• Title/Summary/Keyword: 영상 전처리

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Development of surface detection model for dried semi-finished product of Kimbukak using deep learning (딥러닝 기반 김부각 건조 반제품 표면 검출 모델 개발)

  • Tae Hyong Kim;Ki Hyun Kwon;Ah-Na Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.4
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    • pp.205-212
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    • 2024
  • This study developed a deep learning model that distinguishes the front (with garnish) and the back (without garnish) surface of the dried semi-finished product (dried bukak) for screening operation before transfter the dried bukak to oil heater using robot's vacuum gripper. For deep learning model training and verification, RGB images for the front and back surfaces of 400 dry bukak that treated by data preproccessing were obtained. YOLO-v5 was used as a base structure of deep learning model. The area, surface information labeling, and data augmentation techniques were applied from the acquired image. Parameters including mAP, mIoU, accumulation, recall, decision, and F1-score were selected to evaluate the performance of the developed YOLO-v5 deep learning model-based surface detection model. The mAP and mIoU on the front surface were 0.98 and 0.96, respectively, and on the back surface, they were 1.00 and 0.95, respectively. The results of binary classification for the two front and back classes were average 98.5%, recall 98.3%, decision 98.6%, and F1-score 98.4%. As a result, the developed model can classify the surface information of the dried bukak using RGB images, and it can be used to develop a robot-automated system for the surface detection process of the dried bukak before deep frying.

Comparison of the Medication Effects between Milnacipran and Pregabalin in Fibromyalgia Syndrome Using a Functional MRI: a Follow-up Study (섬유근통 환자에 대한 Milnacipran과 Pregabalin 약물치료에 대한 기능적 자기공명영상에서의 후속 영향 비교)

  • Kang, Min Jae;Mun, Chi-Woong;Lee, Young Ho;Kim, Seong-Ho
    • Investigative Magnetic Resonance Imaging
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    • v.18 no.4
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    • pp.341-351
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    • 2014
  • Purpose : In this study, the medication effects of Milnacipran and Pregabalin, as well known as fibromyalgia treatment medicine, in fibromyalgia syndrome patients were compared through the change of BOLD signal in pain related functional MRI. Materials and Methods: Twenty fibromyalgia syndrome patients were enrolled in this study and they were separated into two groups according to the treatment medicine: 10 Milnacipran (MLN) treatment group and 7 Pregabalin (PGB) treatment group. For accurate diagnosis, all patients underwent several clinical tests. Pre-treated and post-treated fMRI image with block-designed pressure-pain stimulation for each group were obtained to conduct the statistical analysis of paired t-test and two sample t-test. All statistical significant level was less than 0.05. Results: In clinical tests, the clinical scores of the two groups were not significantly different at pre-treatment stage. But, PGB treatment group had lower Widespread Pain Index (WPI) and Brief Fatigue Inventory (BFI) score than those of MLN treatment group at post-treatment stage. In functional image analysis, BOLD signal of PGB treatment group was higher BOLD signal at several regions including anterior cingulate and insula than MLN treatment group at post-treatment stage. Also, paired t-test values of the BOLD signal in MLN group decreased in several regions including insula and thalamus as known as 'pain network'. In contrast, size and number of regions in which the BOLD signal decreased in PGB treatment group were smaller than those of MLN treatment group. Conclusion: This study showed that MLN group and PGB group have different medication effects. It is not surprising that MLN and PGB have not the same therapeutic effects since these two drugs have different medicinal mechanisms such as antidepressants and anti-seizure medication, respectively, and different detailed target of fibromyalgia syndrome treatment. Therefore, it is difficult to say which medicine will work better in this study.

Digital Hologram Compression Technique By Hybrid Video Coding (하이브리드 비디오 코팅에 의한 디지털 홀로그램 압축기술)

  • Seo, Young-Ho;Choi, Hyun-Jun;Kang, Hoon-Jong;Lee, Seung-Hyun;Kim, Dong-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.29-40
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    • 2005
  • According as base of digital hologram has been magnified, discussion of compression technology is expected as a international standard which defines the compression technique of 3D image and video has been progressed in form of 3DAV which is a part of MPEG. As we can identify in case of 3DAV, the coding technique has high possibility to be formed into the hybrid type which is a merged, refined, or mixid with the various previous technique. Therefore, we wish to present the relationship between various image/video coding techniques and digital hologram In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video and image. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. Finally the proposed hybrid compression algorithm is all of these methods. The tool for still image coding is JPEG2000, and the toots for video coding include various international compression algorithm such as MPEG-2, MPEG-4, and H.264 and various lossless compression algorithm. The proposed algorithm illustrated that it have better properties for reconstruction than the previous researches on far greater compression rate above from four times to eight times as much. Therefore we expect that the proposed technique for digital hologram coding is to be a good preceding research.

