• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1074-1076
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• 2005

Magnetic Inductance Tomography System은 비투자율이 공기보다 큰 대상물체를 외부에서 자기장을 인가하여 자기장의 변화를 자기센서로 측정하여 대상물체의 형상, 위치, 비투자율을 측정하고 판단하는 시스템이다. Magnetic Inductance Tomog-raphy System은 비투자율이 공기보다 큰 대상물체를 외부에서 자기장을 인가하여 자기장의 변화를 자기센서로 측정하여 대상물체의 형상, 위치, 비투자율을 측정하고 판단하는 시스템이다. Magnetic Inductance To-mography System은 대상물체의 위치, 모양, 크기에 따라 자기장의 변화가 달라게 된다. 대상물체를 실시간으로 측정하기 위하여 Magnetic Inductance To-mography System을 자기장 발생부와 신호변환부, 모니터링 부로 구분하여 구축하였다. 또한 대상물체를 위치를 이동시키거나 크기를 변경하여 대상물체의 신호를 해석, 측정하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.252-256
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• 2018

호우 시 산지하천 유역에서 빈발하는 토석류에 따라 하천 흐름에 들어온 전석과 같이 상대적으로 큰 물체는 하류로 이송되거나 하상에 퇴적하여 기존 흐름과 하상을 변화시키는 교란요인이 된다. 따라서 산지하천 흐름에서 전석의 영향을 예측하는 것이 필요하나 이는 유속, 전석의 크기와 형상, 유입조건, 부유사 농도 등 수 많은 변수들에 영향을 받기 때문에 그 경로를 정확히 예측하기 어렵다. 이 연구는 유리와 철로 된 구형물체가 개수로 흐름에서 이동하는 경로를 조사한 것이며 흐름의 수심, 물체의 크기와 초기침강조건을 고려하여 수리실험을 실시하고 물체의 이동경로와 유하거리를 분석하였다. 개수로 흐름에 유입한 구형 물체는 침강에 의한 항력과 유수에 의한 항력을 동시에 받는다. 이 힘은 물체의 형상, 유수의 점성, 난류, 물체와 물의 밀도차가 복합적으로 작용한 결과이며 구체의 이동경로와 시간을 좌우한다. 실험결과 개수로 흐름에서 낙하중인 구형물체는 하상에 가까워질수록 흐름방향 이동거리가 증가하였다. 물체의 수중무게가 작을수록 유수 중에서 체류하는 시간이 길고 이동거리가 더 크며, 구체에 작용하는 초기항력에 따라 초기 낙하각도와 이동거리가가 증가하는 것을 확인하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.91-98
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• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.

• Convergence Security Journal
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• v.24 no.1
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• pp.77-82
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• 2024

Recent research has seen significant improvements in various object detection and classification models overall. However, the study of object detection and classification in situations where objects are partially obscured remains an intriguing research topic. Particularly in the military domain, unmanned combat systems are often used to detect and classify objects, which are typically partially concealed or camouflaged in military scenarios. In this study, a method is proposed to enhance the classification performance of partially obscured objects. This method involves adding occlusions to specific parts of object images, considering the surrounding environment, and has been shown to improve the classification performance for concealed and obscured objects. Experimental results demonstrate that the proposed method leads to enhanced object classification compared to conventional methods for concealed and obscured objects.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.603-625
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• 2010

Neural representation of a visual object is distributed across visual cortex and overlapped with those of many other objects. Thus repeating an object facilitates the recognition of the object while it impairs the recognition of other objects. These effects are called repetition priming and antipriming, respectively. Two experiments investigated a new phenomenon of repetition antipriming, in which a repeated object itself is antiprimed. The learning stage presented object pictures which were degraded at various levels. Participants determined how recognizable each object was. Then, the test stage presented the intact version of the object pictures and made participants to perform a categorization task. Both Experiment 1 and 2 found that the processing of the objects that had been recognized were facilitated (repetition priming) while the processing of the objects that had been perceptually ambiguous were impaired (repetition antipriming). These findings suggest that experiencing a perceptually ambiguous object might enhance the connection between feature-level representations and multiple object-level representations, which impairs the subsequent recognition of the repeated object.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.1-8
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• 2012

The application of object recognition technology has been increased with a growing need to introduce automated system in industry. However, object transformed by noises and shadows appeared from illumination causes challenge problem in object detection and recognition. In this paper, an illumination invariant object detection using a DoG filter and adaptive threshold is proposed that reduces noises and shadows effects and reserves geometry features of object. And also, rotation invariant object recognition is proposed that has trained with neural network using classes categorized by object type and rotation angle. The simulation has been processed to evaluate feasibility of the proposed method that shows the accuracy of 99.86% and the matching speed of 0.03 seconds on ETRI database, which has 16,848 object images that has obtained in various lighting environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.11-22
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• 2004

Conventional algorithms of separating overlapped objects are mostly based on template matching methods and thus their application domain is restricted to 2D objects and the processing time increases when the number of templates (object models) does. To solve these problems, this paper proposes a new approach of separating the occluding object from the stack of 3D objects using the relationship between surfaces without any information on the objects. The proposed algorithm considers an object as a combination of surfaces which are consisted with a set of boundary edges. Overlap of 3D objects appears as overlap of surfaces and thus as crossings of edges in 2D image. Based on this observation, the types of edge crossings are classified from which the types of overlap of 3D objects can be identified. The relationships between surfaces are represented by an attributed graph where the types of overlaps are represented by relation values. Using the relation values, the surfaces pertained to the same object are discerned and the overlapping object on the top of the stack can be separated. The performance of the proposed algorithm has been proved by the experiments using the overlapped images of 3D objects selected among the standard industrial parts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1015-1017
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• 2013

Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, non-rigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location or the shape of the object in every frame. This paper describes an object tracking system based on active vision with two cameras, into algorithm of single camera tracking system an object active visual tracking and object locked system based on Extend Kalman Filter (EKF) is introduced, by analyzing data from which the next running state of the object can be figured out and after the tracking is performed at each of the cameras, the individual tracks are to be fused (combined) to obtain the final system object track.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.1-13
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• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• Korean Journal of Cognitive Science
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• v.27 no.3
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• pp.355-376
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• 2016

We used holes defined by color similarity (Experiment 1) and binocular disparity (Experiment 2) to study how the inner contour of an object (i.e., boundary of a hole in it) is encoded in visual working memory. Many studies in VWM have shown that an object's boundary properties can be integrated with its surface properties via their shared spatial location, yielding an object-based encoding benefit. However, encoding of the hole contours has rarely been tested. We presented objects (squares or circles) containing a bar under a change detection paradigm, and relevant features to be remembered were the color of objects and the orientation of bars (or holes). If the contour of a hole belongs to the surrounding object rather than to the hole itself, the object-based feature binding hypothesis predicts that the shape of it can be integrated with color of an outer object, via their shared spatial location. Thus, in the hole display, change detection performance was expected to better than in the conjunction display where orientation and color features to be remembered were assigned to different parts of a conjunction object, and comparable to that in a single bar display where both orientation and color were assigned into a single bar. However, the results revealed that performance in the hole display did not differ from that in the conjunction display. This suggests that the shape of holes is not automatically encoded together with the surface properties of the outer object via object-based feature binding, but encoded independently from the surrounding object.