• Title/Summary/Keyword: Image Size Reduction

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Emotion Recognition and Expression System of Robot Based on 2D Facial Image (2D 얼굴 영상을 이용한 로봇의 감정인식 및 표현시스템)

  • Lee, Dong-Hoon;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.4
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    • pp.371-376
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    • 2007
  • This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.

A Noise Reduction Technique for Enhancing Pituitary Adenoma Diagnostic on Magnetic Resonance Image (개선된 뇌하수체 선종 진단을 위한 자기공명영상 노이즈 제거 기법)

  • Jung, Young-Jin
    • Journal of radiological science and technology
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    • v.42 no.4
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    • pp.285-290
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    • 2019
  • Magnetic resonance imaging is a technique specialized in soft tissue imaging with high contrast resolution without in vivo ionization and has been widely used in various clinical settings. In particular, the recent increase in social stress factors has been used in the diagnosis of pituitary adenoma, the incidence increases rapidly. Recently, due to the development of magnetic resonance imaging, it is possible to diagnose micro pituitary adenoma, but despite the use of contrast medium, there has been a difficulty in diagnosing the pituitary adenoma due to its small size and noise. In order to solve this problem, a proposed method of separating signal components image and noise components image from a measured image is applied, and the improvement of diagnostic efficiency is attempted by removing noise. As a result, it was confirmed that the image quality was improved as a whole by applying SNR for 30 subjects data. It is expected that this study will be useful as a pre-processing method for improving the image quality and developing diagnostic indicators of pituitary adenoma.

Band Selection Algorithm based on Expected Value for Pixel Classification (픽셀 분류를 위한 기댓값 기반 밴드 선택 알고리즘)

  • Chang, Duhyeuk;Jung, Byeonghyeon;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.107-112
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    • 2022
  • In an embedded system such as a drone, it is difficult to store, transfer and analyze the entire hyper-spectral image to a server in real time because it takes a lot of power and time. Therefore, the hyper-spectral image data is transmitted to the server through dimension reduction or compression pre-processing. Feature selection method are used to send only the bands for analysis purpose, and these algorithms usually take a lot of processing time depending on the size of the image, even though the efficiency is high. In this paper, by improving the temporal disadvantage of the band selection algorithm, the time taken 24 hours was reduced to around 60-180 seconds based on the 40000*682 image resolution of 8GB data, and the use of 7.6GB RAM was significantly reduced to 2.3GB using 45 out of 150 bands. However, in terms of pixel classification performance, more than 98% of analysis results were derived similarly to the previous one.

A three-stage deep-learning-based method for crack detection of high-resolution steel box girder image

  • Meng, Shiqiao;Gao, Zhiyuan;Zhou, Ying;He, Bin;Kong, Qingzhao
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.29-39
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    • 2022
  • Crack detection plays an important role in the maintenance and protection of steel box girder of bridges. However, since the cracks only occupy an extremely small region of the high-resolution images captured from actual conditions, the existing methods cannot deal with this kind of image effectively. To solve this problem, this paper proposed a novel three-stage method based on deep learning technology and morphology operations. The training set and test set used in this paper are composed of 360 images (4928 × 3264 pixels) in steel girder box. The first stage of the proposed model converted high-resolution images into sub-images by using patch-based method and located the region of cracks by CBAM ResNet-50 model. The Recall reaches 0.95 on the test set. The second stage of our method uses the Attention U-Net model to get the accurate geometric edges of cracks based on results in the first stage. The IoU of the segmentation model implemented in this stage attains 0.48. In the third stage of the model, we remove the wrong-predicted isolated points in the predicted results through dilate operation and outlier elimination algorithm. The IoU of test set ascends to 0.70 after this stage. Ablation experiments are conducted to optimize the parameters and further promote the accuracy of the proposed method. The result shows that: (1) the best patch size of sub-images is 1024 × 1024. (2) the CBAM ResNet-50 and the Attention U-Net achieved the best results in the first and the second stage, respectively. (3) Pre-training the model of the first two stages can improve the IoU by 2.9%. In general, our method is of great significance for crack detection.

A neural network approach to defect classification on printed circuit boards (인쇄 회로 기판의 결함 검출 및 인식 알고리즘)

  • An, Sang-Seop;No, Byeong-Ok;Yu, Yeong-Gi;Jo, Hyeong-Seok
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.4
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    • pp.337-343
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    • 1996
  • In this paper, we investigate the defect detection by making use of pre-made reference image data and classify the defects by using the artificial neural network. The approach is composed of three main parts. The first step consists of a proper generation of two reference image data by using a low level morphological technique. The second step proceeds by performing three times logical bit operations between two ready-made reference images and just captured image to be tested. This results in defects image only. In the third step, by extracting four features from each detected defect, followed by assigning them into the input nodes of an already trained artificial neural network we can obtain a defect class corresponding to the features. All of the image data are formed in a bit level for the reduction of data size as well as time saving. Experimental results show that proposed algorithms are found to be effective for flexible defect detection, robust classification, and high speed process by adopting a simple logic operation.

