• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.108-114
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• 2007

This paper presented an image reconstruction method based on the original capsule endoscopy photos yielding a 2-D image for faster diagnosis proposes. The proposed method constructed a 3-D intestine model using the massive images obtained from the capsule endoscope. It merged all images and completed a 3-D model of an intestine. This 3-D model was reformed as a 2-D plane image showing the inner side of the entire intestine. The proposed image composition was evaluated by the 3-D simulator, OpenGL. This approach was demonstrated successfully. A physician can find the location of a disease at a glance because the composite image provided an easy-to-understand view to show the patient's intestine and thereby shorten diagnosis time.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.69-75
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• 2023

In recent years, there has been a growing interest in deep learning-based animal pose estimation, especially in the areas of animal behavior analysis and healthcare. However, existing animal pose estimation techniques do not perform well when body parts are occluded or not present. In particular, the occlusion of dog tail or ear might lead to a significant degradation of performance in pet behavior and emotion recognition. In this paper, to solve this intractable problem, we propose a simple yet novel framework for pet pose estimation where pet pose is predicted on an outpainted image where some body parts hidden outside the input image are reconstructed by the image inpainting network preceding the pose estimation network, and we performed a preliminary study to test the feasibility of the proposed approach. We assessed CE-GAN and BAT-Fill for image outpainting, and evaluated SimpleBaseline for pet pose estimation. Our experimental results show that pet pose estimation on outpainted images generated using BAT-Fill outperforms the existing methods of pose estimation on outpainting-less input image.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.2
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• pp.27-34
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• 2019

This study explores the emergence of a modern form of Cheongju-eup townscape in the late 1930s by re-examining the 1960s restoration model of Seongan-dong and Jungang-dong in Cheongju, one of the historic cities in South Korea. According to the acquired data from the restoration model, it is found that the construction of a new urban area during the late 1930 was resulted from the following events: the development of a railroad station located outside of the north gate of Cheongju-eup since 1921, the completion of Musimcheon embankment outside the south gate in 1932, and the construction of Chungcheongbuk provincial office outside the eastern gate in 1937. In this period of development, which the author named 'Cheongju-eup period', the streets in the old castle, consisting only of two-story financial buildings, had been expanded from the existing area at the Seongan-gil intersection to the outside the east gate of Cheongju-eup. In addition, public government buildings, which were mainly located in both Seongan-gil and Yulgok-ro in the east-west direction, were newly constructed during the late 1930s in Seokgyo-dong, a new area in which a large number of commercial buildings including department stores, clothing stores, shoes shops, and watch stores were also built along the streets. Moreover, the modern form of Cheongju-eup was to be formed by several construction projects in the area of Jungang-ro in the late 1930s. Until the 1920s, the townscape outside the northern gate of Cheongju-eup, were composed of primary, agricultural, and female schools built on a largest site of Gyoseo-ro and Daeseong-ro as well as a transportation warehouse and a railway office near the Cheongju station. Then, entering the 1930s, new school buildings and domestic industrial shops and factories were built around the area of Jungang-ro ranging from the railway outside the northern gate to Bangadari. As a result, the expansion of townscape with newly constructed buildings in the late 1930s marked the emergence of a modern form of Cheongju-eup.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.49-57
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• 2012

An image reconstruction algorithm is proposed to estimate transmitted original images from images displayed on a video terminal. The proposed algorithm acquires images that are displayed on video terminal screens by using a camera. The transmitted images are then estimated with the acquired images. However, camera-acquired images exhibit geometric and color distortions caused by characteristics of the camera and display devices. We make use of a geometric distortion correction algorithm that exploits homography and color distortions using a weighted-linear model. The experimental results show that the proposed algorithm yields promising estimation performance with respect to the peak signal-to-noise ratio (PSNR). PSNR values of the estimated images with respect to the corresponding original images range from 28-29 dB.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.212-227
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• 2008

Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.117-124
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• 2008

The approaches to overcome the limited spatial resolution and the limited dynamic range of image sensors have been studied independently. A high resolution image is reconstructed from multiple low resolution observations and a wide dynamic range image is reconstructed from differently exposed multiple low dynamic range in es based on signal processing approach. In practical situations, it is reasonable to address them in a unified context because the recorded image suffers from limitations of both spatial resolution and dynamic range. In this paper, the image acquisition process including limited spatial resolution and limited dynamic range is modelled. With the image acquisition model, the response function of the imaging system is estimated and the single image of which spatial resolution and dynamic range are simultaneously enhanced is obtained. Experimental results indicate that the proposed algorithm outperforms the conventional approaches that perform the high resolution and wide dynamic range reconstruction sequentially with respect to both objective and subjective criteria.

• International Journal of Highway Engineering
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• v.1 no.1
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• pp.107-119
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• 1999

The joints in the jointed concrete pavement provide a control against transverse or longitudinal cracking at slab, which may be caused by temperature or moisture variation during or after hydration. Without control of cracking, random cracks cause more serious distresses and result in structural or functional failure of pavement system. However, joints nay cause distresses due to its inherent weakness in structural integrity. Thus, the evaluation at joint is very important. and the joint-related distresses should be evaluated reasonably for economic rehabilitation. The purpose of this paper was to develop an evaluation system at joints of jointed concrete pavement using finite element analysis program, ILLI-SLAB, and nondestructive testing device. FWD. To develop an evaluation system for JCP, a sensitivity analysis was performed using ILLI-SLAB program with a selected variables which might affect fairly to on the performance of transverse joints. The most significant variables were selected from precise analysis. An evaluation charts were made for jointed concrete pavement by adopting the field FWD data. It was concluded that the variables which most significantly affect to pavement deflections are the modulus of subgrade reaction(K) and the modulus of dowel/concrete interaction(G), and limiting criteria on the performance of joints at JCP are 300pci. 500,000 lb/in. respectively. Using these variables and FWD test, a charts of load transfer ratio versus surface deflection at joints were made in order to evaluate the performance of JCP. Practically, Chungbu highway was evaluated by these evaluation charts and FWD field data for jointed concrete pavement. For Chungbu highway, only one joint showed smaller value than limiting criterion of the modulus of dowel/concrete interaction(G). The rest joints showed larger values than limiting criteria of the modulus of subgrade reaction(K) and the modulus of dowel/concrete interaction(G).

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.262-268
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• 2010

In this paper, this study restores the distorted image to its original image by compensating for the distortion of image from a fixed-focus camera lens. The various developments and applications of the imaging devices and the image sensors used in a wide range of industries and expanded use, but due to the needs of the small size and light weight of the camera, the distortion from acquiring images of the distorted curvature of the lens tends to affect many. In particular, the three-dimensional imaging camera, each different distortion of left and right lens cause the degradation of three-dimensional sensitivity and left-right image distortion ratio. we approached the way of generalizing the approximate equations to restore each part of left-right camera images to the coordinators of the original images. The adaptive Neuro-Fuzzy Inference System is configured for it. This system is divided from each membership function and is inferred by 1st order Sugeno Fuzzy model. The result is that the compensated images close to the left, right original images. Using low-cost and compact imaging lens by which also determine the exact three-dimensional image-sensing capabilities and will be able to expect from this study.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.