• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.169-171
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• 2001

Unlike rigid objects, the edge intensity of a gaseous object is various along the object boundary (edge intensities of some pixels on a gaseous object boundary are weaker than those of small rigid objects or noise itself). Therefore, the conventional edge detectors may not adequately detect boundary-like edge pixels for gaseous objects. In this paper A new methodology for segmenting gaseous object images is introduced. Proposed method consists of fuzzy-based boundary detector applicable to gaseous as well as rigid objects and concave region filling to recover object regions.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.375-380
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• 2010

Most of previous algorithms of object boundary extraction have been studied for extracting the boundary of single object. However, multiple objects are much common in the real image. The proposed algorithm of extracting the boundary of each of multiple objects has two steps. In the first step, we propose the fast method using the outer and inner products; the initial contour including multiple objects is split and connected and each of new contours includes only one object. In the second step, an improved active contour model is studied to extract the boundary of each object included each of contours. Experimental results with various test images have shown that our algorithm produces much better results than the previous algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1350-1353
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• 2015

In this paper, we have researched about how to detect the fish robot objects in aquarium. We had used designed fish robots DOMI ver1.0, which had researched and developed for aquarium underwater robot. The model of the robot fish is analysis to maximize the momentum of the robot fish and the body of the robot is designed through the analysis of the biological fish swimming. We are planned to non-external equipment to find the position and manipulated the position using creating boundary to fish robot to detect the fish robot objects. Also, we focused the detecting fish robot in aquarium by using boundary algorithm. In order to the find the object boundary, it is filtering the video frame to picture frames and changing the RGB to gray. Then, applied the boundary algorithm stand of equations which operates the boundary for objects. We called these procedures is kind of image processing that can distinguish the objects and background in the captured video frames. It was confirmed that excellent performance in the field test such as filtering image, object detecting and boundary algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.571-580
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• 1995

Medial axis transformation is an important concept used in many engineering applications. We propose a new approach to medial axis transformation of 2D objects with smooth boundary. Our approach differs from the traditional ones: we construct the medial axis starting from the inside points, while the previous algorithms started from the boundary points. As a result, previous algorithms are highly sensitive to the small irregularities of the object's boundary curve, while our approach is robust.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.30-37
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• 1997

We present an efficient technique, bidirectioanl inertial maximum cost search technique, for th edetection and segmentation of circular shaped objects using the spatial information around the neighborhood of the boundary candidates. This technique searches boundary candidates using local pixdl information such as pixel value and its direction. And then to exclude pseudo-boundary caused by shadows or noises, the local contrast is defined between the clique of the boundary candidates and the cliques of the background. In order to effectively segment circular shaped boundary, the technique also uses the curvature based on trigonometirc function which determines circular shaped boundary segments. Since the proposed technique is applied to the pixel cliques instead of a pixel itself, it is proposed method can easily find out circular boundaries form iamges of the PCB containing circular shaped parts and the trees with round fruits compared to boundary detection by using the pixel information and the laplacian curvature.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.2
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• pp.41-47
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• 2007

A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2901-2919
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• 2012

Recent research in MEMS (Micro-Electro-Mechanical Systems) and wireless communication has enabled tracking of continuous objects, including fires, nuclear explosions and bio-chemical material diffusions. This paper proposes an energy-efficient scheme that detects and tracks different dynamic shapes of a continuous object (i.e., the inner and outer boundaries of a continuous object). EBCO (Efficient Boundary detection and tracking of Continuous Objects in WSNs) exploits the sensing capabilities of sensor nodes by automatically adjusting the sensing range to be either a boundary sensor node or not, instead of communicating to its neighboring sensor nodes because radio communication consumes more energy than adjusting the sensing range. The proposed scheme not only increases the tracking accuracy by choosing the bordering boundary sensor nodes on the phenomenon edge, but it also minimizes the power consumption by having little communication among sensor nodes. The simulation result shows that our proposed scheme minimizes the energy consumption and achieves more precise tracking results than existing approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.5
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• pp.415-427
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• 1987

This paper presents an experimental model-based vision system which can identify and locate objects in scenes containing multiple occluded parts. The objects are assumed to be rigid and planar parts. In any recognition system the-type of objects that might appear in the image dictates the type of knowledge that is needed to recognize the object. The data is reduced to a sequential list of points or pixels that appear on the boundary of the objects. Next the boundary of the objects is smoothed using a polygonal approximation algorithm. Recognition cosists in finding the prototype that matches model to image. Now the hidden edge is reconstructed by transition model objects into occluded objects. The best match is obtained by optimising some similarity measure.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.9
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• pp.77-83
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• 1997

Based on the curve segment grouping, an efficient recognition of round objects form partially occuluded round boundaries is proposed. Curve segments are extracted from an image using a criterion based on the intra-segment curvature and local contrast. During the curve segment extraction the boundaries of pratially occluding and occuluded objects are segmented to different curve segments. The extracted segments of constant intra-segment curvature are grouped to different curve segments. The extracted segments of constant intra-segment curvature are grouped nto a round boundary by the proposed grouping algorithm using inter-segment curvature which gives the relatinships among the curve segments of the same round boundary. The 1st and the 2nd order moments are used for the parameter estimation of the best fitted ellipse with round boundary, and then recognition is perfomed based on the estimated parameters. The proposed scheme processes in segment unit and is more efficient in computational complexity and memory requirements those that of the conventional scheme which processed in pixel units. Experimental results show that the proposed technique is very efficient in recognizing the round object sfrom the real images with apples and pumpkins.