• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.725-730
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• 2007

Gray-level histogram-based threshold selection methods such as Otsu's method, Huang and Wang's method, and etc. have been widely used for the threshold selection in image processing. They are simple and effective, but take too much time to determine the optimal multilevel threshold values as the number of thresholds are increased. In this paper, we measure correlation between gray-levels by using the Gaussian function and define a Gaussian-type finite mixture distribution which is combination of the Gaussian distribution function with the gray-level histogram, and propose a fast and effective threshold selection method using it. We show the effectiveness of the proposed through experimental results applied it to three images and the efficiency though comparison of the computational complexity of the proposed with that of Otsu's method.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.8-17
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• 2008

A new algorithm for automatic extraction of interesting objects is proposed in this paper. The proposed algorithm can be summarized in two steps. First, segmentation of color image that split interesting objects and backgrounds is performed. According to the research stating, 'Humans perceive things by contracting color into three to four essential colors,' a color image is segmented into three regions utilizing k-mean algorithm, followed by annexing the regions when the similarities of them exceeds the critical value based on the calculation of degrees in the histogram similarity, Second, identifying the interesting objects out of the segmented image, partitioned by the image composition theory, is performed. To have a good picture, it is important to adjust positions of interesting objects according to picture composition. Extracting objects is a retro-deduction process using a weighted mask designed upon the triangular composition of picture. To prove the quality of the proposed method, experiments are performed over four hundreds images as well as comparison with recently proposed KMCC and GBIS methods.

• Radiation Oncology Journal
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• v.37 no.2
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• pp.127-133
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• 2019

Purpose: The aim of this study was to identify volume changes and dose variations of rectum and bladder during radiation therapy in prostate cancer (PC) patients. Materials and Methods: We analyzed 20 patients with PC treated with helical tomotherapy. Daily image guidance was performed. We re-contoured the entire bladder and rectum including its contents as well as the organ walls on megavoltage computed tomography once a week. Dose variations were analyzed by means of Dmedian, Dmean, Dmax, V₁₀ to V₇₅, as well as the organs at risk (OAR) volume. Further, we investigated the correlation between volume changes and changes in Dmean of OAR. Results: During treatment, the rectal volume ranged from 62% to 223% of its initial volume, the bladder volume from 22% to 375%. The average Dmean ranged from 87% to 118% for the rectum and 58% to 160% for the bladder. The Pearson correlation coefficients between volume changes and corresponding changes in Dmean were -0.82 for the bladder and 0.52 for the rectum. The comparison of the dose wall histogram (DWH) and the dose volume histogram (DVH) showed that the DVH underestimates the percentage of the rectal and bladder volume exposed to the high dose region. Conclusion: Relevant variations in the volume of OAR and corresponding dose variations can be observed. For the bladder, an increase in the volume generally leads to lower doses; for the rectum, the correlation is weaker. Having demonstrated remarkable differences in the dose distribution of the DWH and the DVH, the use of DWHs should be considered.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.279-284
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• 2010

The plane curve approach which was proposed by Boukharouba et. al. is a multi-threshold selection method through searching peak-valley based on histogram cumulative distribution function. However the method is required to select parameters to compose plane curve, and the shape of plane curve is affected according to parameters. Therefore detection of peak-valley is effected by parameters. In this paper, we propose an entropy maximizing-based method to select optimal plane curve parameters, and propose a multi-thresholding method based on the selected parameters. The effectiveness of the proposed method is demonstrated by multi-thresholding experiments on various images and comparison with other conventional thresholding methods based on histogram.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.255-262
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• 2007

This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, $YC_bC_r$, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

• Radiation Oncology Journal
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• v.38 no.1
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• pp.60-67
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• 2020

