• Title/Summary/Keyword: Center Pixel

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Performance Improvement of Human Detection in Thermal Images using Principal Component Analysis and Blob Clustering (주성분 분석과 Blob 군집화를 이용한 열화상 사람 검출 시스템의 성능 향상)

  • Jo, Ahra;Park, Jeong-Sik;Seo, Yong-Ho;Jang, Gil-Jin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.2
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    • pp.157-163
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    • 2013
  • In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.

Sex-, growth pattern-, and growth status-related variability in maxillary and mandibular buccal cortical thickness and density

  • Schneider, Sydney;Gandhi, Vaibhav;Upadhyay, Madhur;Allareddy, Veerasathpurush;Tadinada, Aditya;Yadav, Sumit
    • The korean journal of orthodontics
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    • v.50 no.2
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    • pp.108-119
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    • 2020
  • Objective: The primary objective of this study was to quantitatively analyze the bone parameters (thickness and density) at four different interdental areas from the distal region of the canine to the mesial region of the second molar in the maxilla and the mandible. The secondary aim was to compare and contrast the bone parameters at these specific locations in terms of sex, growth status, and facial type. Methods: This retrospective cone-beam computed tomography (CBCT) study reviewed 290 CBCT images of patients seeking orthodontic treatment. Cortical bone thickness in millimeters (mm) and density in pixel intensity value were measured for the regions (1) between the canine and first premolar, (2) between the first and second premolars, (3) between the second premolar and first molar, and (4) between the first and second molars. At each location, the bone thickness and density were measured at distances of 2, 6, and 10 mm from the alveolar crest. Results: The sex comparison (male vs. female) in cortical bone thickness showed no significant difference (p > 0.001). The bone density in growing subjects was significantly (p < 0.001) lower than that in non-growing subjects for most locations. There was no significant difference (p > 0.001) in bone parameters in relation to facial pattern in the maxilla and mandible for most sites. Conclusions: There was no significant sex-related difference in cortical bone thickness. The buccal cortical bone density was higher in females than in males. Bone parameters were similar for subjects with hyperdivergent, hypodivergent, and normodivergent facial patterns.

Calculation of Dose Distribution for SBRT Patient Using Geant4 Simulation Code (Geant4 전산모사 코드를 이용한 SBRT 환자의 선량분포 계산)

  • Kang, Jeongku;Lee, Jeongok;Lee, Dong Joon
    • Progress in Medical Physics
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    • v.26 no.1
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    • pp.36-41
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    • 2015
  • The Monte Carlo based dose calculation program for stereotactic body radiotherapy was developed in this study. The Geant4 toolkit widely used in the radiotherapy was used for this study. The photon energy spectrum of the medical linac studied in the previous research was applied for the patient dose calculations. The geometry of the radiation fields defined by multi-leaf collimators were taken into account in the PrimaryGeneratorAction class of the Geant4 code. The total of 8 fields were demonstrated in the patient dose calculations, where rotation matrix as a function of gantry angle was used for the determination of the source positions. The DicomHandler class converted the binary file format of the DICOM data containing the matrix number, pixel size, endian type, HU number, bit size, padding value and high bits order to the ASCII file format. The patient phantom was constructed using the converted ASCII file. The EGSnrc code was used to compare the calculation efficiency of the material data.

Improvement of Analytic Reconstruction Algorithms Using a Sinogram Interpolation Method for Sparse-angular Sampling with a Photon-counting Detector

  • Kim, Dohyeon;Jo, Byungdu;Park, Su-Jin;Kim, Hyemi;Kim, Hee-Joung
    • Progress in Medical Physics
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    • v.27 no.3
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    • pp.105-110
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    • 2016
  • Sparse angular sampling has been studied recently owing to its potential to decrease the radiation exposure from computed tomography (CT). In this study, we investigated the analytic reconstruction algorithm in sparse angular sampling using the sinogram interpolation method for improving image quality and computation speed. A prototype of the spectral CT system, which has a 64-pixel Cadmium Zinc Telluride (CZT)-based photon-counting detector, was used. The source-to-detector distance and the source-to-center of rotation distance were 1,200 and 1,015 mm, respectively. Two energy bins (23~33 keV and 34~44 keV) were set to obtain two reconstruction images. We used a PMMA phantom with height and radius of 50.0 mm and 17.5 mm, respectively. The phantom contained iodine, gadolinium, calcification, and lipid. The Feld-kamp-Davis-Kress (FDK) with the sinogram interpolation method and Maximum Likelihood Expectation Maximization (MLEM) algorithm were used to reconstruct the images. We evaluated the signal-to-noise ratio (SNR) of the materials. The SNRs of iodine, calcification, and liquid lipid were increased by 167.03%, 157.93%, and 41.77%, respectively, with the 23~33 keV energy bin using the sinogram interpolation method. The SNRs of iodine, calcification, and liquid state lipid were also increased by 107.01%, 13.58%, and 27.39%, respectively, with the 34~44 keV energy bin using the sinogram interpolation method. Although the FDK algorithm with the sinogram interpolation did not produce better results than the MLEM algorithm, it did result in comparable image quality to that of the MLEM algorithm. We believe that the sinogram interpolation method can be applied in various reconstruction studies using the analytic reconstruction algorithm. Therefore, the sinogram interpolation method can improve the image quality in sparse-angular sampling and be applied to CT applications.

