• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.427-439
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• 2006

The SBF (Simple Boundary Follower) is a boundary-following algorithm, and is used mainly for image recognition and presentation. The SBF is very popular because of its simplicity and efficiency in tracing the boundary of an object from an acquired binary image; however, it does have two drawbacks. First, the SBF cannot consistently process inner or inner-outer corners according to the follower's position and direction. Second, the SBF requires movement operations for the non-boundary pixels that are connected to boundary pixels. The MSBF (Modified Simple Boundary Follower) has a diagonal detour step for preventing inner-outer corner inconsistency, but is still inconsistent with inner-corners and still requires extra movement operations on non-boundary pixels. In this paper, we propose the ISBF (Improved Simple Boundary Follower), which solves the inconsistencies and reduces the extra operations. In addition, we have classified the tour maps by paths from a current boundary pixel to the next boundary pixel and have analyzed SBF, MSBF, and ISBF. We have determined that the ISBF has no inconsistency issues and reduces the overall number of operations.

• Geophysics and Geophysical Exploration
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• v.1 no.1
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• pp.57-63
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• 1998

The electrical resistivity method, one of old and widely used geophysical prospecting methods, has extended its scope to civil & environmental engineering areas. The electrical resistivity imaging technique was performed at the waste disposal site located in Junju to verify the applicability to the environmental engineering area. The dipole-dipole array, with the dipole spacing of 10 m, was applied along eight survey lines. The field data were obtained under the control of automatic acquisition softwares and topographic effects were corrected during processing stage. The processed resistivity images show that very low resistivity develops inside the disposal site and the distribution of low resistivity is exactly in accord with the boundary of the site except the river side. The depth of low resistivity zones is deeper toward the river side, which is interpreted that there is a high possibility for contaminants to be scattered to the river. From resistivity images, it was feasible to deduce the depth of waste disposal as well as the horizontal/vertical distribution of the contaminated zone, which proved the applicability of the electrical resistivity imaging technique to the environmental engineering area.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.444-453
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• 2003

Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

• Journal of the HCI Society of Korea
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• v.2 no.1
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• pp.57-63
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• 2007

Our research was performed in order to implement a new pointing device for human-computer interactions in a collaborative environments based on Tiled Display system. We mainly focused on tracking the position of an infrared light source and applying our system to various areas. More than simple functionality of mouse clicking and pointing, we developed a device that could be used to help people communicate better with the computer. The strong point of our system is that it could be implemented in any place where a camera can be installed. Due to the fact that this system processes only infrared light, computational overhead for LED recognition was very low. Furthermore, by analyzing user's movement, various actions are expected to be performed with more convenience. This system was tested for presentation and game control.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.10-19
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• 2005

It may not be strange to anticipate that the forth-coming epoch of electronic government would bring us lots of convenience on account of ubiquitous environment with mobile devices. Such environment enables us to access the up-to-date information anytime and also a worker to carry out administration services to perform one's line of duty at anytime with electronic, handy devices such as PDA. What we now recognize from the field of electronic traffic administration services is that the office work flow as well as the public services has been remarkably improved by using of not only text but video and image information under the distributed, mobile environment. One of key requirements of this kinds of services is the feature of exchanging various information among multiple information publishers and subscribers. We call this feature Messaging Services generally The study in this paper focuses on the architecture design of the Messaging Engine software, complying with the pattern-oriented software architecture design methodology. And our contribution also goes to the discovery of three architecture patterns found in the design process and the efficient multi-threading architecture compared to one of the Messaging Engine solutions.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.93-102
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• 2003

A slant correction method for handwritten Korean strings based on analysis of stroke distribution, which effectively reflects structural properties of Korean characters, is presented in this paper. The method aims to deal with typical problems which have been frequently observed in slant correction of handwritten Korean strings with conventional approaches developed for English/European languages. Extracted strokes from a line of text image are classified into two clusters by applying the K-means clustering. Gaussian modeling is applied to each of the clusters and the slant angle is estimated from the model which represents the vertical strokes. Experimental results support the effectiveness of the proposed method. For the performance comparison 1,300 handwritten address string images were used, and the results show that the proposed method has more superior performance than other conventional approaches.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.75-81
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• 2014

Until recently, photogrammetric applications for processing the satellite images and remotely sensed data have been used in different structure of functions and interfaces for sensor modeling by each developer. Thus, a standardized utilization procedure was necessary to solve the problems, such as expandability, cost, inefficiency of sources which were resulted from different approaches. Therefore, National Geospatial Intelligence Agency (NGA) provided unified interfaces by developing Community Sensor Model (CSM) to sensor models in same way. In this study, we suggested the method of design and analyzed main functions needed modeling for the frame sensor using CSM Application Program Interface (API) provided by NGA. We also applied the designed structure to the modeling. The implemented CSM was verified by groundToImage and imageToGround. In the future, the active R&D is expected with using CSM due to the cost saving effect of software development and remarkable expandability of sensor.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.265-279
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• 2008

The idea of using hand gestures for human-computer interaction is not new and has been studied intensively during the last dorado with a significant amount of qualitative progress that, however, has been short of our expectations. This paper describes a dynamic Bayesian network or DBN based approach to both two-hand gestures and one-hand gestures. Unlike wired glove-based approaches, the success of camera-based methods depends greatly on the image processing and feature extraction results. So the proposed method of DBN-based inference is preceded by fail-safe steps of skin extraction and modeling, and motion tracking. Then a new gesture recognition model for a set of both one-hand and two-hand gestures is proposed based on the dynamic Bayesian network framework which makes it easy to represent the relationship among features and incorporate new information to a model. In an experiment with ten isolated gestures, we obtained the recognition rate upwards of 99.59% with cross validation. The proposed model and the related approach are believed to have a strong potential for successful applications to other related problems such as sign languages.