• Title/Summary/Keyword: Pixel-Based

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Deep Learning Applied Method for Acquisition of Digital Position Signal of PET Detector (PET 검출기의 디지털 위치 신호 측정을 위한 딥러닝 적용 방법)

  • Byungdu, Jo;Seung-Jae, Lee
    • Journal of the Korean Society of Radiology
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    • v.16 no.6
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    • pp.697-702
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    • 2022
  • For imaging in positron emission tomography(PET), it is necessary to measure the position of the scintillation pixel interacting with the gamma rays incident on the detector. To this end, in the conventional system, a flood image of the scintillation pixel is obtained, the imaged area of each scintillation pixel is separated, and the position of the scintillation pixel is specified and acquired as a digital signal. In this study, a deep learning method was applied based on the signal formed by the photosensor of the detector, and a method was developed to directly acquire a digital signal without going through various procedures. DETECT2000 simulation was performed to verify this and evaluate the accuracy of position measurement. A detector was constructed using a 6 × 6 scintillation pixel array and a 4 × 4 photosensor, and a gamma ray event was generated at the center of the scintillation pixel and summed into four channels of signals through the Anger equation. After training the deep learning model using the acquired signal, the positions of gamma-ray events that occurred in different depth directions of the scintillation pixel were measured. The results showed accurate results at every scintillation pixel and position. When the method developed in this study is applied to the PET detector, it will be possible to measure the position of the scintillation pixel with a digital signal more conveniently.

Evaluation on extraction of pixel-based solar zenith and offnadir angle for high spatial resolution satellite imagery (고해상도 위성영상의 화소기반 태양 천정각 및 촬영각 추출 및 평가)

  • Seong, Seon Kyeong;Seo, Doo Chun;Choi, Jae Wan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.563-569
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    • 2021
  • With the launch of Compact Advanced Satellite 500 series of various characteristics and the operation of KOMPSAT-3/3A, uses of high-resolution satellite images have been continuously increased. Especially, in order to provide satellite images in the form of ARD (Analysis Ready Data), various pre-processing such as geometric correction and radiometric correction have been developed. For pre-processing of high spatial satellite imagery, auxiliary information, such as solar zenith, solar azimuth and offnadir angle, should be required. However, most of the high-resolution satellite images provide the solar zenith and nadir angle for the entire image as a single variable. In this paper, the solar zenith and offnadir angle corresponding to each pixel of the image were calculated using RFM (Rational Function Model) and auxiliary information of the image, and the quality of extracted information were evaluated. In particular, for the utilization of pixel-based solar zenith and offnadir angle, pixel-based auxiliary data were applied in calculating the top of atmospheric reflectance, and comparative evaluation with a single constant-based top of atmospheric reflectance was performed. In the experiments using various satellite imagery, the pixel-based solar zenith and offnadir angle information showed a similar tendency to the auxiliary information of satellite sensor, and it was confirmed that the distortion was reduced in the calculated reflectance in the top of atmospheric reflectance.

Land Cover Classification Using UAV Imagery and Object-Based Image Analysis - Focusing on the Maseo-myeon, Seocheon-gun, Chungcheongnam-do - (UAV와 객체기반 영상분석 기법을 활용한 토지피복 분류 - 충청남도 서천군 마서면 일원을 대상으로 -)

  • MOON, Ho-Gyeong;LEE, Seon-Mi;CHA, Jae-Gyu
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.1
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    • pp.1-14
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    • 2017
  • A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.

Hybrid Facial Representations for Emotion Recognition

  • Yun, Woo-Han;Kim, DoHyung;Park, Chankyu;Kim, Jaehong
    • ETRI Journal
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    • v.35 no.6
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    • pp.1021-1028
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    • 2013
  • Automatic facial expression recognition is a widely studied problem in computer vision and human-robot interaction. There has been a range of studies for representing facial descriptors for facial expression recognition. Some prominent descriptors were presented in the first facial expression recognition and analysis challenge (FERA2011). In that competition, the Local Gabor Binary Pattern Histogram Sequence descriptor showed the most powerful description capability. In this paper, we introduce hybrid facial representations for facial expression recognition, which have more powerful description capability with lower dimensionality. Our descriptors consist of a block-based descriptor and a pixel-based descriptor. The block-based descriptor represents the micro-orientation and micro-geometric structure information. The pixel-based descriptor represents texture information. We validate our descriptors on two public databases, and the results show that our descriptors perform well with a relatively low dimensionality.

