• Title/Summary/Keyword: Blurring effect

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Performance Analysis of Matching Cost Functions of Stereo Matching Algorithm for Making 3D Contents (3D 콘텐츠 생성에서의 스테레오 매칭 알고리즘에 대한 매칭 비용 함수 성능 분석)

  • Hong, Gwang-Soo;Jeong, Yeon-Kyu;Kim, Byung-Gyu
    • Convergence Security Journal
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    • v.13 no.3
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    • pp.9-15
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    • 2013
  • Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

Cortical Thickness Estimation Using DIR Imaging with GRAPPA Factor 2 (DIR 영상을 이용한 피질두께 측정: GRAPPA 인자 2를 이용한 비교)

  • Choi, Na-Rae;Nam, Yoon-Ho;Kim, Dong-Hyun
    • Investigative Magnetic Resonance Imaging
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    • v.14 no.1
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    • pp.56-63
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    • 2010
  • Purpose : DIR image is relatively free from susceptibility artifacts therefore, DIR image can make it possible to reliably measure cortical thickness/volume. One drawback of the DIR acquisition is the long scan time to acquire the fully sampled 3D data set. To solve this problem, we applied a parallel imaging method (GRAPPA) and verify the reliability of using the volumetric study. Materials and methods : Six healthy volunteers (3 males and 3 females; age $25.33{\pm}2.25$ years) underwent MRI using the 3D DIR sequence at a 3.0T Siemens Tim Trio MRI scanner. GRAPPA simulation was performed from the fully sampled data set for reduction factor 2. Data reconstruction was performed using MATLAB R2009b. Freesurfer v.4.3.0 was used to evaluate the cortical thickness of the entire brain, and to extract white matter information from the DIR image, Analyze 9.0 was used. The global cortical thickness estimated from the reconstructed image was compared with reference image by using a T-test in SPSS. Results : Although reduced SNR and blurring are observed from the reconstructed image, in terms of segmentation the effect was not so significant. The volumetric result was validated that there were no significant differences in many cortical regions. Conclusion : This study was performed with DIR image for a volumetric MRI study. To solve the long scan time of 3D DIR imaging, we applied GRAPPA algorithm. According to the results, fast imaging can be done with reduction factor 2 with little loss of image quality at 3.0T.

A Study about Learning Graph Representation on Farmhouse Apple Quality Images with Graph Transformer (그래프 트랜스포머 기반 농가 사과 품질 이미지의 그래프 표현 학습 연구)

  • Ji Hun Bae;Ju Hwan Lee;Gwang Hyun Yu;Gyeong Ju Kwon;Jin Young Kim
    • Smart Media Journal
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    • v.12 no.1
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    • pp.9-16
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    • 2023
  • Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

Effective Detective Quantum Efficiency (eDQE) Evaluation for the Influence of Focal Spot Size and Magnification on the Digital Radiography System (X-선관 초점 크기와 확대도에 따른 디지털 일반촬영 시스템의 유효검출양자효율 평가)

  • Kim, Ye-Seul;Park, Hye-Suk;Park, Su-Jin;Kim, Hee-Joung
    • Progress in Medical Physics
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    • v.23 no.1
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    • pp.26-32
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    • 2012
  • The magnification technique has recently become popular in bone radiography, mammography and other diagnostic examination. However, because of the finite size of X-ray focal spot, the magnification influences various imaging properties with resolution, noise and contrast. The purpose of study is to investigate the influence of magnification and focal spot size on digital imaging system using eDQE (effective detective quantum efficiency). Effective DQE is a metric reflecting overall system response including focal spot blur, magnification, scatter and grid response. The adult chest phantom employed in the Food and Drug Administration (FDA) was used to derive eDQE from eMTF (effective modulation transfer function), eNPS (effective noise power spectrum), scatter fraction and transmission fraction. According to results, spatial frequencies that eMTF is 10% with the magnification factor of 1.2, 1.4, 1.6, 1.8 and 2.0 are 2.76, 2.21, 1.78, 1.49 and 1.26 lp/mm respectively using small focal spot. The spatial frequencies that eMTF is 10% with the magnification factor of 1.2, 1.4, 1.6, 1.8 and 2.0 are 2.21, 1.66, 1.25, 0.93 and 0.73 lp/mm respectively using large focal spot. The eMTFs and eDQEs decreases with increasing magnification factor. Although there are no significant differences with focal spot size on eDQE (0), the eDQEs drops more sharply with large focal spot than small focal spot. The magnification imaging can enlarge the small size lesion and improve the contrast due to decrease of effective noise and scatter with air-gap effect. The enlargement of the image size can be helpful for visual detection of small image. However, focal spot blurring caused by finite size of focal spot shows more significant impact on spatial resolution than the improvement of other metrics resulted by magnification effect. Based on these results, appropriate magnification factor and focal spot size should be established to perform magnification imaging with digital radiography system.

