• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.273-285
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• 2000

While page segmentation is an important step in document recognition, there haven's been many researches on it. More improvement is still needed on the segmentation of document elements in complicated or color documents. In this paper, I present a new page segmentation method which can segment pages with multiple columns, dotted lines, graphics, and photographs. I extract all connected components using contour following and combine them depending on the size and positional information of them. Separate text location is done for non-text color regions to extract possible text lines. To see the performance of the proposed method, experiments are done for 180 documents. Four commercial OCR programs are also tested and the proposed method showed the best result.

• Geophysics and Geophysical Exploration
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• v.20 no.1
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• pp.33-42
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• 2017

Recently, the grounded electrical-source airborne transient electromagnetic (GREATEM) system with high power source was introduced to achieve deeper investigation depth and to overcome high noise level. Although the GREATEM is a transient electromagnetic system using a long grounded wire as the transmitter, GREATEM data have been interpreted with 1D earth models because 2D or 3D modeling and inversion of vast airborne data are complicated and expensive to calculate. Generally, 1D inversion is subsequently applied to every survey point and combining 1D images together forms the stitched conductivity-depth image. However, the stitched models often result in abrupt variations in neighboring models. To overcome this problem, laterally constrained inversion (LCI) has been developed in inversion of ATEM data, which can yield layered sections with lateral smooth transitions. In this study, we analysed the GREATEM data through 1D numerical modeling for a curved grounded wire source. Furthermore, we developed a laterally constrained inversion scheme for continuous GREATEM data based on a layered earth model. All 1D data sets and models are inverted as one system, producing layered sections with lateral smooth transitions. Applying the developed LCI technique to the GREATEM data, it was confirmed that the laterally constrained inversion can provide laterally smooth model sections that reflect the layering of the survey area effectively.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.266-275
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• 2006

Mostly mechanical products are connected by several components instead of single accessory in product process. Although majority of assembly process is automated, the fault analysis is not automated because it needs expert knowledge in various fields to support inclusive decision-marking. This paper proposes an assembly fault analysis support system that uses image regions which can be easily accessed and understood by experts of various fields. An assembly fault analysis support system helps effective fault analysis from assembly by integrating image regions, product design information, and fault detection information. The proposed method enables fault information access from multimedia information by segmenting product images. After product images are segmented by labeling, design information and fault information are integrated in extended Attributed Relational Graph.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.684-689
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• 2005

In this paper, we propose car license plate recognition using morphological information and an enhanced neural network. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. We used a contour tracking algorithm combined with the method of histogram and location information to extract individual characters in the extracted plate. The enhanced neural network is proposed for recognizing them, which has the method of combining the ART-1 and the supervised teaming method. The proposed method has applied to real world car images. The experimental results show that the proposed method has better the extraction rates than the methods with information of the thresholding, the RGB and the HSI, respectively. And the proposed neural network has better recognition performance than the conventional neural networks.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.803-810
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• 2005

Information retrieval is one of the most challenging areas in which the ontology technology is effectively used. Among them image retrieval using the image meta data and ontology is the one that can substitute the keyword-based image retrieval. In the paper, the retrieval of visual media such as the art image and photo picture is handled. It is assumed that there are more than one service providers of the visual media and also there is one central service broker that mediates the user's query. Given the user's query the first step that must be done in the service broker is to get the list of candidate service providers that fit the query. This is done by defining various ontologies such as the service ontology and matching the query against the ontology and providers. A novel matching method based on the ASN.1. The experiment shows that the method is more effective than existing tree-based and interval-based methods. Ontology merging issue is also handled that can happen when the service providers register their service into the service broker. An effective method is also proposed.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.607-611
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• 2008

This paper proposes new video signature using spatio-temporal information for copy detection. The proposed video copy detection method is based on concentric circle partitioning method for each key frame. Firstly, key frames are extracted from whole video using temporal bilinear interpolation periodically and each frame is partitioned as a shape of concentric circle. For the partitioned sub-regions, 4 feature distributions of average intensity, its difference, symmetric difference and circular difference distributions are obtained by using the relation between the sub-regions. Finally these feature distributions are converted into binary signature by using simple hash function and merged together. For the proposed video signature, the similarity distance is calculated by simple Hamming distance so that its matching speed is very fast. From experiment results, the proposed method shows high detection success ratio of average 97.4% for various modifications. Therefore it is expected that the proposed method can be utilized for video copy detection widely.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.104-115
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• 1999

This paper proposes an efficient method for 3D modeling of a human face from trinocular images by reconstructing face surface using range data. By using a trinocular camera system, we mitigated the tradeoff between the occlusion problem and the range resolution limitation which is the critical limitation in binocular camera system. We also propose an MPC_MBS (Matching Pixel Count Multiple Baseline Stereo) area-based matching method to reduce boundary overreach phenomenon and to improve both of accuracy and precision in matching. In this method, the computing time can be reduced significantly by removing the redundancies. In the model generation sub-pixel accurate surface data are achieved by 2D interpolation of disparity values, and are sampled to make regular triangular meshes. The data size of the triangular mesh model can be controlled by merging the vertices that lie on the same plane within user defined error threshold.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.132-151
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• 2022

Vehicle localization is one of the core technologies for autonomous driving. Image-based localization provides location information efficiently, and various related studies have been conducted. However, the image-based localization methods using feature points or lane information has a limitation that positioning accuracy may be greatly affected by road and driving environments. In this study, we propose a line segment matching framework for accurate vehicle localization. The proposed framework consists of four steps: line segment extraction, merging, overlap area detection, and MSLD-based segment matching. The proposed framework stably performed line segment matching at a sufficient level for vehicle positioning regardless of vehicle speed, driving method, and surrounding environment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.93-101
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• 2009

This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.