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An Efficient Vehicle Image Compensation Algorithm based on Histogram Equalization (히스토그램 균등화 기반의 효율적인 차량용 영상 보정 알고리즘)

  • Hong, Sung-Il;Lin, Chi-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.3
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    • pp.2192-2200
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    • 2015
  • In this paper, we propose an efficient vehicle image compensation algorithm based on Histogram Equalization. The proposed a vehicle image compensation algorithm was elimination to the vehicle image shake using motion compensation and motion estimation. And, algorithm was calculated the histogram of pixel values from each sub-image by dividing the image as the constant size areas in order to image enhancement. Also, it had enhancement to the image by adjusting the gradient. The proposed algorithm was evaluate the difference between of performance and time, image by applied to the IP, and were confirmed the image enhancement with removing of vehicle camera image shake. In this paper, the proposed vehicle image enhancement algorithm was demonstrated effectiveness when compared to existing vehicle image stabilization, because the elimination of shake for the vehicle images used real-time processing without using a memory. And it was obtained the reduction effect of the computation time by the calculated through block matching, and obtained the better restoration result for naturalness of the image with the lowest noise.

Low Noise Vacuum Cleaner Design (저소음 청소기 개발)

  • Joo, Jae-Man;Lee, Jun-Hwa;Hong, Seun-Gee;Oh, Jang-Keun;Song, Hwa-Gyu
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.939-942
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    • 2007
  • Vacuum cleaner is a close life product that can remove various dusts from our surroundings. However well vacuum cleaner clean our environments, many people are looking away from it, due to its loud noise. Its noise causes a big trouble in the usual life, for example, catch calls, TV watching and discussing etc. To reduce these inconveniences, noise reduction methods and systematic design of low noise vacuum cleaner are studied in this paper. At first, sound quality investigation is performed to get the noise level and quality that make people TV watching and catch calls available. Based on the European and domestic customer SQ survey result, sound power, peak noise level and target sound spectrum guideline are studied and introduced. As a second, precise product sound spectrums are designed into each part based on the sound quality result. Fan-motor, brush, mainbody, cyclone spectrums are decided to get the final target sound based on the contribution level. Fan-motor is the major noise source of vacuum cleaner. Specially, its peak sound, RPM peak and BPF Peak, cause the people nervous. To reduce these peak sounds, high rotating impeller and diffuser are focused due to its interaction. A lot of experimental and numerical tests, operation points are investigated and optimization of flow path area between diffusers is performed. As a bagless device, cyclones are one of the major noise sources of vacuum cleaner. To reduce its noise, previous research is used and adopted well. Brush is the most difficult part to reduce noise. Its noise sources are all comes from aero-acoustic phenomena. Numerical analysis helps the understanding of flow structure and pattern, and a lot of experimental test are performed to reduce the noise. Gaps between the carpet and brush are optimized and flow paths are re-designed to lower the noise. Reduction is performed with keeping the cleaning efficiency and handling power together and much reduction of noise is acquired. With all above parts, main-body design is studied. To do a systematic design, configuration design developments technique is introduced from airplane design and evolved with each component design. As a first configuration, fan-motor installation position is investigated and 10 configuration ideas are developed and tested. As a second step, reduced size and compressed configuration candidates are tested and evaluated by a lot of major factor. Noise, power, mass production availability, size, flow path are evaluated together. If noise reduction configuration results in other performance degrade, the noise reduction configuration is ineffective. As a third configuration, cyclones are introduced and the size is reduced one more time and fourth, fifth, sixth, seventh configuration are evolved with size and design image with noise and other performance indexes. Finally we can get a overall much noise level reduction configuration. All above investigations are adopted into vacuum cleaner design and final customer satisfaction tests in Europe are performed. 1st grade sound quality and lowest noise level of bagless vacuum cleaner are achieved.

