.04a
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    • pp.129-130
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    • 2008
  • In this study, we implement the color image processing algorithm to analyze the quantitative assessment of denticulus by computing spectral characteristics in HGB color domain. We can observe that we can utilize the normalized HGB color feature to assess the quantitative formation of denticulus.

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A New Hybrid Weight Pooling Method for Object Image Quality Assessment with Luminance Adaptation Effect and Visual Saliency Effect (광적응 효과와 시각 집중 효과를 이용한 새로운 객관적 영상 화질 측정 용 하이브리드 가중치 풀링 기법)

  • Shahab Uddin, A.F.M.;Kim, Donghyun;Choi, Jeung Won;Chung, TaeChoong;Bae, Sung-Ho
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.827-835
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    • 2019
  • In the pooling stage of a full reference image quality assessment (FR-IQA) technique, the global perceived quality for any distorted image is usually measured from the quality of its local image patches. But all the image patches do not have equal contribution when estimating the overall visual quality since the degree of degradation on those patches depends on various considerations i.e., types of the patches, types of the distortions, distortion sensitivities of the patches, saliency score of the patches, etc. As a result, weighted pooling strategy comes into account and different weighting mechanisms are used by the existing FR-IQA methods. This paper performs a thorough analysis and proposes a novel weighting function by considering the luminance adaptation as well as the visual saliency effect to offer more appropriate local weights, which can be adopted in the existing FR-IQA frameworks to improve their prediction accuracy. The extended experimental results show the effectiveness of the proposed weighting function.