Estimation of Rice Heading Date of Paddy Rice from Slanted and Top-view Images Using Deep Learning Classification Model (딥 러닝 분류 모델을 이용한 직하방과 경사각 영상 기반의 벼 출수기 판별)

  • Hyeok-jin Bak;Wan-Gyu Sang;Sungyul Chang;Dongwon Kwon;Woo-jin Im;Ji-hyeon Lee;Nam-jin Chung;Jung-Il Cho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.337-345
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    • 2023
  • Estimating the rice heading date is one of the most crucial agricultural tasks related to productivity. However, due to abnormal climates around the world, it is becoming increasingly challenging to estimate the rice heading date. Therefore, a more objective classification method for estimating the rice heading date is needed than the existing methods. This study, we aimed to classify the rice heading stage from various images using a CNN classification model. We collected top-view images taken from a drone and a phenotyping tower, as well as slanted-view images captured with a RGB camera. The collected images underwent preprocessing to prepare them as input data for the CNN model. The CNN architectures employed were ResNet50, InceptionV3, and VGG19, which are commonly used in image classification models. The accuracy of the models all showed an accuracy of 0.98 or higher regardless of each architecture and type of image. We also used Grad-CAM to visually check which features of the image the model looked at and classified. Then verified our model accurately measure the rice heading date in paddy fields. The rice heading date was estimated to be approximately one day apart on average in the four paddy fields. This method suggests that the water head can be estimated automatically and quantitatively when estimating the rice heading date from various paddy field monitoring images.

Imaging of Lung Metastasis Tumor Mouse Model using $[^{18}F]FDG$ Small Animal PET and CT ($[^{18}F]FDG$ 소동물 PET과 CT를 이용한 폐 전이 종양 마우스 모델의 영상화)

  • Kim, June-Youp;Woo, Sang-Keun;Lee, Tae-Sup;Kim, Kyeong-Min;Kang, Joo-Hyun;Woo, Kwang-Sun;Chung, Wee-Sup;Jung, Jae-Ho;Cheon, Gi-Jeong;Choi, Chang-Woon;Lim, Sang-Moo
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.1
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    • pp.42-48
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    • 2007
  • Purpose: The purpose of this study is to image metastaic lung melanoma model with optimal pre-conditions for animal handling by using $[^{18}F]FDG$ small animal PET and clinical CT. Materials and Methods: The pre-conditions for lung region tumor imaging were 16-22 h fasting and warming temperature at $30^{\circ}C$. Small animal PET image was obtained at 60 min postinjection of 7.4 MBq $[^{18}F]FDG$ and compared pattern of $[^{18}F]FDG$ uptake and glucose standard uptake value (SUVG) of lung region between Ketamine/Xylazine (Ke/Xy) and Isoflurane (Iso) anesthetized group in normal mice. Metastasis tumor mouse model to lung was established by intravenous injection of B16-F10 cells in C57BL/6 mice. In lung metastasis tumor model, $[^{18}F]FDG$ image was obtained and fused with anatomical clinical CT image. Results: Average blood glucose concentration in normal mice were $128.0{\pm}23.87$ and $86.0{\pm}21.65\;mg/dL$ in Ke/Xy group and Iso group, respectively. Ke/Xy group showed 1.5 fold higher blood glucose concentration than Iso group. Lung to Background ratio (L/B) in SUVG image was $8.6{\pm}0.48$ and $12.1{\pm}0.63$ in Ke/Xy group and Iso group, respectively. In tumor detection in lung region, $[^{18}F]FDG$ image of Iso group was better than that of Ke/Xy group, because of high L/B ratio. Metastatic tumor location in $[^{18}F]FDG$ small animal PET image was confirmed by fusion image using clinical CT. Conclusion: Tumor imaging in small animal lung region with $[^{18}F]FDG$ small animal PET should be considered pre-conditions which fasting, warming and an anesthesia during $[^{18}F]FDG$ uptake. Fused imaging with small animal PET and CT image could be useful for the detection of metastatic tumor in lung region.

Research of Water-related Disaster Monitoring Using Satellite Bigdata Based on Google Earth Engine Cloud Computing Platform (구글어스엔진 클라우드 컴퓨팅 플랫폼 기반 위성 빅데이터를 활용한 수재해 모니터링 연구)

  • Park, Jongsoo;Kang, Ki-mook
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1761-1775
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    • 2022
  • Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

Thermal and electrical Characteristics of Epoxy-Nanocomposites according to AIN Nanoparticles Surface Treatment (Epoxy/AIN Nanoparticles의 표면처리에따른 에폭시-Nanocomposites 열적 그리고 전기적 특성연구)