Distortion Correction in Magnetic Resonance Images on the Measurement of Muscle Cross-sectional Area (자기공명영상을 이용한 근육 단면적 측정법의 활용을 위한 영상왜곡보정)

  • Hong, Cheol-Pyo;Lee, Dong-Hoon;Park, Ji-Won;Han, Bong-Soo
    • The Journal of Korean Physical Therapy
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    • v.24 no.2
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    • pp.66-72
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    • 2012
  • Purpose: The purpose of this study is to explore the importance of the image distortion correction in the cross sectional area measurement for the iliopsas muscle, tensor fasciae latae muscle, gluteus maximus muscle and the knee extensor muscles, by using (magnetic resonance imaging) MRI. Methods: This study was performed using an open 0.32T MRI system. To estimate the image distortion, T1 images for an AAPM homogeneity/linearity phantom were acquired, and the region in which the maximum geometric distortion was less than or equal to the pixel size (1.6 mm) of the images, it was defined as the distortion correction-free region. The T2 images for a human subject's pelvis and thigh in normal positions were obtained. Then, after the regions of interest in the pelvis and thigh were moved into the distortion correction-free region, T2 images for the pelvis and thigh were scanned with the same imaging parameters used in the previous T2 imaging. The cross-sectional areas were measured in the two T2 images that were obtained in the normal position, and the distortion correction-free region, as well as the area error caused by geometric image distortion was calculated. Results: The geometrical distortion is gradually increased, from the magnet center to the outer region, in axial and coronal plane. The cross-sectional area error of gluteus maximus muscle and the knee extensors was as high as 9.27% and 3.16% in before and after distortion correction, respectively. Conclusion: The cross-sectional area of the muscles that suffered from the geometrical distortion is necessary to correct for the estimation of the intervention.

Removal of Ring Artifact in Computed Tomography (전산화단층촬영장치에서 링 아티팩트 제거)

  • Chon, Kwon Su
    • Journal of the Korean Society of Radiology
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    • v.9 no.6
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    • pp.403-408
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    • 2015
  • Hard X-ray has been widely used in medical and industrial fields because it can be applied to observe the inside of a sample. Computed tomography provides sectional images of the sample through the reconstruction of the projection images. The quality of sectional images strongly depends on that of projection images. Ring artifact appeared on the seconal image can be made by the abnormal pixels of the detector used. In this study, we examine the ring artifact ratio in the circle phantom as a function of detection error of the detector used in computed tomography. The ring artifact increased with the increment of detection error under parallel and fan beam geometries and strongly increased near the center of rotation. The corrections, dead pixel and flat field corrections, for the images taken with the detector are required before the image reconstruction process to reduce the ring artifact in the computed tomography.

Distribution of Eurasian Otter Lutra lutra in Korea (한국 수달(Lutra lutra)의 분포 현황)

  • Jo Yeong-Seok;Won Chang-Man;Kim Joo-Pill
    • Korean Journal of Environmental Biology
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    • v.24 no.1 s.61
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    • pp.89-94
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    • 2006
  • This study was conducted to infer habitat distribution of Eurasian otter Lutra lutra in Korea. We recognized trace or presence of otter spraints from 254 of 750 pixels (pixel size: 13.75X11 km) used in this survey, amounting to 34%. The highest frequency of localities, with the spraints present, occurred in Gyeongsangbuk-do (49.62%) and the lowest one was observed in Gyeonggi-do (7.36%). The other regions were as follows: Gangwong-do (49.56%), Chungcheong buk-do (41.67%), Gyeongsangnam-do (38.00%), Jeolabuk-do (37.93%), Jeolanam-do (24.24%), Chungchengnam-do (20.29%). The counted number of the spraints was very low level in most of the localities where they were found (1.7spraints per sprainting site). It may indicate that small size of local populations would be expected in most of the localities. The habitat distribution of Korean otter, inferred from the distribution pattern of the spraints, will provide valuable basic information required for conserving and managing Korean otter.

