• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.40-47
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• 2006

This paper proposes a multitoning method using threshold modulation of MJBNM(Modified Jointly Blue Noise Mask) for banding artifacts reduction. As banding artifacts in multitoning appear as uniform dot distributions around the intermediate output levels, such multitone output results in discontinuity and visually unpleasing patterns in smooth transition regions. Therefore, to reduce these banding artifacts, the proposed method rearranges the dot distribution by introducing pixels in the neighborhood of output levels that occurs banding artifacts. First of all principal cause of banding artifacts are analyzed using mathematical description. Based on this analytical result, a threshold modulation technique of MJBNM which takes account of chrominance error and correlation between channels is applied. The original threshold range of MJBNM is first scaled linearly sot that the minimum and maximum of the scaled range include two pixel more than adjacent two output levels that cover an input value. In an input value is inside the vicinity of any intermediate output levels produce banding artifacts, the output is set to one of neighboring output levels based on the pointwise comparison result according to threshold modulation parameter that determines the dot density and distribution. In this case, adjacent pixels are introduced at the position where the scaled threshold values are located between two output levels and the minimum and maximum threshold values. Otherwise, a conventional multitoning method is applied. As a result, the proposed method effectively decreased the appearance of banding artifacts around the intermediate output levels. To evaluate the quality of the multitone result, HVS-WRMSE according to gray level for gray ramp image and S-CIELAB color difference for color ramp image are compared with other methods.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.355-358
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• 2012

배경 영상에서 움직이는 물체 검출은 대상의 정확한 분류나 움직임, 패턴의 이해 또는 감시 시스템에 활용이 된다. 동적 물체 검출을 위한 여러 방법이 연구되고 제시되었으며, 그 중 일반적으로 차 영상 검출 방법이 많이 사용된다. 이는 시간적으로 연속된 영상 프레임간의 차를 구하고, 이 차 영상에 임계값을 설정하여 이진 영상을 만들어 물체를 검출한다. 기존 여러 연구에서는 이 임계값을 대부분을 고정하여 사용하거나 특정 환경에만 적합하게 설정하였다. 본 논문에서는 주변 환경에 적응하여 임계값을 자동으로 설정하는 방법을 제시하였고, 차 영상 검출 방법에 실제 적용하여 기존 방법에 비해 더 나은 결과를 확인하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.2
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• pp.57-64
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• 2015

At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.137-151
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• 2017

The space between urban buildings becomes a waterway during rain events and requires a boundary condition in numerical calculations on grids to separate overland storm flows from building areas. Minimization of the building data distortion as a boundary condition is a necessary step for generating accurate calculation results. A building generalization is used to reduce the distortion of building shapes and areas during a raster conversion. The objective of this study was to provide the appropriate threshold value for building generalization and grid size in a numerical calculation. The impact of building generation on the connectivity of urban storm waterways were analyzed for a general residential area. The building generalization threshold value and the grid size for numerical analysis were selected as the independent variables for analysis, and the number and area of sinks were used as the dependent variables. The values for the building generalization threshold and grid size were taken as the optimal values to maximize the building area and minimize the sink area. With a 3 m generalization threshold, sets of $5{\times}5m$ to $10{\times}10m$ caused 5% less building area and 94.4% more sink area compared to the original values. Two sites representing general residential area types 2 and 3 were used to verify building generalization thresholds for improving the connectivity of storm waterways. It is clear that the recommended values are effective for reducing the distortion in both building and sink areas.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.663-673
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• 2010

As a tool used for video maintenance, Video segmentation divides videos in hierarchical and structural manner. This technique can be considered as a core technique that can be applied commonly for various applications such as indexing, abstraction or retrieval. Conventional video segmentation used adaptive threshold to split video by calculating difference between consecutive frames and threshold value in window with fixed size. In this case, if the time difference between occurrences of cuts is less than the size of a window or there is much difference in neighbor feature, accurate detection is impossible. In this paper, Improved Adaptive threshold algorithm which enables determination of window size according to video format and reacts sensitively on change in neighbor feature is proposed to solve the problems above. Post-Processing method for decrement in error caused by camera flash and fast movement of large objects is applied. Evaluation result showed that there is 3.7% improvement in performance of detection compared to conventional method. In case of application of this method on modified video, the result showed 95.5% of reproducibility. Therefore, the proposed method is more accurated compared to conventional method and having reproducibility even in case of various modification of videos, it is applicable in various area as a video maintenance tool.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.487-496
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• 2011

