• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.1-4
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• 2007

In this paper, we propose an efficient scheme for automatically detecting highlight scenes in soccer videos. Highlights are defined as shooting scenes and goal scenes. Through the analysis of soccer videos, we notice that most of highlight scenes are shown around the goal post area. It is also noticed that the TV camera zooms in a setter player or spectators after the highlight stones. Detection of highlight scenes for soccer videos consists of three steps. The first step is the extraction of the playing field using a statistical threshold. The second step is the detection of goal posts. In the final step, we detect a zooming of a soccer player or spectators by using connected component labeling of non-playing field. In order to evaluate the performance of our method, the precision and the recall are computed. Experimental results have shown the effectiveness of the proposed method, with 95.2% precision and 85.4% recall.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.192-198
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• 2010

With the popularization of the mobile phone with a built-in camera, there are a lot of effort to provide useful information to users by detecting and recognizing the text in the video which is captured by the camera in mobile phone, and there is a need to detect the text regions in such mobile phone video. In this paper, we propose a method to detect the text regions in the mobile phone video. We employ morphological operation as a preprocessing and obtain binarized image using modified k-means clustering. After that, candidate text regions are obtained by applying connected component analysis and general text characteristic analysis. In addition, we increase the precision of the text detection by examining the frequency of the candidate regions. Experimental results show that the proposed method detects the text regions in the mobile phone video with high precision and recall.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.209-214
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• 2010

This paper proposes an algorithm of segmentation and title detection for document image. The automated title detection method that we have developed is composed of two phases, segmentation and title area detection. In the first phase, we extract and segment the document image. To perform this operation, the binary map is segmented by combination of morphological operation and CCA(connected component algorithm). The first phase provides segmented regions that would be detected as title area for the second stage. Candidate title areas are detected using geometric information, then we can extract the title region that is performed by removing non-title regions. After classification step that removes non-text regions, projection is performed to detect a title region. From the fact that usually the largest font is used for the title in the document, horizontal projection is performed within text areas. In this paper, we proposed a method of segmentation and title detection for various forms of document images using geometric features and projection profile analysis. The proposed system is expected to have various applications, such as document title recognition, multimedia data searching, real-time image processing and so on.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.777-785
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• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.922-928
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• 2004

We propose a new 3 dimensional labeling method based on slice information for the volume data. This method is named SIL (Slice Information based Labeling). Compare to the conventional algorithms, it has advantages that the use of memory is efficient and it Is possible to combine with a variety of 2 dimensional labeling algorithms for finding an appropriate labeling algorithm to its application. In this study, we applied SIL to confocal microscopy images of cervix cancer cell and compared the results of labeling. According to the measurement, we found that the speed of Sd combined with, CCCL (Contour based Connected Component Labeling) is almost 2 times higher than that of other methods. In conclusion, considering that the performance of labeling depends on a kind of image, we obtained that the proposed method provide better result for the confocal microscopy cell volume data.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.149-158
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• 2004

This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.10
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• pp.73-82
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• 2015

This paper proposes an ripple reduction algorithm and analyzes the effects of offset and scale errors generated by voltage sensor while measuring grid voltage in grid-tied single-phase inverters. Generally, the grid-connected inverter needs to detect the phase angle information by measuring grid voltage for synchronization, so that the single-phase inverter can be accurately driven based on estimated phase angle information. However, offset and scale errors are inevitably generated owing to the non-linear characteristics of voltage sensor and these errors affect that the phase angle includes 1st harmonic component under using SRF-PLL(Synchronous Reference Frame - Phase Locked Loop) system for detecting grid phase angle. Also, the performance of the overall system is degraded from the distorted phase angle including the specific harmonic component. As a result, in this paper, offset and scale error due to the voltage sensor in single-phase grid connected inverter under SRF-PLL is analyzed in detail and proportional resonant controller is used to reduce the ripples caused by the offset error. Especially, the integrator output of PI(Proportional Integral) controller in SRF-PLL is selected as an input signal of the proportional resonant controller. Simulation and experiment are performed to verify the effectiveness of the proposed algorithm.

• Journal of Digital Contents Society
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• v.3 no.2
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• pp.245-254
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• 2002

Currently, communication field for automation system can be divided by simple serial communication for communication between each internal devices and network base remote control system that is based on TCP/IP. In spite of great development of network, communication part for internal control is using simple RS232 base until present. Also, development techniques of system developed by object oriented program in modular programming techniques of each function unit. Currently, it developed by component base development technique that is parts unit of software. This is presented by the new alternative of software development techniques as techniques to composition independent operation unit including business logic and is connected to development of new system. Therefore, this research implemented internal communication Emulate in RS232C based on GUI that apply development techniques of component base. that is, I maked component to commnication control part between receiving and sending and, as composite it, Control part did to handling between send and receive data.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.149-157
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• 2008

In the field of computing service, there is a copernican revolution indebted to development of network & computer technology. Computer system, which is set to mainframe in the 1960's, is advancing torwards to the paradigm of server based computing, so-called thin-client. In thin-client computing, network is the platform which is responsible for transfer of application, so that client execute application installed on server. It is also possible that each system share the computing resource connected with network. In this parer, we suggest component & distributed computing technology as a measn for the implementation of thin-client architecture hence, make the best use of COM(Component Object Model and PYRO(PYthon Remote Objects). We talk about the concept and mechanism of thin-client at the beginning, and propose the design of network architecture for the implementation thin-client.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.27-35
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• 1999

Researches on the recognition of handwritten script have been conducted under the assumption that the isolated recognition units are provided as inputs. However, in practical recognition system designs, providing the isolated recognition unit is an challenge due to various writing syles. This paper proposes an approach for segmenting words from lines of unconstrained handwritten text, without help of recognition. In contrast to the conventional approaches which are based on physical gaps between connected components, clues that reflect the author's writing style, in terms of spacing, are extracted and utilized for the segmentation using a simple neural network. The clues are from character segments and include normalized heights and intervals of the segments. Effectiveness of the proposed approach compared with the conventional connected component based approaches in terms of word segmentation performance was evaluated by experiments.