Improved Contrast for Threshold Random-grid-based Visual Cryptography

  • Hu, Hao;Shen, Gang;Fu, Zhengxin;Yu, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3401-3420
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    • 2018
  • Pixel expansion and contrast are two major performance parameters for visual cryptography scheme (VCS), which is a type of secret image sharing. Random Grid (RG) is an alternative approach to solve the pixel expansion problem. Chen and Tsao proposed the first (k, n) RG-based VCS, and then Guo et al., Wu et al., Shyu, and Yan et al. significantly improved the contrast in recent years. However, the investigations on improving the contrast of threshold RG-based VCS are not sufficient. In this paper, we develop a contrast-improved algorithm for (k, n) RG-based VCS. Theoretical analysis and experimental results demonstrate that the proposed algorithm outperformers the previous threshold algorithms with better visual quality and a higher accuracy of contrast.

Separation of Blind Signals Using Robust ICA Based-on Neural Networks (신경망 기반 Robust ICA에 의한 은닉신호의 분리)

  • Cho, Yong-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.7 no.1
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    • pp.41-46
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    • 2004
  • This paper proposes a separation of mixed signals by using the robust independent component analysis(RICA) based on neural networks. RICA is based on the temporal correlations and the second order statistics of signal. This method e is applied for improving the analysis rate and speed in which the sources have very small or zero kurtosis. The proposed method has been applied for separating the 10 mixed finger prints of $256{\times}256$-pixel and the 4 mixed images of $512{\times}512$-pixel, respectively. The simulation results show that RICA has the separating rate and speed better than those using the conventional FP algorithm based on Newton method.

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Development of hand-held coded-aperture gamma ray imaging system based on GAGG(Ce) scintillator coupled with SiPM array

  • Jeong, Manhee;Hammig, Mark
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2572-2580
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    • 2020
  • Emerging gamma ray detection applications that utilize neutron-based interrogation result in the prompt emission of high-energy (>2 MeV) gamma-rays. Rapid imaging is enabled by scintillators that possess high density, high atomic number, and excellent energy resolution. In this paper, we evaluate the bright (50,000 photons/MeV) oxide scintillator, cerium-doped Gd2Al2Ga3O12 (GAGG(Ce)). A silicon photomultiplier (SiPM) array is coupled to a GAGG(Ce) scintillator array (12 × 12 pixels) and integrated into a coded-aperture based gamma-ray imaging system. A resistor-based symmetric charge division circuit was used reduce the multiplicity of the analog outputs from 144 to 4. The developed system exhibits 9.1%, 8.3%, and 8.0% FWHM energy resolutions at 511 keV, 662 keV, and 1173.2 keV, respectively. In addition, a pixel-identification resolution of 602 ㎛ FWHM was obtained from the GAGG(Ce) scintillator array.

Efficient 3D Model based Face Representation and Recognition Algorithmusing Pixel-to-Vertex Map (PVM)

  • Jeong, Kang-Hun;Moon, Hyeon-Joon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.1
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    • pp.228-246
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    • 2011
  • A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

EFFICIENT IHS BASED IMAGE FUSION WITH 'COMPENSATIVE' MATRIX CONSTRUCTED BY SIMULATING THE SCALING PROCESS

  • Nguyen, TienCuong;Kim, Dae-Sung;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.639-642
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    • 2006
  • The intensity-hue-saturation (IHS) technique has become a standard procedure in image analysis. It enhances the colour of highly correlated data. Unfortunately, IHS technique is sensitive to the properties of the analyzed area and usually faces colour distortion problems in the fused process. This paper explores the relationship of colour between before and after the fused process and the change in colour space of images. Subsequently, the fused colours are transformed back into the 'simulative' true colours by the following steps: (1) For each pixel of fused image that match with original pixel (of the coarse spectral resolution image) is transformed back to the true colour of original pixel. (2) The value for interpolating pixels is compensated to preserve the DN ratio between the original pixel and it's vicinity. The 'compensative matrix' is constructed by the DN of fused images and simulation of scaling process. An illustrative example of a Landsat and SPOT fused image also demonstrates the simulative true colour fusion methods.

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Study on the Pixel Design for the Prerrue-stable Fringe-field Switching (FFS) Mode with 3 Slit Structure (압력에 안정한 3분할 FFS 모드의 화소 설계에 관한 연구)

  • Kim, Mi-Sook;Seen, Seung-Min;Jung, Yeon-Hak;Kim, Hayng-Yuil;Kim, Seo-Yoon;Lim, Young-Jin;Lee, Seung-Hee
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.18 no.7
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    • pp.647-651
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    • 2005
  • We studied the external pressure-stable advanced frnge field switching (FFS) pixel design with 3 slit sructue. In this mode, a patterned pixel slit is partitioned into 3 areas, namely, two edges and a center, where the edge slit angle is larger than the center slit angle. Thus the reverse twist region in the pixel edge is reduced comparing to the conventional FFS mode so that the LC dynamics in this region becomes very stable. And also, when the external pressure is applied to the panel at the high voltage, the disclination lines (DLs) were barely intruded into active area. Therefore, the structure is use for the pen based system such as the tablet personal computer (PC), personal digital asistant (PDA).