• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.31-37
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• 2020

Identification of the mandibular canal path in Computed Tomography (CT) scans is important in dental implantology. Typically, prior to the implant planning, dentists find a sagittal plane where the mandibular canal path is maximally observed, to manually identify the mandibular canal. However, this is time-consuming and requires extensive experience. In this paper, we propose a deep-learning-based framework to detect the desired sagittal plane automatically. This is accomplished by utilizing two main techniques: 1) a modified version of the iterative transformation network (ITN) method for obtaining initial planes, and 2) a fine searching method based on a convolutional neural network (CNN) classifier for detecting the desirable sagittal plane. This combination of techniques facilitates accurate plane detection, which is a limitation of the stand-alone ITN method. We have tested on a number of CT datasets to demonstrate that the proposed method can achieve more satisfactory results compared to the ITN method. This allows dentists to identify the mandibular canal path efficiently, providing a foundation for future research into more efficient, automatic mandibular canal detection methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.2
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• pp.103-109
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.210-217
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• 2016

Damage caused by FOD which is a foreign substance at the movement area in airports around the world has reached 200 million every year. In 2000, the casualties occurred 133 people at charles de gaulle airport due to FOD. The occurrence of damage by FOD has continuously influenced in domestic also it makes equipment repair indirectly or directly. Accordingly, One of the solutions to the problem is the development of FOD automatic detection system. That is ongoing for plane movement area in airport. As the analyzed result, the military airport prefered mobile type and the civil airport prefered fixed type due to the characteristics of the operating type. In this paper, we analyzed the minimum performance specifications meeting the domestic requirements by investigating military and private FOD detection systems.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.185-190
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• 2016

This paper deals with analysis of the characteristics of mobile robot's motion by automatic detection of markers on a robot using a camera. Analysis of motion behaviors according to parameters is important in developing control algorithm for robot operation or autonomous navigation. For this purpose, we use four chessboard patterns on the robot. Their location on the robot is adjusted to be on single plane. Homography is used to compute the actual amount of movement of the robot. Presented method is tested using P3-AT robot and it gives reliable results.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.290-293
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• 2003

다중 물체 추적은 움직이는 물체를 추출하고 검출된 정보와 물체 정보를 이용하여 움직임 궤도률 추적하는 것이다. 따라서 정확한 움직임 추적이 수행되려면 효율적인 물체의 추출이 선행 되어 져야 한다. 일반적으로 영상 분할 알고리즘은 다양한 증류의 영상에 대한 물체의 수학적 모델이 찌대로 설정되어 있지 않기 때문에 물체를 정확하게 분리해 내기 어렵다. 그러나 물체의 추출에 주로 처리 속도가 빠른 배경영상을 이용한 차(difference) 영상 기법과 반 자동 영상분할인 Snake Model이 갖는 Active Contour 알고리즘과 같이 물체 추출 과정에서 물체의 정의니 semantic 정보를 부여 한다면 개선된 영상 분할의 결과를 얻을 수 있다. 따라서 차 영상 기법과 semantic 정보를 가진 영상분할 알고리즘은 동영상에서 움직임 물체의 VOP(Video Object Plane)를 생성하는 매우 현실적인 방법이다. 본 논문에서는 영상의 상위 레벨Semantic 정보를 이용하기 위해 변형 Snake Model를 이용한 영상분할 방법을 이용하여 영상을 추출한다. 추출된 물체는 윤곽선(곡선) 정보와 함께 에지 성분의 기울기에서 얻은 특징 점을 이용하여 물체를 추적해 나간다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1534-1538
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• 2005

In this paper, we propose a method to detect contours of a face, eyes, and a mouth of a person in the color image in order to make an avatar automatically. First, we use the HSI color model to exclude the effect of various light conditions, and find skin regions in the input image by using the skin color defined on HS-plane. And then, we use deformable templates and genetic algorithm (GA) to detect contours of a face, eyes, and a mouth. Deformable templates consist of B-spline curves and control point vectors. Those represent various shapes of a face, eyes and a mouth. GA is a very useful search algorithm based on the principals of natural selection and genetics. Second, the avatar is automatically created by using GA-detected contours and Fuzzy C-Means clustering (FCM). FCM is used to reduce the number of face colors. In result, we could create avatars which look like handmade caricatures representing user's identity. Our approach differs from those generated by existing methods.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.4
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• pp.26-33
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• 1993

The acoustic emission automatic detection system is developed to observe tree deterioration phenomena. Applying an alternating voltage of 15(kVnns) toXLPE tree specimens, many pulses of small amplitude are detected when the bush type tree developes branch type and a few pulses of high amplitude prcxluced as branch type propagated to bush type tree. Therefore, it is known that pulses having small amplitude operates as a destructive factor. It is observed that the skewness of the amplitude and the number of average pulses as distribution tendency of three dimension are characteristic quantity of AE pulses. As the trajectory of skewness is farther from the origin on the S-plane, it is more likely to breakdown.

• Plant Journal
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• v.17 no.3
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• pp.37-41
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• 2021

P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.