• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1677-1683
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• 2006

Color image segmentation is useful for fast retrieval in large image database. For that purpose, new image segmentation technique based on the probability of pixel distribution in the image is proposed. Color image is first divided into R, G, and B channel images. Then, pixel distribution from each of channel image is extracted to select to which it is similar among the well known probabilistic distribution function-Weibull, Exponential, Beta, Gamma, Normal, and Uniform. We use sum of least square error to measure of the quality how well an image is fitted to distribution. That P.d.f has minimum score in relation to sum of square error is chosen. Next, each image is quantized into 4 gray levels by applying thresholds to the c.d.f of the selected distribution of each channel. Finally, three quantized images are combined into one color image to obtain final segmentation result. To show the validity of the proposed method, experiments on some images are performed.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.53.4-53.4
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• 2019

We reconstruct the underlying dark matter (DM) density distribution of the local universe within 20Mpc/h cubic box by using the galaxy position and peculiar velocity. About 1,000 subboxes in the Illustris-TNG cosmological simulation are used to train the relation between DM density distribution and galaxy properties by using UNet-like convolutional neural network (CNN). The estimated DM density distributions have a good agreement with their truth values in terms of pixel-to-pixel correlation, the probability distribution of DM density, and matter power spectrum. We apply the trained CNN architecture to the galaxy properties from the Cosmicflows-3 catalogue to reconstruct the DM density distribution of the local universe. The reconstructed DM density distribution can be used to understand the evolution and fate of our local environment.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.990-1002
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• 2016

In this paper, we propose a new compression method for the edge image by analyzing the characteristics and the distribution of pixel values of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are `0`. By these analyses we suggest the Zero-Based codec that expresses all values in a CU by a single bit flag. Also, in order to reduce the computational complexity of the proposed codec, the block partition and the intra-prediction techniques are proposed by using edge information like the number of each edge direction, the distribution and the amplitude of a major edge direction in the CU. Experimental results show that the proposed codec leads to a slighter distortion in Y domain than that of HEVC, but has far faster processing speed up to 53 times while it maintains the similar image quality compared to HEVC.

• The Journal of Korean Physical Therapy
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• v.25 no.5
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• pp.260-265
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• 2013

Purpose: This study was conducted in order to evaluate the quantitative effectiveness of region of interest (ROI) setting in MR-DTI analysis with and without fMRI activation results. Methods: Ten right-handed normal volunteers participated in this study. DTI and fMRI datasets for each subject were obtained using a 1.5T MRI system. For neural fiber tracking, ROIs were drawn using two methods: The drawing points were located in the fMRI activation areas or areas randomly selected by users. In this study, the neural fiber tract targeted the corticospinal tract (CST) Quantitative analyses were performed and compared. The pixel numbers passing through the fiber tract in the individual brain volume were counted. The ratios between the ROI pixel numbers and the extracted fiber pixel numbers, and the ratios between the fiber pixel numbers and the whole-brain pixel numbers were also calculated. Results: According to our results, extracted CST fiber tract in which the ROI was drawn with fMRI activation areas showed higher distribution than drawing the ROI by users' hands. In addition, the quantitatively measured values represented higher pixel distribution: The counted average pixel numbers were 4553.8 and 1943.3. The average ratios of the ROI areas were 33.87 and 22.52. The average percentages of the individual whole-brain volume numbers were 2.06 and 0.87. Conclusion: Results of this study appear to indicate that use of this method can allow for more objectives and significant for study of the recovery of neural fiber mechanisms and brain rehabilitation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.294-297
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• 2012

본 논문에서는 컬러 영상의 검색을 위하여 영상을 색상 정보에 기반한 pixel layer (cluster)의 집합체로 모델링하고, 두 layer 간의 유사도를 각 layer 를 이루는 pixel 들의 색상 분포에 따른 공간적 분포를 이용하여 측정하는 기법을 제안한다. 먼저 pixel layering 단계에서는 HSV 색 공간에서 mean-shift clustering 알고리즘을 통해 초기 layer 들을 얻고, 비슷한 색상의 layer 들은 합쳐 영상의 soft segmentation 과 유사한 결과를 얻는다. 비교할 두 영상에서 pixel layering 을 한 후, 각 layer 를 이진화된 공간분포 지도로 형성하고 그 차이를 비교함으로써 유사도를 측정한다. 이 때, 사용하는 가중치로서 HSV 색 공간 분포의 비슷한 정도를 정의하는데, 이는 HSV 색 공간을 XYZ 의 3 차원 좌표로 설정하고, overlap 되는 pixel 수로 정의하였다. 본 논문에서 제안한 pixel layer 들 간의 색상 공간 분포에 따른 공간적 분포를 이용한 영상 검색 기법은 MPEG-7 에서 정의한 대표색상 기반의 영상 검색보다 우수한 성능을 보여주었다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.578-597
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• 2014