A Study on Fast Iris Detection for Iris Recognition in Mobile Phone (휴대폰에서의 홍채인식을 위한 고속 홍채검출에 관한 연구)

  • Park Hyun-Ae;Park Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.19-29
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    • 2006
  • As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).

Development of Artificial Pulmonary Nodule for Evaluation of Motion on Diagnostic Imaging and Radiotherapy (움직임 기반 진단 및 치료 평가를 위한 인공폐결절 개발)

  • Woo, Sang-Keun;Park, Nohwon;Park, Seungwoo;Yu, Jung Woo;Han, Suchul;Lee, Seungjun;Kim, Kyeong Min;Kang, Joo Hyun;Ji, Young Hoon;Eom, Kidong
    • Progress in Medical Physics
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    • v.24 no.1
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    • pp.76-83
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    • 2013
  • Previous studies about effect of respiratory motion on diagnostic imaging and radiation therapy have been performed by monitoring external motions but these can not reflect internal organ motion well. The aim of this study was to develope the artificial pulmonary nodule able to perform non-invasive implantation to dogs in the thorax and to evaluate applicability of the model to respiratory motion studies on PET image acquisition and radiation delivery by phantom studies. Artificial pulmonary nodule was developed on the basis of 8 Fr disposable gastric feeding tube. Four anesthetized dogs underwent implantation of the models via trachea and implanted locations of the models were confirmed by fluoroscopic images. Artificial pulmonary nodule models for PET injected $^{18}F$-FDG and mounted on the respiratory motion phantom. PET images of those acquired under static, 10-rpm- and 15-rpm-longitudinal round motion status. Artificial pulmonary nodule models for radiation delivery inserted glass dosemeter and mounted on the respiratory motion phantom. Radiation delivery was performed at 1 Gy under static, 10-rpm- and 15-rpm-longitudinal round motion status. Fluoroscpic images showed that all models implanted in the proximal caudal bronchiole and location of models changed as respiratory cycle. Artificial pulmonary nodule model showed motion artifact as respiratory motion on PET images. SNR of respiratory gated images was 7.21. which was decreased when compared with that of reference images 10.15. However, counts of respiratory images on profiles showed similar pattern with those of reference images when compared with those of static images, and it is assured that reconstruction of images using by respiratory gating improved image quality. Delivery dose to glass dosemeter inserted in the models were same under static and 10-rpm-longitudinal motion status with 0.91 Gy, but dose delivered under 15-rpm-longitudinal motion status was decreased with 0.90 Gy. Mild decrease of delivered radiation dose confirmed by electrometer. The model implanted in the proximal caudal bronchiole with high feasibility and reflected pulmonary internal motion on fluoroscopic images. Motion artifact could show on PET images and respiratory motion resulted in mild blurring during radiation delivery. So, the artificial pulmonary nodule model will be useful tools for study about evaluation of motion on diagnostic imaging and radiation therapy using laboratory animals.

The Evaluation of Resolution Recovery Based Reconstruction Method, Astonish (Resolution Recovery 기반의 Astonish 영상 재구성 기법의 평가)

  • Seung, Jong-Min;Lee, Hyeong-Jin;Kim, Jin-Eui;Kim, Hyun-Joo;Kim, Joong-Hyun;Lee, Jae-Sung;Lee, Dong-Soo
    • The Korean Journal of Nuclear Medicine Technology
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    • v.15 no.1
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    • pp.58-64
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    • 2011
  • Objective: The 3-dimensional reconstruction method with resolution recovery modeling has advantages of high spatial resolution and contrast because of its precise modeling of spatial blurring according to the distance from detector plane. The aim of this study was to evaluate one of the resolution recovery reconstruction methods (Astonish, Philips Medical), compare it to other iterative reconstructions, and verify its clinical usefulness. Materials and Methods: NEMA IEC PET body phantom and Flanges Jaszczak ECT phantom (Data Spectrum Corp., USA) studies were performed using Skylight SPECT (Philips) system under four different conditions; short or long (2 times of short) radius, and half or full (40 kcts/frame) acquisition counts. Astonish reconstruction method was compared with two other iterative reconstructions; MLEM and 3D-OSEM which vendor supplied. For quantitative analysis, the contrast ratios obtained from IEC phantom test were compared. Reconstruction parameters were determined by optimization study using graph of contrast ratio versus background variability. The qualitative comparison was performed with Jaszczak ECT phantom and human myocardial data. Results: The overall contrast ratio was higher with Astonish than the others. For the largest hot sphere of 37 mm diameter, Astonish showed about 27.1% and 17.4% higher contrast ratio than MLEM and 3D-OSEM, in short radius study. For long radius, Astonish showed about 40.5% and 32.6% higher contrast ratio than MLEM and 3D-OSEM. The effect of acquired counts was insignificant. In the qualitative studies with Jaszczak phantom and human myocardial data, Astonish showed the best image quality. Conclusion: In this study, we have found out that Astonish can provide more reliable clinical results by better image quality compared to other iterative reconstruction methods. Although further clinical studies are required, Astonish would be used in clinics with confidence for enhancement of images.

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