  • Lee, Chang-Hun;Kim, Jong-Min;Kim, Jae-Bong;Lee, Sang-Hyup;Kim, Do-Hwan;Park, Jae-Jun
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2009.11a
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    • pp.149-149
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    • 2009
  • 본 연구는 고압전력용 중전기기의 몰드절연 및 옥외용 LED의 절연소재는 기기내부에서 발생된 열에너지를 외부로 방사시키는 것이 무엇보다 중요한 것이다. 이런 이유로 고압전력용 전력기기 대부분은 상당한 체적분을 가지고 있기에 초절연을 가지면서 고열전도를 갖는 나노콤포지트를 개발하기위해 에폭시 메트릭스 기반 질화알루미륨의 표면 처리를 실시하여 에폭시 AIN Nanocomposites를 제조하였다. 나노입자의 균질분산은 나노콤포지트 열전도와 초절연성능에 크게 영향을 주게 된다. 이런 소재개발을 위해 에폭시메트릭스에 나노입자의 충진함량을 3wt%로 하였다. 전처리공정을 통하여 에폭시-나노콤포지트에 두 종류의 금속성 coupling agent (Tyzor TE, Tyzor AA-75)를 질화알루미륨 나노입자 표면처리를 건식법으로 실시하였다. 제조된 Epoxy-AIN Nanocomposites의 열적특성과 전기적 특성을 측정하였다. 전기적특성으로 초절연성의 특성인 형상파라미터가 10.93을 그리고 척도파라미터는 176 kV/mm로서 Weibull Plot 누적확률밀도로서(63.2%)의 통계분석된 값을 얻었다. 또한 열적특성 평가를 위해 유리천이온도와 DMA의 온도특성를 조사하였고, 열적.전기적 특성과 나노콤포지트 내부분산(내부 모폴로지:TEM영상)와 연관되어 연구한 결과, 상당히 일치한 결과를 얻을 수 있었다.

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Fingerprint Identification Using the Distribution of Ridge Directions (방향분포를 이용한 지문인식)

  • Kim Ki-Cheol;Choi Seung-Moon;Lee Jung-Moon
    • Journal of Digital Contents Society
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    • v.2 no.2
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    • pp.179-189
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    • 2001
  • This paper aims at faster processing and retrieval in fingerprint identification systems by reducing the amount of preprocessing and the size of the feature vector. The distribution of fingerprint directions is a set of local directions of ridges and furrows in small overlapped blocks in a fingerprint image. It is extracted initially as a set of 8-direction components through the Gabor filter bank. The discontinuous distribution of directions is smoothed to a continuous one and visualized as a direction image. Then the center of the distribution is selected as a reference point. A feature vector is composed of 192 sine values of the ridge angles at 32-equiangular positions with 6 different distances from the reference point in the direction image. Experiments show that the proposed algorithm performs the same level of correct identification as a conventional algorithm does, while speeding up the overall processing significantly by reducing the length of the feature vector.

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Integrated 3D Skin Color Model for Robust Skin Color Detection of Various Races (강건한 다인종 얼굴 검출을 위한 통합 3D 피부색 모델)

  • Park, Gyeong-Mi;Kim, Young-Bong
    • The Journal of the Korea Contents Association
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    • v.9 no.5
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    • pp.1-12
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    • 2009
  • The correct detection of skin color is an important preliminary process in fields of face detection and human motion analysis. It is generally performed by three steps: transforming the pixel color to a non-RGB color space, dropping the illuminance component of skin color, and classifying the pixels by the skin color distribution model. Skin detection depends on by various factors such as color space, presence of the illumination, skin modeling method. In this paper we propose a 3d skin color model that can segment pixels with several ethnic skin color from images with various illumination condition and complicated backgrounds. This proposed skin color model are formed with each components(Y, Cb, Cr) which transform pixel color to YCbCr color space. In order to segment the skin color of several ethnic groups together, we first create the skin color model of each ethnic group, and then merge the skin color model using its skin color probability. Further, proposed model makes several steps of skin color areas that can help to classify proper skin color areas using small training data.

A CONSTRUCTION OF A SEMI-AUTOMATIC TELESCOPE FOR ECLIPSE TIMING OBSERVATIONS OF ECLIPSING BINARY STARS (식쌍성의 극심시각 관측을 위한 소형 반자동 망원경 관측시스템의 구성)

  • 이충욱;박성수;김천휘;변용익
    • Journal of Astronomy and Space Sciences
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    • v.20 no.2
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    • pp.143-152
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    • 2003
  • We constructed the photometric observation system with a small semi-automatic telescope for the systematic observations of eclipse timings of eclipsing binary stars. The system is consisted of a Paramount GT-1100s mount system, a Celestron 14 optical system, and a SBIG ST-8 camera. We developed the OBSTOOL S/W which controls the telescope and the CCD camera using the COM(Component Object Model) supported by the softwares, The Sky and MaximDL. The system performs photometric observations of a variable, comparison and check stars by moving the telescope to the chosen star separately in a similar way such as the method of photoelectric observation. We wrote pert scripts which enable a data handling pipeline for the obtained data to be classified by each of date, object and filter. And thus the images are easily preprocessed using the IRAF S/W package. Eclipse light curves of some eclipsing binary stars observed with this system are presented.