• Journal of Korean Port Research
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• v.14 no.2
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• pp.209-217
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• 2000

This study is to develop the technology and the ways of the practical use of the integrated digital map of and Electronical Navigational Chart(ENC) and Digital Terrain Map(DTM) for the effective and scientific based conservation, development and management. In this study, as preliminary studies to make eventual integrated maps, the concept of coastal areas are defined and the characteristics of digital maps developed by Korean Geography Institute and National Marine Investigation Institute are carefully analyzed. A test coastal map was developed based on the integrated digital map, a high resolution satellite image and Global Positioning System. Results from the edge matching analysis of coastal lines shows 8 meters difference in maximum. The problems, causes and solutions for the edge matched differences are described. Furthermore, the practical value of utilization, future use and various field of application are described based on the integrated digital map data base of coastal area.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.347-356
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• 1999

This study is to develop the technology and the ways of the practical use of the integrated digital map of and Electronical Navigational Chart(ENC) and Digital Terrain Map(DTM) for the effective and scientific based conservation, development and management. In this study, as preliminary studies to make eventual integrated maps, the concept of coastal areas are defined and the characteristics of digital maps developed by Korean Geography Institute and National Marine Investigation Institute are carefully analyzed. A test coastal map was developed based on the integrated digital map, a high resolution satellite image and Global Positioning System. Results from the edge matching analysis of coastal lines shows 8 meters difference in maximum. The problems, causes and solutions for the edge matched differences are described. Furthermore, the practical value of utilization, future use and various field of application are described based on the integrated digital map data base of coast area.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.269-274
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• 2008

In this paper, we propose a new stereo correspondence method for generating excellent external energy for snake-based object segmentation methods in stereo images. Our method first generates an edge-based disparity map by performing stereo correspondence between multi-level edge maps of the stereo image pair. Only edges of similar strength are considered for matching. To filter the disparity map for edges of the object of interest, the method estimates the object's disparity value by matching the pattern of edges of the region of interest in the left image against candidate patterns in the right image. The filtered edge map is then used to generate external energy for the snake. The proposed method has been tested on two snake models and results show a noticeable enhancement on performance of the snake when compared with other methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.249-255
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• 2013

In this paper, we propose an algorithm to detect scale invariant object from IR image obtained in the sea environment. We create horizontal edge (HL), vertical edge (LH), diagonal edge (HH) of images through 2-D discrete Haar wavelet transform (DHWT) technique after noise reduction using morphology operations. Considering the sea environment, Gaussian blurring to the horizontal and vertical edge images at each level of wavelet is performed and then saliency map is generated by multiplying the blurred horizontal and vertical edges and combining into one image. Then we extract object candidate region by performing a binarization to saliency map. A small area in the object candidate region are removed to produce final result. Experiment results show the feasibility of the proposed algorithm.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.363-368
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• 2016

Rectangular shape detection plays an important role in many image recognition systems. However, it requires continued research for its improved performance. In this study, we propose a strong rectangular shape detection algorithm, which combines the canny edge and line detection algorithms based on the perpendicularity and parallelism of a rectangle. First, we use the canny edge detection algorithm in order to obtain an image edge map. We then find the edge of the contour by using the connected component and find each edge contour from the edge map by using a DP (douglas-peucker) algorithm, and convert the contour into a polyline segment by using a DP algorithm. Each of the segments is compared with each other to calculate parallelism, whether or not the segment intersects the perpendicularity intersecting corner necessary to detect the rectangular shape. Using the perpendicularity and the parallelism, the four best line segments are selected and whether a determined the rectangular shape about the combination. According to the result of the experiment, the proposed rectangular shape detection algorithm strongly showed the size, location, direction, and color of the various objects. In addition, the proposed algorithm is applied to the license plate detecting and it wants to show the strength of the results.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.53-55
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• 1986

The edge detection system makes use or 3*3 compass gradient masks, which are well suited for digital implementation. Edge angles are quantized to eight equally spaced directions, suitable for chain coding of contours. Use of edge direction msp improves the simple thresholding of gradient modulus image. The concept of local connectivity of the edge direction map is useful improving the performance of this method as well as other edge operators such as Kirsch and Sobel.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.23-32
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• 2021

Semantic image segmentation technology in the field of computer vision is a technology that classifies an image by dividing it into pixels. This technique is also rapidly improving performance using a machine learning method, and a high possibility of utilizing information in units of pixels is drawing attention. However, this technology has been raised from the early days until recently for 'lack of detailed segmentation' problem. Since this problem was caused by increasing the size of the label map, it was expected that the label map could be improved by using the edge map of the original image with detailed edge information. Therefore, in this paper, we propose a post-processing algorithm that maintains semantic image segmentation based on learning, but modifies the resulting label map based on the edge map of the original image. After applying the algorithm to the existing method, when comparing similar applications before and after, approximately 1.74% pixels and 1.35% IoU (Intersection of Union) were applied, and when analyzing the results, the precise targeting fine segmentation function was improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.593-598
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• 2006

High-resolution satellite imagery has many benefits, compared to aerial photo in the wide area as well as multi-spectral character. So, it can be used well for constructing GIS data when making digital map. This study analysed the possibilities that road information derived automatically from IKONOS can be used for making ITS system or updating digital map of the urban areas where change frequently and producing satellite image map. In this study, Sobel was applied for road edge dectection after low pass filtering. As the results, it's possible for low pass filtering and high pass filtering to be used as the basic data for ITS construction when extracting edge roads and constructs according to the characteristic of high-resolution satellite imagery.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.73-79
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• 2000

The part-surface of mold or stamping-dies consists of a compound surface which consists of lots of composite surfaces, and may have various types of feature shapes including convex sharp edge (CSE). Those CSE features should be considered with care in machining the surface, which necessitates extraction of CSE curves on a compound surface. This work can be done rather easily for a solid model which has a complete topology information. In case of the compound surface without topology information, however, such CSE curves must be gathered through some geometrical calculations paying much computation time. In the paper, extracting CSE curves by the construction of a CSE region-map which can reduce time, and detecting various common edge types are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3217-3238
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• 2018

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).