Purpose: We performed three-dimensional (3D) dose reconstruction-based pretreatment verification to evaluate gamma analysis acceptance criteria in volumetric modulated arc therapy (VMAT) for prostate cancer. Materials and Methods: Pretreatment verification for 28 VMAT plans for prostate cancer was performed using the COMPASS system with a dolphin detector. The 3D reconstructed dose distribution of the treatment planning system calculation (TC) was compared with that of COMPASS independent calculation (CC) and COMPASS reconstruction from the dolphin detector measurement (CR). Gamma results (gamma failure rate and average gamma value [GFR and γAvg]) and dose-volume histogram (DVH) deviations, 98%, 2% and mean dose-volume difference (DD_98%, DD_2% and DD_mean), were evaluated. Gamma analyses were performed with two acceptance criteria, 2%/2 mm and 3%/3 mm. Results: The GFR in 2%/2 mm criteria were less than 8%, and those in 3%/3 mm criteria were less than 1% for all structures in comparisons between TC, CC, and CR. In the comparison between TC and CR, GFR and γAvg in 2%/2 mm criteria were significantly higher than those in 3%/3 mm criteria. The DVH deviations were within 2%, except for DD_mean (%) for rectum and bladder. Conclusions: The 3%/3 mm criteria were not strict enough to identify any discrepancies between planned and measured doses, and DVH deviations were less than 2% in most parameters. Therefore, gamma criteria of 2%/2 mm and DVH related parameters could be a useful tool for pretreatment verification for VMAT in prostate cancer.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.338-348
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• 1997

In this pater, we first propose a data distribution framework to resolve load imbalance and bucket oerflow in parallel hash join.Using the histogram equalization technique, the framework transforms a histogram of skewed data to the desired uniform distribution that corresponds to the relative computing power of node processors in the system.Next we propose an effcient parallel hash join algorithm for handing skwed data based on the proposed data distribution methodology.For performance comparison of our algorithm with other hash join algorithms.we perform similation experiments and actual exeution on COREDB database computer with 8-node hyperube architecture. In these experiments, skwed data distebution of the join atteibute is modeled using a Zipf-like distribution.The perfomance studies undicate that our algorithm outperforms other algorithms in the skewed cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1284-1289
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• 2016

Recently, digital image processing is applied a lot to the broadcasting, communication, computer graphic, and medical sectors. It generates noise when data is transmitted. There are many kinds of noises that add to the image such as salt and pepper noise, AWGN, and complex noise. Thus, this study divides the corrupted image into four4 areas and estimates the types of noises each pixel, and this study suggested a switching filter that separates the estimated into salt and pepper noise and AWGN. In the case that center pixel of local mask is corrupted by salt and pepper noise, it used a histogram probability weighting of subdivided area. Also, in case that it is corrupted by AWGN, algorithm that is applied to with different weights given for the distribution of each area with using subdivided area's distribution was suggested. For an objective comparison and conclusion, this study used PSNR and compared to existing methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.137-146
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• 2015

In this paper, we propose a pothole detection method using various features of intensity and motion. Segmentation, decision steps of pothole detection are processed according to the values which are derived from feature characteristics. For segmentation using intensity, we use a binarization method using histogram to separate pothole region from background. For segmentation using motion, we filter using high pass filter and get standard deviation value. This value is divided by regression value according to camera environment such as photographing angle, height, velocity, etc. We get binary image by histogram based binarization. For decision, candidate regions are decided whether pothole or not using comparison of candidate and background's features. Experimental results show that our proposed pothole detection method has better results than existing methods and good performance in discrimination between pothole and similar patterns.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.563-566
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• 2003

Quality measures play an important role in the field of image processing. Such measures are commonly used to assess the performance of different algorithms that are designed to perform a specific image processing task. In this paper we propose two novel measures for image quality assessment based on the notion of correlation between fuzzy sets. Two different definitions fur the correlation between fuzzy sets have been used. In order to calculate the proposed quality measures two approaches were evaluated, one with direct application of the measures to the image′s pixels and the other using the fuzzy set corresponding to the normalized histogram of the image. A comparative study of the proposed measures is performed by investigating their behavior using images with different types of distortions, such as impulsive "salt at pepper" noise, additive white Gaussian noise, multiplicative speckle noise, blurring, gamma distortion, and JPEG compression.