• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.395-408
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• 2015

High-resolution satellite image mosaics are becoming increasingly important in the field of remote sensing image analysis as an essential image processing to create a large image constructed from several smaller images. In this paper, we present an automatic seamline extraction technique and the procedure to generate a mosaic image by this technique. For more effective seamline extraction in the overlap region of adjacent images, an NDVI-based seamline extraction technique is developed, which takes advantage of the computational time and memory. The Normalized Difference Vegetation Index(NDVI) is an index of plant "greeness" or photosynthetic activity that is employed to extract the initial seamline. The NDVI can divide into manmade region and natural region. The cost image is obtained by the canny edge detector and the buffering technique is used to extract the ranging cost image. The seamline is extracted by applying the Dijkstra algorithm to a cost image generated through the labeling process of the extracted edge information. Histogram matching is also conducted to alleviate radiometric distortion between adjacent images acquired at different time. In the experimental results using the KOMPSAT-2/3 satellite imagery, it is confirmed that the proposed method greatly reduces the visual discontinuity caused by geometric difference of adjacent images and the computation time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.184-187
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• 2010

본 논문에서는 움직임 추정(Motion Estimation, ME), 색상 라벨링(Labeling) 그리고 Non-Local means 필터 등을 이용하여 2D 영상을 3D 입체 영상으로 변환하는 기법을 제안한다. 제안하는 기법에서는 프레임 간의 움직임 추정 방법을 사용하여 물체의 움직임 벡터를 추출하며 색상 라벨링 작업을 통해 세밀한 객체를 추출한다. 객체를 추출한 후 영상을 이동시켜서 우영상을 생성한다. 우 영상을 생성하는 과정에서 채워지지 않은 화소들이 발생하는데 전체 화소의 상관도를 고려하는 Non-local means 필터를 사용하여 이 부분을 처리한다. 생성된 우 영상과 원본 영상인 좌 영상으로 비월주사(interlace)하여 최종 3D 입체 영상을 생성한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.69-78
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• 1996

This paper presetns an iterative relaxation method for stereo matching using matching probability and compatibility coefficients between disparities. Stereo matching can be considered as the labeling problem of assigning unique matches to feature points of image an relaxation labelin gis an iterative procedure which reduces local ambiguities and achieves global consistency. the relation between disparities is determined from highly reliable matches in initial matching and quantitatively expressed in temrs of compatibility coefficient. The matching results of neighbor pixels support center pixel through compatibility coefficients and update its matching probability. The proposed adaptive method reduces the degradtons on the discontinuities of disparity areas and obtains fast convergence.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.67-74
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• 2001

In this paper, we propose a face detection algorithm using the color and shape information in color still images. The proposed algorithm is only applied to chrominance components(Cb and Cr) in order to reduce the variations of lighting condition in YCbCr color space. Input image is segmented by pixels with skin-tone color and then the segmented mage follows the morphological filtering an geometric correction to eliminate noise and simplify the segmented regions in facial candidate regions. Multiple facial regions in input images can be isolated by connected component labeling. Moreover tilting facial regions can be detected by extraction of second moment-based ellipse features.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.605-613
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD (Head Mounted Display) to control the tele-operated vision system on the mobile robot. In the preexistence tele-operated vision system, a joystick was used to control the pan-tilt unit of the remote camera system. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image. The simple experiment is conducted to demonstrate the feasibility.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.655-658
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• 2003

The crack of concrete structure plays an important role in the durability and safety of structure. Therefore, the features such as width, length, and direction of that must be measured periodically. The conventional method of measurement of cracks is manually sketched, however. it takes a fairly long time and lacks quantitative objectivity. This study proposes the algorithm to extract and analyze cracks automatically. The proposed algorithm is composed of two sub-algorithms. The extraction algorithm includes elimination of effect due to light, binarization. and noise reduction. The analysis algorithm includes thinning process, labeling, and calculation of crack width, length, and direction. The test to demonstrate the algorithm is fulfilled using the images of cracks on real concrete surface.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.360-362
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD(Head Mounted Display) using the feature points detection to control the tele-operated vision system on the mobile robot. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image.

• The Korean Journal of Nuclear Medicine
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• v.34 no.3
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• pp.159-168
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• 2000

In the 1980s, techniques to image the human subjects in a three-dimensional direction were developed. Two major techniques are SPECT (Single Photon Emission Computed Tomography) and PET (Positron Emission Tomography) which allow the detector to detect a single photon or annihilation photons emitted from the subjects injected with radiopharmaceuticals. Since the latter two techniques can measure the density of receptors, enzymes and transporters in living human, it may be very important project to develop selective methods of labeling with radionuclides and to develop new radiopharmaceuticals. There has been a considerable interest in developing new compounds which specifically bind to dopamine and serotonin receptor and transporters, and it will be thus very useful to label those compounds with radionuclides in order to gain a better understanding in biochemical and pharmacological interactions in living human. This review mentions the characteristics of radioligands for the imaging of dopamine and serotonin receptors and transporters. Although significant progress has been achieved in the development of new PET and SPECT ligands for in vivo imaging of those receptors and transporters, there are continuous needs of new diagnostic radioligands.

• Journal of Platform Technology
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• v.6 no.1
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• pp.3-8
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• 2018

This paper proposes a technique for recognizing online handwritten cursive data obtained by tracing a motion trajectory while a user is in the 3D space based on a convolution neural network (CNN) algorithm. There is a difficulty in recognizing the virtual character input by the user in the 3D space because it includes both the character stroke and the movement stroke. In this paper, we divide syllable into consonant and vowel units by using labeling technique in addition to the result of localizing letter stroke and movement stroke in the previous study. The coordinate information of the separated consonants and vowels are converted into image data, and Korean handwriting recognition was performed using a convolutional neural network. After learning the neural network using 1,680 syllables written by five hand writers, the accuracy is calculated by using the new hand writers who did not participate in the writing of training data. The accuracy of phoneme-based recognition is 98.9% based on convolutional neural network. The proposed method has the advantage of drastically reducing learning data compared to syllable-based learning.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.85-88
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• 2009

In this paper, we propose a DRF-based object detection method using the object adaptive patch in the satellite imagery. It is a Discriminative Random Fields (DRF) based work, so the detection is done by labeling to the possible patches in the image. For the feature information of each patch, we use the multi-scale and object adaptive patch and its texton histogram, instead of using the single scale and fixed grid patch. So, we can include contextual layout of texture information around the object. To make object adaptive patch, we use "superpixel lattice" scheme. As a result, each group of labeled patches represents the object or object's presence region. In the experiment, we compare the detection result with a fixed grid scheme and shows our result is more close to the object shape.