This study is aimed to perform more reliable unsupervised change detection through the re-extraction of the changed pixels which were extracted with global thresholding by applying buffer zone concept. First, three buffer zone was divided on the basis of the thresholding value which was determined using range average and the maximum distance point from a straight line. We re-extracted the changed pixels by performing unsupervised classification for buffer zone II which consists of changed pixels and unchanged pixels. The proposed method was implemented in Hyperion hyperspectral images and evaluated comparing to the existing global thresholding method. The experimental results demonstrated that the proposed method performed more accuracy change detection for vegetation area even if extracted slightly more changed pixels.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.167-170
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• 2007

동일한 집단에 속하는 개체를 다른 집단에 속하는 개체로부터 구별할 수 있는 염기의 특징을 해당 집단의 시그너쳐라고 한다. 학습 데이터는 두 집단에 속하는 염기서열들이고, 염기서열에 대한 시그너쳐는 개체를 다른 집단과 구별할 수 있는 위치의 염기들로 구성된 서열이다. 제안한 방법에서는 각 집단에 대해서 위치별로 염기의 발생빈도를 계산하고, 가장 발생빈도가 높은 염기를 결정한 다음, 다른 집단의 대응 위치에서 해당 염기의 빈도를 계산하여, 빈도차이가 지정한 분류임계값 이상이면, 해당 위치의 염기를 시그너쳐를 구성하는 특징으로 간주한다. 시그너쳐를 대한 임의의 염기서열에 대한 부합정도는 시그너쳐에 속하는 염기의 학습집단에서의 상대빈도값을 가중치로 하여 계산한다. 임의의 염기서열이 특정 집단에 속하는지 판단하기 위해서는 해당 집단의 시그너쳐에 대한 부합정도를 계산하게 되는데, 부합정도가 얼마이상이 되어야 해당 집단에 속하는 것으로 간주할지 기준이 되는 임계값을 엄밀도 임계값이라고 한다. 엄밀도 임계값은 학습 데이터 집합에 대해서 주어진 시그너쳐에 대한 엄밀도 임계값이 민감도와 특이도를 최대로 하는 것을 선택한다. 제안한 방법을 구현한 바이오인포매틱스 도구를 개발하여, 한국형 HIV-1 바이러스 시그너쳐 추출에 적용하여 분류특성이 우수한 시그너쳐를 추출할 수 있음을 확인하였다.

• Journal of Digital Contents Society
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• v.16 no.6
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• pp.951-959
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• 2015

Scene text extraction is important because it offers some important information on different image based applications pouring in current smart generation. Edge-Enhanced MSER(Maximally Stable Extremal Regions) which enhances the boundaries using the canny operator after extracting the basic MSER shows excellent performance in terms of text extraction. But according to setting the threshold of the canny operator, the result images using Edge-Enhanced MSER are different, so there needs a method figuring out the threshold. In this paper, we propose a AEMSER(Adaptive Edge-enhanced MSER) that applies the method extracting the boundary using the middle value of histogram to Edge-Enhanced MSER to get the canny operator's threshold. The proposed method can acquire better result images than the existing methods because it extracts the area only for the obvious boundaries.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.275-278
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• 2003

본 논문에서는 영상의 국부적인 특성을 고려한 임계값 변조치를 적용한다. 먼저 원영상과 해프토닝 영상의 선형이득을 이용해 평탄영역에 대한 오차를 최소화하는 임계값 변조치를 구한다. 그리고 이 값들에 경계정보에 따른 보정값을 주어 경계영역을 표현한다. 제안방법은 해프토닝시 발생하는 오차를 줄여 오차로 인해 발생하는 영상내의 뭉쳐짐 현상과 웜 현상 등을 최소화하여 기존의 방법에 비해 더 좋은 화질을 얻을 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.607-608
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• 2009

최근 7.7 DDoS 대란과 폭발적인 SPAM 발송과 같은 다양한 봇넷의 악성행위는 정보 시스템에 막대한 악영향을 미친다. 특히, 봇넷의 구조적 특징인 좀비PC의 제어는 네트워크 환경에서는 다양한 악성 행위를 유발한다. 때문에, 봇넷 탐지와 관련한 다양한 연구가 시도되었지만, 탐지의 한계점을 지니고 있다. 즉, 기존의 봇넷 탐지 방법은 임의의 임계값을 설정하고, 그 값을 벗어나는 시점에서 경고를 보내어 탐지하게 된다. 하지만, 전문가에 의한 임계값 설정은 자칫 오탐율과 미탐율을 야기할 수 있다. 따라서, 본 논문에서는 봇넷 탐지를 보다 능동적으로 하기 위하여 특정 타임 윈도우 구간동안의 봇넷이 유발하는 네트워크 트래픽을 분석하고 마르코프 체인을 응용한 학습을 하여 능동적으로 적용 가능한 임계값을 측정 방법론에 대하여 고찰하고자 한다.