• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.1-13
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• 2000

While various types of information can be mixed in a continuous video stream without any cleat boundary, the meaning of a video scene can be interpreted by multiple levels of abstraction, and its description can be varied among different users. Therefore, for the content-based retrieval in video data it is important for a user to be able to describe a scene flexibly while the description given by different users should be maintained consistently This paper proposes an effective way to represent the different types of video information in conventional database models such as the relational and object-oriented models. Flexibly defined attributes and their values are organized as tree-structured dictionaries while the description of video data is stored in a fixed database schema. We also introduce several browsing methods to assist a user. The dictionary browser simplifies the annotation process as well as the querying process of a user while the result browser can help a user analyze the results of a query in terms of various combinations of Query conditions.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.177-186
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• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.589-600
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• 2002

Deformable models offer an attractive approach for extracting three-dimensional boundary structures from volumetric images. However, conventional deformable models have three major limitations - sensitive to initial condition, difficult to represent complex boundaries with severe object concavities and protrusions, and self-intersective between model elements. This paper proposes a deformable model that is effective to extract geometrically complex boundary surfaces by improving away the limitations of conventional deformable models. First, the proposed deformable model resamples its elements hierarchically based on volume image pyramid. The hierarchical resampling overcomes sensitivity to initialization by extracting the boundaries of objects in a multiscale scheme and enhances geometric flexibility to be well adapted to complex image features by refining and regularizing the size of model elements based on voxel size. Second, the physics-based formulation of our model integrates conventional internal and external forces, as well as a non-self-intersecting force. The non-self-intersecting force effectively prevents collision or crossing over between non-neighboring model elements by pushing each other apart if they are closer than a limited distance. We show that the proposed model successively extracts the complex boundaries including severe concavities and protrusions, neither depending on initial position nor causing self-intersection, through the experiments on several computer-generated volume images and brain MR volume images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.141-143
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• 2022

This paper presented a new technology to identify traffic violations of motorbike riders by detecting the traffic signal using You Only Look Once (YOLO) object detection. The hardware module that is mounted on the front of the motorbike consists of Raspberry Pi with a camera to run the YOLO object detection, a GPS module to acquire the motorcycle's coordinate, and a LoRa communication module to send the data to a cloud DB. The main goal of the software is to determine whether a motorbike has violated a traffic signal. This paper proposes a function to recognize the red traffic signal colour with its movement inside the camera angle and determine that the traffic signal violation happens if the traffic signal is moving to the right direction (the rider turns left) or moving to the top direction (the riders goes straight). Furthermore, if a motorbike rider is violated the signal, the rider's personal information (name, mobile phone number, etc), the snapshot of the violation situation, rider's location, and date/time will be sent to a cloud DB. The violation information will be delivered to the driver's smartphone as a push notification and the local police station to be used for issuing violation tickets, which is expected to prevent motorbike riders from violating traffic signals.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.189-200
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• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.197-200
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• 2007

항공사진 원데이터의 변형을 방지하고 효율적인 관리를 위해서는 자동독취를 통한 수치화 방안이 마련되어야 한다. 항공사진 판독업무에 있어서 기존 판독자만 밀착항공사진과 입체경을 통하여 건축물의 형태와 변화 여부를 판단하던 것을 모니터 상에서 누구나 건물의 변동사항을 볼 수 있도록 효율적인 판독시스템을 구축하여 판독의 신뢰도를 높여야 한다. 판독시스템 구축은 디지털 영상의 다양한 활용과 업무의 효율성 확보 및 대민서비스 향상 차원에서 이루어져야 할 것이다. 또한 현재 외국의 항측사들이 실제로 활용하고 있으며 조만간 국내에서도 도입 예정인 디지털항공카메라는 항공사진의 수치화 단계를 거치치 않고 직접 수치항공영상을 취득 할 수 있으므로 수치화 과정에서 발생하는 많은 오류들을 제거할 수 있음은 물론 판독시스템을 활용한 데이터의 직접처리가 가능해 시간적, 경제적으로 많은 장점들을 가지고 있다. 그러므로 디지털항공카메라의 도입에 대비한 개발현황과 활용도 등에 관한 사전 연구가 수행되어야 한다. 본 연구에서는 사용자가 직접 입체 판독 및 분석을 수행할 수 있는 플랫폼을 구비함으로서 오류를 최소화 할 수 있도록 편광 모니터(Z-Screen)를 사용하여 수행하였다. 또한 환경은 Microsoft Window OS 환경 상에서 구동될 수 있도록 개발함으로서 시스템의 범용적 사용을 위한 기초 환경을 제공하도록 제안하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.11-20
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• 2000

Topological relationships play an important role in query optimization in spatial databases. If topological relationships are known a priori, then expensive query processing can be avoided. In this paper we address the problems of： ⅰ) identifying topological relationships among spatial objects, ⅱ) checking consistency of specified topological relationships, and ⅲ) exhaustively deriving new topological relationships from the ones specified. These activities lead to an efficient query processing when queries associated with topological relationships are invoked. Specifically, eight types of topological relationships (｛equal, disjoint, overlap, meets, contains, contained-in, properly-contains, and properly-contained-in｝) are considered. We present an algorithm to check the consistency of specified topological relationships and to derive all possible relationships from the given set of known relationships.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.171-176
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• 2009

본 논문은 사용할 수 있는 헤어스타일의 수가 제한되는 문제를 해결하기 위한 것으로, 상호대화식 매팅을 이용한 2D 가상 컬러 헤어스타일러에 관한 것이다. 사전에 준비된 그래픽 헤어스타일 외에도 원하는 헤어스타일을 보유한 2D 실사 영상으로부터 상호대화식 매팅 기술을 사용하여 헤어스타일을 분리 추출한 후, 영상 간 픽 앤 드롭(pick-and-drop) 방식으로 옮겨와 두상에 부착한 다음, 필요시 헤어스타일의 컬러도 자유롭게 변경할 수 있는 기능을 제공함으로써 저비용으로 활용 가능한 헤어스타일의 수를 증대시킬 수 있다. 이때 헤어스타일의 분리 추출은 사용자가 전경 객체의 개략적 윤곽을 그려줌에 따라 점증적으로 알파 매트를 계산하는 상호대화식 매팅 기술을 사용한다. 그리고 헤어스타일의 컬러 변경은 명도 차분 맵(intensity difference map)에 기반한 모발 컬러 매핑 기술을 사용한다. 제안된 방법은 직관적이고 편리한 상호대화식 사용자 인터페이스를 제공하기 때문에 작업자의 피로도를 경감시킴과 동시에 작업 시간을 단축할 수 있고 비숙련자도 간단한 사용자 입력을 통해 자연스러운 가상 헤어스타일을 생성할 수 있는 장점이다.