• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.49-60
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• 2002

We propose an algorithm for extracting the boundary of a desired object with shape information obtained from sample images. Considering global shape obtained from sample images and edge orientation as well as edge magnitude, the Proposed method composed of two steps finds the boundary of an object. The first step is the approximate segmentation that extracts a rough boundary with a probability map and an edge map. And the second step is the detailed segmentation for finding more accurate boundary based on the SEEL (seed-point extraction and edge linking) algorithm. The experiment results using IR images show robustness to low-quality image and better performance than conventional segmentation methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.663-670
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• 2019

The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.99-111
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• 2009

The result of Image segmentation, an indispensable process in image processing, significantly affects the analysis of an image. Despite the significance of image segmentation, it produces some problems when the variation of pixel values is large, or the boundary between background and an object is not clear. Also, these problems occur frequently when many objects in an image are placed very close by. In this paper, when the shape of objects in an image is circular, we proposed an algorithm which segment an each object in an image using the geometric characteristic of circular shape. The proposed algorithm is composed of 4 steps. First is the boundary edge extraction of whole object. Second step is to find the candidate points for further segmentation using the boundary edge in the first step. Calculating the representative circles using the candidate points is the third step. Final step is to draw the line connecting the overlapped points produced by the several erosions and dilations of the representative circles. To verify the efficiency of the proposed algorithm, the algorithm is compared with the three well-known cell segmentation algorithms. Comparison is conducted by the number of segmented region and the correctness of the inner segment line. As the result, the proposed algorithm is better than the well-known algorithms in both the number of segmented region and the correctness of the inner segment line by 16.7% and 21.8%, respectively.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.69-73
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• 1999

In this paper, an algorithm based on Snakes is proposed to detect the boundary of 3D images. From the first-slice MR image, the boundary of an object is detected manually. The detected boundary points are used as initial control points for detecting the boundary of the next MR image. To detect the boundary from the rest of MR images automatically, an energy term using spatial correlation between adjacent images is added to the Greedy Snakes energy formulation. A measure of shape similarity called BMD was used to evaluate the accuracy of the proposed algorithm. The average BMD value for the proposed algorithm's result is higher than Greedy algorithm's showing the utility of the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.211-217
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• 2005

The general rule of boundary delimitation is the principle of equidistance. The principle of equidistance is a method that determine boundary delimitation from the fixed distant of baseline or basepoint. But there is no artificial and natural object in the sea to determine boundary. And the principle of equidistant can't be applied in every cases, because of the local characteristic of ground. In this paper, we suggest Three-Point Algorithm which is effective algorithm for maritime boundary delimitation. And the main objective of this study is to get capability of maritime boundary delimitation technique.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.84-90
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• 2010

In this paper, we propose a quadratic discriminant analysis based approach for improving the discriminating strength of weak classifiers based on simple Haar-like features that were used in the Viola-Jones object detection framework. Viola and Jones built a strong classifier using a boosted ensemble of weak classifiers. However, their single threshold (or decision boundary) based weak classifier is sub-optimal and too weak for efficient discrimination between object class and background. A quadratic discriminant analysis based approach is presented which leads to hyper-quadric boundary between the object class and background class, thus realizing multiple thresholds based weak classifiers. Experiments carried out for car detection using 1000 positive and 3000 negative images for training, and 500 positive and 500 negative images for testing show that our method yields higher classification performance with fewer classifiers than single threshold based weak classifiers.

• Korean Institute of Interior Design Journal
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• v.17 no.3
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• pp.86-93
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• 2008

The purpose of this study is to find out how the otherness philosophy reveals itself in the principle of F.O.A construction space creation. The traditional philosophy of totality is self-centered and thoughts are based on the subject. It couldn't escape from the world associated with the self, and has subordinated the other to the main body. But the philosophy of otherness transcends the subject, to the open, creative way of thinking which acknowledges deconstruction, decentralization, and non-hierarchy. This is very similar to contemporary architecture, which pursuits change, and also to the current state of society. In construction by the construction group F.O.A, which is doing notable activity this generation, there is an attempt to transcend the fixed subject which is seen in the otherness discussion, and realize recategorization by overcoming the boundaries of subject and object. First, by the realization of landscape architecture using a topographical folding technique, boundaries of the subject and object are demolished in the relationship of the landscape construction, and recategorization. Second, by breaking up the meaning of the surface which is a visual and physical boundary for both the internal and external, recategorization is being done. Third, by making the boundary between the interior and exterior indistinct, cognitive threshold is dissolved, and the relationship between the subject and object is being recategorization. In conclusion, we can see that the many recategorization phenomenons that are happening in the F.O.A construction show the otherness that escapes from the conventional and stationary relationship, and recognizes each other at the same time, forming new relationships.