• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.175-183
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• 2004

In this paper, we propose a new accurate and robust image mosaic technique of the mural underdrawing taken from the infra-red camera, which is based on multiple image registration and adaptive blending technique. The image mosaicing methods which have been developed so far have the following deficits. It is hard to generate a high resolution image when there are regions that do not have features or intensity gradients, and there is a trade-off in overlapping region size in view of registration and blending. We consider these issues as follows. First, in order to mosaic images with neither noticeable features nor intensity gradients, we use a projected supplementary pattern and pseudo color image for features in the image pieces which are registered. Second, we search the overlapping region size with minimum blending error between two adjacent images and then apply blending technique to minimum error overlapping region. Finally, we could find our proposed method is more effective and efficient for image mosaicing than conventional mosaic techniques and also is more adequate for the application of infra-red mural underdrawing mosaicing. Experimental results show the accuracy and robustness of the algorithm

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.868-869
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• 2005

• 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.

• Convergence Security Journal
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• v.8 no.4
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• pp.161-166
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• 2008

This paper proposes a new approach to align 3D data sets by using curvatures of feature surface. We use the Gaussian curvatures and the covariance matrix which imply the physical characteristics of the model to achieve registration of unaligned 3D data sets. First, the physical characteristics of local area are obtained by the Gaussian curvature. And the camera position of 3D range finder system is calculated from by using the projection matrix between 3D data set and 2D image. Then, the physical characteristics of whole area are obtained by the covariance matrix of the model. The corresponding points can be found in the overlapping region with the cross-projection method and it concentrates by removed points of self-occlusion. By the repeatedly the process discussed above, we finally find corrected points of overlapping region and get the optimized registration result.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2037-2040
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• 2004

In this paper we introduce a new prototype based classifiers for overlapping data, where training pattern can be overlap on the feature space. The proposed classifier is based on the prototype from neural network classifier (NNC)[1] for overlap data. The method automatically chooses the initial center and two radiuses for each class. The center is used as a mean representative of training data for each class. The unclassified pattern is classified by measure distance from the class center. If the distance is in the lower (shorter radius) the unknown pattern has the high percentage of being in this class. If the distance is between the lower and upper (further radius), the pattern has the probability of being in this class or others. But if the distance is outside the upper, the pattern is not in this class. We borrow the words upper and lower from the rough set to represent the region of certainty [3]. The training algorithm to find number of cluster and their parameters (center, lower, upper) is presented. The clustering result is tested using patterns from Thai handwritten letter and the clustering result is very similar to human eyes clustering.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.127-135
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• 2015

In recent years, meteorological disasters have frequently occurred in rural areas. As a result, there have been growing concerns over the protective measures needed. In order to avoid natural risks and damage, and to strengthen countermeasure to meteorological disasters, local governments needs to be prepared. Therefore, this paper seeks to prevent meteorological disasters through mapping of inundation vulnerability in agricultural land, Chungcheongnam-do. In doing so, this study were considered 5 variables (i.e. precipitation, region of altitude below 50m, region of slope gradient is below 10 degree, distance from river within less 50m) for creating vulnerability map. The precipitation was excluded in five variables. Since, the precipitation which include Daily maximum precipitation, 2-Daily maximum precipitation, summer precipitation was not any correlation among them. The results of analysing four variables, exclusive of precipitation, were showed that the agricultural lands where located in Dangjin, Buyeo, Hongseong and Asan were low correlation of inundation vulnerability by overlapping analysis. Moreover, The correlation analysis was showed low correlation between each factors and the annual average area of agricultural lands' inundation, whereas, the correlation analysis which was overlapping each factor showed high correlation. In conclusion, in order to create reliable vulnerability map in agricultural lands, Chungcheongnam-do, it must be considered to overlap analysis of the four main factors such region of altitude below 50m, region of slope gradient is below 10 degree, distance from river within less 50m. We suppose that this study's analysis can help to set the preparedness site of agricultural lands inundation.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.220-223
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• 2001

This study was carried out to developed that appraisement model of Potential Productivity Index (PPI). PPI model was used Farmland Productivity Index(FPI) and Labor Productivity Index(LPI) by GIS, and PPI model applied to farm land consolidation region which has been completed recently. FPI was determined by overlapping Poly Grid of the soil properties at the analyzed project region. LPI was estimated by addition productive wages ratio of total direct productive cost. Addition productive wages was determined by GIS Network analysis of working distance between farm house to paddy and each paddy. PPI variation of each the analyzed paddy of Masu and Weoncheon region was $0.967{\sim}0.712,\;0.986{\sim}0.780$ respectively, and could be showed relative largely PPI value. PPI will provide basic element for large scaling and gathering of farm land and a substitute lot of farm land consolidation, and will be maximize productivity of paddy.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.66.2-66.2
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• 2021

We list up the Paα-emitting sources observed in the Carina Region (l = 276°-296°) using the MIRIS Paα Galactic Plane Survey data. A total of 201 sources are cataloged. Out of them, 118 sources are coincident with those in the WISE H II region catalog. 52 H II region candidates are newly confirmed as definite H II regions by detecting the Paα recombination lines. For the remaining 83 sources, we search the corresponding objects in the SIMBAD database. 26 point-like sources are associated with planetary nebulae or emission-line stars (such as Wolf-Rayet and Blue supergiant stars). Also, we carry out aperture photometry to measure Paα fluxes for the sources that show circular features without overlapping with other bright sources. For the whole Galactic Plane, the complete Paα-emitting source catalog is in progress.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.3 no.1
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• pp.19-28
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• 1973

The author has studied maxillo-facial anatomical landmarks using Status X with two methods. The one has performed by application of contrast media on the human dry skull, the other has performed on living human skull as control group. Comparing the panagraphs taken by two methods, the author has drawn following results: 1. The panagraphs revealed the undistorted, highly sharp panoramic shadows of each jaw on a film. 2. Diminishing the inserted anode tube overlapping-free representation of the anterior teeth was taken. 3. Alternating the head position of the objects, direction of anode tube and film placing, the shadows of temporo-mandibular joint and zygomatic arch were taken without overlapping the other bone tissues. 4. In the panagraphs applied various shaped contrast media to each anatomical landmark, a radio-anatomical atlas which is necessary to interpret various bone tissues was taken. 5. In order to interpret panagraphic shadows easily, the author has tried this study by comparing the films of the living human skull with the films of the human dry skull applied contrast media.

• Journal of the Semiconductor & Display Technology
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• v.8 no.1
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• pp.43-48
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• 2009

We have examined the problem of the number of quad-tree blocks that an n-dimensional rectangle will be decomposed into on the average. the contribution of this paper are both practical and theoretical. In this paper, we develops the overlapping multi-scale models and the region quad-tree models which is useful in computer graphics animation, image processing, pattern recognition and also for modeling three dimensional objects. These models, which represent something of a conceptual departure from other models developed for multi-scale framework were developed with the specific interest of producing smooth estimates.