• Title/Summary/Keyword: SIFT

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A Study on the Policy Convergence of Forest Policy : A Paradigm Sift to Convergence between Forest Development and Preservation (산림정책융합에 관한 연구 : 산림이용·개발 및 보전의 융합패러다임으로의 변화)

  • Chang, Je-Won;Park, Yong-Sung
    • Journal of Digital Convergence
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    • v.13 no.6
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    • pp.13-28
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    • 2015
  • In accordance with importance of the economic value of forests and forest use, the paradigm of development and use has emerged as the dominant paradigm of forest policy. As forests are recognized as an important means of Wellness, the government pursues a policy convergence between forest use and conservation. So, this article analyzed whether the change of forestry convergence paradigm is reflected in policy or not. The purpose of this study was to analyze through content analysis and network analysis, whether the new combined text value are fused in how forest policy. According to the results, the function of utilization which is off the traditional forestry industry and recreation, wellness are acquired a greater importance in the 5th plan than 4th plan. But the 5th plan is insufficient to establish of foundation for forestry management and welfare functions. The evidence suggest a sign of sustained paradigm convergency in forest policy of Korea. As the policy implication in establishing national forest master plan, it is necessary to strengthen policy capability to pursue sustainable forestry utilization, which can converge forest use and conservation.

Multi-Object Detection Using Image Segmentation and Salient Points (영상 분할 및 주요 특징 점을 이용한 다중 객체 검출)

  • Lee, Jeong-Ho;Kim, Ji-Hun;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.2
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    • pp.48-55
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    • 2008
  • In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.

Exome sequencing in a breast cancer family without BRCA mutation

  • Noh, Jae Myoung;Kim, Jihun;Cho, Dae Yeon;Choi, Doo Ho;Park, Won;Huh, Seung Jae
    • Radiation Oncology Journal
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    • v.33 no.2
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    • pp.149-154
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    • 2015
  • Purpose: We performed exome sequencing in a breast cancer family without BRCA mutations. Materials and Methods: A family that three sisters have a history of breast cancer was selected for analysis. There were no family members with breast cancer in the previous generation. Genetic testing for BRCA mutation was negative, even by the multiplex ligation-dependent probe amplification method. Two sisters with breast cancer were selected as affected members, while the mother of the sisters was a non-affected member. Whole exome sequencing was performed on the HiSeq 2000 platform with paired-end reads of 101 bp in the three members. Results: We identified 19,436, 19,468, and 19,345 single-nucleotide polymorphisms (SNPs) in the coding regions. Among them, 8,759, 8,789, and 8,772 were non-synonymous SNPs, respectively. After filtering out 12,843 synonymous variations and 12,105 known variations with indels found in the dbSNP135 or 1000 Genomes Project database, we selected 73 variations in the samples from the affected sisters that did not occur in the sample from the unaffected mother. Using the Sorting Intolerant From Tolerant (SIFT), PolyPhen-2, and MutationTaster algorithms to predict amino acid substitutions, the XCR1, DLL1, TH, ACCS, SPPL3, CCNF, and SRL genes were risky among all three algorithms, while definite candidate genes could not be conclusively determined. Conclusion: Using exome sequencing, we found 7 variants for a breast cancer family without BRCA mutations. Genetic evidence of disease association should be confirmed by future studies.

Semi-automatic 3D Building Reconstruction from Uncalibrated Images (비교정 영상에서의 반자동 3차원 건물 모델링)

  • Jang, Kyung-Ho;Jang, Jae-Seok;Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of Korea Multimedia Society
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    • v.12 no.9
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    • pp.1217-1232
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    • 2009
  • In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

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Performance Analysis of IT Enterprise for the New-growth System Construction (IT기업의 신성장 체계 구축을 위한 성과분석)

  • Kim Yoon-ho;Kang Hee-jo;Park Kyong-ryol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.8
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    • pp.1796-1801
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    • 2004
  • IT Technology Paradigm Sift from hardware, software, networking to digital contents. In year 2001, IT small and medium size manufacture occupied 3.8% of gross domestic product(GDP). In the mean time, owing to the acceleration of global competition in information and communication technology, life cycle is reduced and global M&A is increased. The aim of this research is to analyze the performance of potential small and medium sized IT enterprise which can be adapt the change of new paradigm. and Also to work out a program of government's supports plan. Finally, It is to study a better plan that promote a new shape enterprise, which aimed to reform the industrial system. Some kinds of investigation, namely, ground investigation as well as questionnaire are performed in order to analyze not only the results of potential small and medium sized IT enterprise but also it's promoting plans.

