• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.41-47
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• 2019

It is very important to search for and obtain an example of a similar judgment in case of court judgment. The existing judge's document search uses a method of searching through key-words entered by the user. However, if it is necessary to input an accurate keyword and the keyword is unknown, it is impossible to search for the necessary document. In addition, the detected document may have different contents. In this paper, we want to improve the effectiveness of the method of vectorizing a document into a three-dimensional space, calculating cosine similarity, and searching close documents in order to search an accurate judge's example. Therefore, after analyzing the similarity of words used in the judge's example, a method is provided for extracting the mode and inserting it into the text of the text, thereby providing a method for improving the cosine similarity of the document to be retrieved. It is hoped that users will be able to provide a fast, accurate search trying to find an example of a tax-related judge through the proposed model.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.94-102
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• 2012

Recently entered into an aging socity as the number of elderly drivers is increasing. Traffic accidents of elderly drivers are caused by driver inattentions such as poor vehicle control due to aging, visual information retrieval problems caused by presbyopia, and objects identifying problems caused by low contrast sensitivity. In this paper, detection method of ROIs on the road is proposed. The proposed method creates the saliency map to detect the candidate ROIs from the input image. And, the input image is segmented to obtain the ROIs boundary. Finally, selective visual attention regions are detected according to the presence or absence of a segmented region with saliency pixels. Experimental results from a variety of outdoor environmental conditions, the proposed method presented a fast object detection and a high detection rate.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.231-235
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• 2008

Recently we witnessed a few scandals on plagiarism among academic paper and novels. Plagiarism on documents is getting worse more frequently. Although plagiarism on English had been studied so long time, we hardly find the systematic and complete studies on plagiarisms in Korean documents. Since the linguistic features of Korean are quite different from those of English, we cannot apply the English-based method to Korean documents directly. In this paper, we propose a new plagiarism detecting method for Korean, and we throughly tested our algorithm with one benchmark Korean text corpus. The proposed method is based on "k-mer" and "local alignment" which locates the region of plagiarized document pairs fast and accurately. Using a Korean corpus which contains more than 10 million words, we establish a probability model (or local alignment score (random similarity by chance). The experiment has shown that our system was quite successful to detect the plagiarized documents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4084-4104
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• 2021

Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.547-552
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• 2014

As social multimedia sites are getting popular such as Flickr and Facebook, the amount of image information has been increasing very fast. So there have been many studies for accurate social image retrieval. Some of them were web image classification using semantic relations of image tags and BoVW(Bag of Visual Words). In this paper, we propose a method to detect salient region in images using GBVS(Graph Based Visual Saliency) model which can eliminate less important region like a background. First, We construct BoVW based on SIFT algorithm from the database of the preliminary retrieved images with semantically related tags. Second, detect salient region in test images using GBVS model. The result of image classification showed higher accuracy than the previous research. Therefore we expect that our method can classify a variety of images more accurately.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.24-27
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• 2008

As shown in Wikipedia, tagging or cross-linking through major key-words improves the readability of documents. Recently, the Semantic Web rises the importance of social tagging as a key feature of the Web 2.0 and Tag Cloud has emerged as its crucial phenotype. In this paper we provides an efficient method of automated keyword tagging based on controlled term collection, where the computational complexity of O(mN) - if pattern matching algorithm is used - can be reduced to O(mlogN) - if Information Retrieval is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that IR-based tagging speeds up 5.6 times compared with fast pattern matching algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.812-820
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• 2012

In this paper, multiple pedestrians tracking system using Histogram of Oriented Gradient and occlusion detection is proposed. The proposed system is applicable to Intelligent Surveillance System. First, we detect pedestrian in a image sequence using pedestrian's feature. To get pedestrian's feature, we make block-histogram using gradient's direction histogram based on HOG(Histogram of Oriented Gradient), after that a pedestrian region is classified by using Linear-SVM(Support Vector Machine) training. Next, moving objects are tracked by using position information of the classified pedestrians. And we create motion trajectory descriptor which is used for content based event retrieval. The experimental results show that the proposed method is more fast, accurate and effective than conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1035-1041
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• 2004

Currently users are tend to use multimedia data types in their applications. Main features of multimedia data types are large amount of data compared to conventional data types. In this reason, it's hard to load data into main memory and to search. That is the cause of occur disk input and output frequently, and decrease the system performance. In this paper, we describe to have fast and efficient access to multimedia data using index technique. Index method presented by paper consists of two parts : one is index file part for keywords and the other is posting file part for the list of file names. Of course, we use keyword. But user is not charge of memory for the keywords. Users just use natural language to insert, delete and search data what he or she wants. Internally, System makes keywords from natural language to get access to multimedia data. It provides convenience to users. Using this study to develop one's application for multimedia, one may have a chance for advanced performance of a system and getting a result speedily.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.33-40
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• 2005

In order to successfully exploit underwater resources, the first step would be a marine environmental research and exploration on the seafloor. Traditionally one sets up a long-term underwater experimental unit on the seafloor and retrieves the unit later after a certain period time. Essential to these applications is the reliable teleoperation and telemetering of the unit. This study presents ultrasonic-wave remote control system and an underwater sound recognition algorithm that can identify the sound signal without the influence of disturbances due to underwater environmental changes. The proposed method provides a means suitable for units which require low power dissipation and long-time underwater operation. We demonstrate its ability of securing stability and fast sound recognition through experimental methods.