• 제목/요약/키워드: Matching information

Search Result 4,144, Processing Time 0.139 seconds

Noninformative priors for the log-logistic distribution

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.25 no.1
    • /
    • pp.227-235
    • /
    • 2014
  • In this paper, we develop the noninformative priors for the scale parameter and the shape parameter in the log-logistic distribution. We developed the first and second order matching priors. It turns out that the second order matching prior matches the alternative coverage probabilities, and is a highest posterior density matching prior. Also we revealed that the derived reference prior is the second order matching prior for both parameters, but Jerffrey's prior is not a second order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

Noninformative priors for stress-strength reliability in the Pareto distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.22 no.1
    • /
    • pp.115-123
    • /
    • 2011
  • In this paper, we develop the noninformative priors for stress-strength reliability from the Pareto distributions. We develop the matching priors and the reference priors. It turns out that the second order matching prior does not match the alternative coverage probabilities, and is not a highest posterior density matching or a cumelative distribution function matching priors. Also we reveal that the one-at-a-time reference prior and Jeffreys' prior are the second order matching prior. We show that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example is given.

Environmental Survey Data Analysis by Data Fusion Techniques

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.17 no.4
    • /
    • pp.1201-1208
    • /
    • 2006
  • Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

  • PDF

Local-Based Iterative Histogram Matching for Relative Radiometric Normalization

  • Seo, Dae Kyo;Eo, Yang Dam
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.37 no.5
    • /
    • pp.323-330
    • /
    • 2019
  • Radiometric normalization with multi-temporal satellite images is essential for time series analysis and change detection. Generally, relative radiometric normalization, which is an image-based method, is performed, and histogram matching is a representative method for normalizing the non-linear properties. However, since it utilizes global statistical information only, local information is not considered at all. Thus, this paper proposes a histogram matching method considering local information. The proposed method divides histograms based on density, mean, and standard deviation of image intensities, and performs histogram matching locally on the sub-histogram. The matched histogram is then further partitioned and this process is performed again, iteratively, controlled with the wasserstein distance. Finally, the proposed method is compared to global histogram matching. The experimental results show that the proposed method is visually and quantitatively superior to the conventional method, which indicates the applicability of the proposed method to the radiometric normalization of multi-temporal images with non-linear properties.

Matching Method between Heterogeneous Data for Semantic Search (시맨틱 검색을 위한 이기종 데이터간의 매칭방법)

  • Lee, Ki-Jung;WhangBo, Taeg-Keun
    • The Journal of the Korea Contents Association
    • /
    • v.6 no.10
    • /
    • pp.25-33
    • /
    • 2006
  • For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

  • PDF

Synthesizing Intermediate Images Using Stereoscopic Images

  • Kwak, Ji-Hyun;Komar, V.S.V.;Kim, Kyung-Tae
    • Journal of the Optical Society of Korea
    • /
    • v.6 no.4
    • /
    • pp.143-149
    • /
    • 2002
  • In this paper, we present an algorithm for synthesizing intermediate views from a stereoscopic pair of images. Syntheses of intermediate images allows one to realize a more comfortable the 3D display system. The proposed method is based on block matching, which is not ordinarily used. The contour information is used for a block decision. In order to find an equivalent (or corresponding) block, there are two steps: "matching of contour-to-original image" and "matching of contour-to-contour image" methods. "Matching of contour-to-contour image" uses both left and right contour images. This block matching method allows us to find the corresponding block in spite of different block sizes. Experimental results illustrate the performance of the proposed technique and we obtained a high quality image of more than 31 dB PSNR.image of more than 31 dB PSNR.

A Study on the Extraction of the Minutiae and Singular Point for Fingerprint Matching

  • Na Ho-Jun;Kim Chang-Soo
    • Journal of Korea Multimedia Society
    • /
    • v.8 no.6
    • /
    • pp.761-767
    • /
    • 2005
  • The personal identification procedure through the fingerprints is divided as the classification process by the type of the fingerprints and the matching process to confirm oneself. Many existing researches for the classification and the matching of the fingerprint depend on the number of the minutiae of the fingerprints and the flow patterns by their direction information. In this paper, we focus on extracting the singular points by using the flow patterns of the direction information from identification. The extracted singular points are utilized as a standard point for the matching process by connecting with the extracted information from the singular point embodied. The orthogonal coordinates which is generated by the axises of the standard point can increase the accuracy of the fingerprints matching because of minimizing the effects on the location changes of the fingerprint images.

  • PDF

Multiple Vehicle Detection and Tracking in Highway Traffic Surveillance Video Based on SIFT Feature Matching

  • Mu, Kenan;Hui, Fei;Zhao, Xiangmo
    • Journal of Information Processing Systems
    • /
    • v.12 no.2
    • /
    • pp.183-195
    • /
    • 2016
  • This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.

Comparison Shopping System Based on RSS with Ontology Matching (온톨로지 매칭을 이용한 RSS 기반의 비교쇼핑 시스템)

  • Park, Sang-Un
    • The Journal of Information Systems
    • /
    • v.20 no.3
    • /
    • pp.41-61
    • /
    • 2011
  • In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.

A Study on Preprocessing Method for Effective Semantic-based Similarity Measures using Approximate Matching Algorithm (의미적 유사성의 효과적 탐지를 위한 데이터 전처리 연구)

  • Kang, Hari;Jeong, Doowon;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.25 no.3
    • /
    • pp.595-602
    • /
    • 2015
  • One of the challenges of the digital forensics is how to handle certain amounts of data efficiently. Although reliable and various approximate matching algorithms have been presented to quickly identify similarities between digital objects, its practical effectiveness to identify the semantic similarity is low because of frequent false positives. To solve this problem, we suggest adding a pre-processing of the approximate matching target dataset to increase matching accuracy while maintaining the reliability of the approximate matching algorithm. To verify the effectiveness, we experimented with two datasets of eml and hwp using sdhash in order to identify the semantic similarity.