Prediction-based Reversible Data Hiding Using Empirical Histograms in Images

  • Weng, Chi-Yao;Wang, Shiuh-Jeng;Liu, Jonathan;Goyal, Dushyant
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.4
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    • pp.1248-1266
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    • 2012
  • This paper presents a multilevel reversible data hiding method based on histogram shifting which can recover the original image losslessly after the hidden data has been extracted from the stego-image. The method of prediction is adopted in our proposed scheme and prediction errors are produced to explore the similarity of neighboring pixels. In this article, we propose two different predictors to generate the prediction errors, where the prediction is carried out using the center prediction method and the JPEG-LS median edge predictor (MED) to exploit the correlation among the neighboring pixels. Instead of the original image, these prediction errors are used to hide the secret information. Moreover, we also present an improved method to search for peak and zero pairs and also talk about the analogy of the same to improve the histogram shifting method for huge embedding capacity and high peak signal-to-noise ratio (PSNR). In the one-level hiding, our method keeps image qualities larger than 53 dB and the ratio of embedding capacity has 0.43 bpp (bit per pixel). Besides, the concept with multiple layer embedding procedure is applied for obtaining high capacity, and the performance is demonstrated in the experimental results. From our experimental results and analytical reasoning, it shows that the proposed scheme has higher PSNR and high data embedding capacity than that of other reversible data hiding methods presented in the literature.

Improved Algorithm of Hybrid c-Means Clustering for Supervised Classification of Remote Sensing Images (원격탐사 영상의 감독분류를 위한 개선된 하이브리드 c-Means 군집화 알고리즘)

  • Jeon, Young-Joon;Kim, Jin-Il
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.3
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    • pp.185-191
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    • 2007
  • Remote sensing images are multispectral image data collected from several band divided by wavelength ranges. The classification of remote sensing images is the method of classifying what has similar spectral characteristics together among each pixel composing an image as the important algorithm in this field. This paper presents a pattern classification method of remote sensing images by applying a possibilistic fuzzy c-means (PFCM) algorithm. The PFCM algorithm is a hybridization of a FCM algorithm, which adopts membership degree depending on the distance between data and the center of a certain cluster, combined with a PCM algorithm, which considers class typicality of the pattern sets. In this proposed method, we select the training data for each class and perform supervised classification using the PFCM algorithm with spectral signatures of the training data. The application of the PFCM algorithm is tested and verified by using Landsat TM and IKONOS remote sensing satellite images. As a result, the overall accuracy showed a better results than the FCM, PCM algorithm or conventional maximum likelihood classification(MLC) algorithm.

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Improved and quality-assessed emission and absorption line measurements in Sloan Digital Sky Survey galaxies

  • Oh, Kyu-Seok;Sarzi, Marc;Schawinski, Kevin;Yi, Suk-Young K.
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.73.2-73.2
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    • 2011
  • We present a new database of absorption and emission-line measurements based on the entire spectral atlas from the Sloan Digital Sky Survey (SDSS) 7th data release of galaxies within a redshift of 0.2. Our work makes use of the publicly available penalized pixel-fitting(pPXF) and gas and absorption line fitting (gandalf) IDL codes, aiming to improve the existing measurements for stellar kinematics, the strength of various absorption-line features, and the flux and width of the emissions from different species of ionized gas. Our fit to the stellar continuum uses both standard stellar population models and empirical templates obtained by combining a large number of stellar spectra in order to fit a subsample of high-quality SDSS spectra for quiescent galaxies. Furthermore, our fit to the nebular spectrum includes an exhaustive list of both recombination and forbidden lines. Foreground Galactic extinction is implicitly treated in our models, whereas reddening in the SDSS galaxies is included in the form of a simple dust screen component affecting the entire spectrum that is accompanied by a second reddening component affecting only the ionised gas emission. Most notable of our work is that, we provide quality of the fit to assess reliability of the measurements. The quality assessment can be highly effective for finding new classes of objects. For example, based on the quality assessment around the Ha and [NII] nebular lines, we found approximately 1% of the SDSS spectra which classified as "galaxies" by the SDSS pipeline are in fact type I Seyfert AGN.

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