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The Change in the Buddhist Architecture of the Unified Silla Period (668-935) (통일신라시대(統一新羅時代) 불교건축(佛敎建築)의 변화(變化))

  • Kim, Sung-Woo
    • Journal of architectural history
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    • v.1 no.2 s.2
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    • pp.68-84
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    • 1992
  • The development of Buddhist architectures of the Unified Silla period have been generally understood to have paired pagoda instead of one which had been popular until before the unification. Besides the stylistic categorization of paired pagoda system, there had been no further investigation reported concerning whether there was any detailed process of change within the development of paired pagoda style. This paper aims to identify such change inside the development of paired pagoda style, which, externally, seems to be the same pattern of site design maintained throughout the period of Unified Silla that lasted for about three centuries. Since the temple sites of study are in the same pattern of layout, the method of investigation has to be such that can identify the subtle changes that, in external appearance, are not easily discernible. Hence, this research compared the dimensions of important measurement of five temple sites to be able to clarify the process of minor changes. Among many sites of Silla temples, only five were suitable for the research since detailed measurement were possible through field research or the report of excavation. They are the sites of Sachonwang-sa, Mangduk-sa, site of Kunsuri, and Bulguk-sa. Although the five sites have the same style of paired pagoda, it is clear that there were consistant flow of change. Even though the motivation of such change were not strong enough to change the site pattern itself, it resulted continuous minor changes such as the size and location of architectures. The size of image hall, for example, was growing larger and larger as time goes on, while, the size of Pagoda was getting smaller. In the same way, the size of middle gate became smaller while the size of lecture hall became larger, although the rate of change in these cases were not as severe as that of image hall and pagoda. At the same time, pagoda was coming closer to the middle gate leaving larger space in front of the image hall. Such aspect is even more meaningful considering the fact that the pagoda, from the 8th century in Japan and China, moved outside of the major precinct. The image hall, too, moved toward the middle gate slightly so that the space in front of the lecture hall became more spacious. Such changes, of course, were not accidental but they are the same continuous motivation of change that caused the changes before the period of unification. Enlargement of image hall and reduction of pagoda, for example, represent the changing relative importance of religious meaning. Hence, it is evident that one can not easily imterprete the development of one style only by categorizing it to be one same style. In the veiwpoint of the underlying motivation of change, the fact that one style persisted for a certain period of time, does not mean there had been no change, but means that it was the time of motivational accumulation, causing minor changes within the same style, to be able to create major change coming after.

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Adaptively Compensated-Disparity Prediction Scheme for Stereo Image Compression and Reconstruction (스테레오 영상 압축 및 복원을 위한 적응적 변이보상 예측기법)

  • 배경훈;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.676-682
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    • 2002
  • In this paper, an effective stereo image compression and reconstruction technique using a new adaptively compensated-disparity prediction scheme is proposed. That is, by adaptively predicting the mutual correlation between the stereo image using the proposed method, the bandwidth of the stereo input image can be compressed to the level of the conventional 2D image and the predicted image also can be effectively reconstructed using this transmitted reference image and disparity data in the receiver. Especially, in the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the predicted image reconstruction is adaptively selected in accordance with the magnitude of this feature values. From this adaptive disparity estimation method, reduction of the mismatching probability of the disparity vectors is expected and as a result, the image quality in the reconstructed image can be improved. In addition, from some experiments using the CCETT's stereo images of 'Fichier', 'Manege' and 'Tunnel', it is shown that the proposed method improves the PSNR of the reconstructed image to about 9.08 dB on average by comparing with that of the conventional methods. And also, it is found that there is almost no difference between the original image and the predicted image reconstructed through the proposed method by comparison to that of the conventional methods.

FPGA based Dynamic Thresholding Circuit

  • Cho, J.U.;Lee, S.H.;Jeon, J.W.;Kim, J.T.;Cho, J.D.;Lee, K.M.;Lee, J.H.;Byun, J.E.;Choi, J.C.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1235-1238
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    • 2004
  • Thresholding has been used to reduce the number of gray values in images. Typically, a single threshold value has been used, resulting in two gray level images. Image reduction of one single threshold value, however, may lose too much of the high-frequency edge information. Thus, dynamic thresholding that uses a different threshold for each pixel is preferred instead of using a single threshold value. Dynamic thresholding can preserve high frequency details as well as reduce the size of images. Since it takes long time to perform existing software dynamic thresholding in an embedded system, this paper proposes and implements a circuit by using a FPGA in order to perform a real-time dynamic thresholding,. The proposed circuit consists of two counters, and threshold look-up table, and control unit. The values of two counters determine each pixel position, the threshold look-up table converts each pixel value into other value, and the control unit generates necessary control signals. On arriving from a camera to the proposed circuit, each pixel is compared with its threshold value and is converted into other gray value. An image processing system by using the proposed circuit will be implemented and some experiments will be performed.

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