Bag of Visual Words Method based on PLSA and Chi-Square Model for Object Category

  • Zhao, Yongwei;Peng, Tianqiang;Li, Bicheng;Ke, Shengcai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2633-2648
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    • 2015
  • The problem of visual words' synonymy and ambiguity always exist in the conventional bag of visual words (BoVW) model based object category methods. Besides, the noisy visual words, so-called "visual stop-words" will degrade the semantic resolution of visual dictionary. In view of this, a novel bag of visual words method based on PLSA and chi-square model for object category is proposed. Firstly, Probabilistic Latent Semantic Analysis (PLSA) is used to analyze the semantic co-occurrence probability of visual words, infer the latent semantic topics in images, and get the latent topic distributions induced by the words. Secondly, the KL divergence is adopt to measure the semantic distance between visual words, which can get semantically related homoionym. Then, adaptive soft-assignment strategy is combined to realize the soft mapping between SIFT features and some homoionym. Finally, the chi-square model is introduced to eliminate the "visual stop-words" and reconstruct the visual vocabulary histograms. Moreover, SVM (Support Vector Machine) is applied to accomplish object classification. Experimental results indicated that the synonymy and ambiguity problems of visual words can be overcome effectively. The distinguish ability of visual semantic resolution as well as the object classification performance are substantially boosted compared with the traditional methods.

Image Classification Approach for Improving CBIR System Performance (콘텐트 기반의 이미지검색을 위한 분류기 접근방법)

  • Han, Woo-Jin;Sohn, Kyung-Ah
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.816-822
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    • 2016
  • Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.

Shape Based Framework for Recognition and Tracking of Texture-free Objects for Submerged Robots in Structured Underwater Environment (수중로봇을 위한 형태를 기반으로 하는 인공표식의 인식 및 추종 알고리즘)

  • Han, Kyung-Min;Choi, Hyun-Taek
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.6
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    • pp.91-98
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    • 2011
  • This paper proposes an efficient and accurate vision based recognition and tracking framework for texture free objects. We approached this problem with a two phased algorithm: detection phase and tracking phase. In the detection phase, the algorithm extracts shape context descriptors that used for classifying objects into predetermined interesting targets. Later on, the matching result is further refined by a minimization technique. In the tracking phase, we resorted to meanshift tracking algorithm based on Bhattacharyya coefficient measurement. In summary, the contributions of our methods for the underwater robot vision are four folds: 1) Our method can deal with camera motion and scale changes of objects in underwater environment; 2) It is inexpensive vision based recognition algorithm; 3) The advantage of shape based method compared to a distinct feature point based method (SIFT) in the underwater environment with possible turbidity variation; 4) We made a quantitative comparison of our method with a few other well-known methods. The result is quite promising for the map based underwater SLAM task which is the goal of our research.

Quality Assessment of Images Projected Using Multiple Projectors

  • Kakli, Muhammad Umer;Qureshi, Hassaan Saadat;Khan, Muhammad Murtaza;Hafiz, Rehan;Cho, Yongju;Park, Unsang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.6
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    • pp.2230-2250
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    • 2015
  • Multiple projectors with partially overlapping regions can be used to project a seamless image on a large projection surface. With the advent of high-resolution photography, such systems are gaining popularity. Experts set up such projection systems by subjectively identifying the types of errors induced by the system in the projected images and rectifying them by optimizing (correcting) the parameters associated with the system. This requires substantial time and effort, thus making it difficult to set up such systems. Moreover, comparing the performance of different multi-projector display (MPD) systems becomes difficult because of the subjective nature of evaluation. In this work, we present a framework to quantitatively determine the quality of an MPD system and any image projected using such a system. We have divided the quality assessment into geometric and photometric qualities. For geometric quality assessment, we use Feature Similarity Index (FSIM) and distance-based Scale Invariant Feature Transform (SIFT). For photometric quality assessment, we propose to use a measure incorporating Spectral Angle Mapper (SAM), Intensity Magnitude Ratio (IMR) and Perceptual Color Difference (ΔE). We have tested the proposed framework and demonstrated that it provides an acceptable method for both quantitative evaluation of MPD systems and estimation of the perceptual quality of any image projected by them.

A Hybrid Feature Selection Method using Univariate Analysis and LVF Algorithm (단변량 분석과 LVF 알고리즘을 결합한 하이브리드 속성선정 방법)

  • Lee, Jae-Sik;Jeong, Mi-Kyoung
    • Journal of Intelligence and Information Systems
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    • v.14 no.4
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    • pp.179-200
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    • 2008
  • We develop a feature selection method that can improve both the efficiency and the effectiveness of classification technique. In this research, we employ case-based reasoning as a classification technique. Basically, this research integrates the two existing feature selection methods, i.e., the univariate analysis and the LVF algorithm. First, we sift some predictive features from the whole set of features using the univariate analysis. Then, we generate all possible subsets of features from these predictive features and measure the inconsistency rate of each subset using the LVF algorithm. Finally, the subset having the lowest inconsistency rate is selected as the best subset of features. We measure the performances of our feature selection method using the data obtained from UCI Machine Learning Repository, and compare them with those of existing methods. The number of selected features and the accuracy of our feature selection method are so satisfactory that the improvements both in efficiency and effectiveness are achieved.

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