• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.17-26
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• 2005

In this paper we propose three nonparametric tests such as Wilcoxon test, Median test and Van der Waerden test, based on linear rank statistics for detecting edges in images. The methods used herein are based on detecting changes in gray-levels obtained using an edge-height parameter between two sub-regions in a 5$\times$5 window We compare and analysis the performance of three statistical edge detectors in terms of qualitative measures with the edge maps and objective, quantitative measures.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.147-157
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• 2007

Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.9-15
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• 2006

In this paper we propose Wilcoxon test, Median test and Van der Waerden test such as linear rank tests in two-sample location problem for detecting edges effectively in noisy images. These methods are based on detecting image intensity changes between two pixel neighborhoods using an edge-height model to perform effectively on noisy images. The neighborhood size used here is small and its shape is varied adaptively according to edge orientations. We compare and analysis the performance of these statistical edge detectors on both natural images and synthetic images with and without noise.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.197-201
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• 2004

We describe a new edge detector based on the robust rank-order (RRO) test which is a useful alternative to Wilcoxon test, using $r{\times}r$ window for detecting edges of all possible orientations in noisy images. Some experiments of statistical edge detectors based on the Wilcoxon test and T test with our RRO detector are carried out on synthetic and real images corrupted by both Gaussian and impulse noise. We also implement these edge detectors using Java on the Web.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.59-66
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• 2005

The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

• Communications of the Korean Mathematical Society
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• v.30 no.2
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• pp.65-72
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• 2015

The minimum rank mr(G) of a simple graph G is defined to be the smallest possible rank over all symmetric real matrices whose (i, j)-th entry (for $i{\neq}j$) is nonzero whenever {i, j} is an edge in G and is zero otherwise. The corona $C_n{\circ}K_t$ is obtained by joining all the vertices of the complete graph $K_t$ to each n vertex of the cycle $C_n$. For any t, we obtain an upper bound of zero forcing number of $L(C_n{\circ}K_t)$, the line graph of $C_n{\circ}K_t$, and get some bounds of $mr(L(C_n{\circ}K_t))$. Specially for t = 1, 2, we have calculated $mr(L(C_n{\circ}K_t))$ by the cut-vertex reduction method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.13-21
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• 1988

In order to overcome the disadvantages of linear filters in certain cases of practical interest, a class of nonlinear filters(rank filters) are constructed based on a class of robust estimates, the rank estimates. A subclass of these filters, the limited-degree extended-averaging Wilcoxon filters, is then described as an interesting example of the rank filters with desirable characteristics. The properties of these filters are discussed and the performance of these filters are analyzed for ideal edges and narrow pulses.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.4
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• pp.274-278
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• 2021

Road structures play an important role in collisions involving vehicles and wildlife. Our study aimed to determine the effect of various types of road structures on the risk associated with roadkill. We surveyed 50 previously identified roadkill hotspots, ranked from one to five according to roadkill density. We collected nine types of road structure data on each hotspot road section. Structures with similar characteristics were grouped together, resulting in five categories, namely, median barrier, high edge barrier, low edge barrier, speed, and visibility. We examined the existence of each road structure category at each hotspot rank. The cumulative link model showed that the absence of bottom blocked median barrier increased the roadkill hotspot rank. Our study concluded that a visual obstacle in the middle of roads by the median barrier decreases wildlife road crossing attempts and roadkill risk. We suggest that future roadkill mitigation plans should be established considering these characteristics.