Understanding of 'spatial' pressure distribution is required to determine design loads on local structures, such as plating and framing. However, obtaining a practical 'spatial' pressure distribution is a hard task due to the sensitivity of the data acquisition frequency and resolution. High-resolution Pessure-Idicating Flm (PIF) was applied to obtain pressure distribution and pressure magnitude using stepped crushing method. Different types of PIF were stacked at each test to creating a pressure distribution plot at specific time steps. Two different concepts of plotting 'spatial' pressure-area curve was introduced and evaluated. Diverse unit pixel size was chosen to investigate the effect of the resolution in data analysis. Activated area was not significantly affected by unit pixel size; however, total force was highly sensitive.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.259-262
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• 2012

In this paper, we propose a new fast algorithm for effective scene change detection. The proposed algorithm exploits Otsu threshold matching technique, which was proposed earlier. In this method, the current and the reference frames are divided into square blocks of particular size. After doing so, the pixel histogram of each block is generated. According to Otsu method, every histogram distribution is assumed to be bimodal, i.e. pixel distribution can be divided into two groups, based on within-group variance value. The pixel value that minimizes the within-group variance is said to be Otsu threshold. After Otsu threshold is found, the same procedure is performed at the reference frame. If the difference between Otsu threshold of a block in the current frame and co-located block in the reference frame is larger than predefined threshold, then a scene change between those two blocks is detected.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.44-49
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• 2022

Abstract Recently, with the development of IoT technology and communication media, various video equipment is being used in industrial fields. Image data acquired from cameras and sensors are easily affected by noise during transmission and reception, and noise removal is essential as it greatly affects system reliability. In this paper, we propose a weight filter algorithm based on the pixel value distribution pattern to preserve details in the process of restoring images damaged in AWGN. The proposed algorithm calculates weights according to the pixel value distribution pattern of the image and restores the image by applying a filtering mask. In order to analyze the noise removal performance of the proposed algorithm, it was simulated using enlarged image and PSNR compared to the existing method. The proposed algorithm preserves important characteristics of the image and shows the performance of efficiently removing noise compared to the existing method.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.2
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• pp.397-405
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• 1999

Purpose: To clarify the usefulness and the limitation of Digora system/sup (R)/ by evaluating the physical characteristics as the quantitative image on Image Plate(Ip). Materials and Methods: Radiograms were taken by Heliodent MD(Siemens Co.. Germany) with the image plate for adult. Cu-step wedge as reference material. and three pieces of dry mandibular bone. Image analysis was performed by single color enhancement. density measurement with histogram. The relationship between the exposure conditions and the distribution of the pixel values of the image. the variation of pixel values of each step of Cu-step wedge at two different area and Cu-equivalent value of three pieces of dry mandibular bone measure by the conversion equation. Results: There was no linear relationship between the exposure condition and the average pixel value of the image. of which the distribution was not even. The pixel value differences between the center portion and the periphery were ranged from 60 to 70 in vertical plane and from 15 to 26 in horizontal plane. Two plot profile formed at two different areas of the Cu-step wedge were different. The measured Cu-equivalent values showed the discrepancy among the times of measurement. Conclusion: As above results. Image Plate(Ip) of Digora system/sup (R)/ showed the limitation as the quantitative image. The physical property of IP was expected to need to be compensated for the quantitative evaluation of the bone or others

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.312-322
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• 2015

In this paper a new defect detection method for flat panel display that does not require any separately prepared reference images and shows robustness against problems with regard to pixel tolerance and nonuniform illumination condition is proposed. In order to perform defect detection under any magnification value of camera, the proposed method automatically obtains the value of pattern interval through an image analysis. Using the information for pattern interval, an advanced PCSR-G method presented in this paper utilizes neighboring patterns as its reference images instead of utilizing any separately prepared reference images. Also this paper proposes a scheme to improve the performance of the conventional PCSR-G method by extracting and applying additional information for pixel tolerance and intensity distribution considering the value of pattern interval. Simulation results show that the performance of the proposed method utilizing pixel tolerance and intensity distribution is superior to that of the conventional method. Also, it is proved that the proposed method that is implemented using parallel technique based on GPGPU can be applied to real system.