• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.641-644
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• 2005

This paper introduces an Interactive Feature Extraction (!FE) approach for the registration of satellite imagery by matching extracted point and line features. !FE method contains both point extraction by cross-correlation matching of singular points and line extraction by Hough transform. The purpose of this study is to minimize user's intervention in feature extraction and easily apply the extracted features for image registration. Experiments with these imagery dataset proved the feasibility and the efficiency of the suggested method.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.1-11
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• 2023

Deep-learning-based image segmentation is one of the most widely employed lane detection approaches, and it requires a post-process for extracting the key points on the lanes. A general approach for key-point extraction is using a fixed threshold defined by a user. However, finding the best threshold is a manual process requiring much effort, and the best one can differ depending on the target data set (or an image). We propose a novel key-point extraction algorithm that automatically adapts to the target image without any manual threshold setting. In our adaptive key-point extraction algorithm, we propose a line-level normalization method to distinguish the lane region from the background clearly. Then, we extract a representative key point for each lane at a line (row of an image) using a kernel density estimation. To check the benefits of our approach, we applied our method to two lane-detection data sets, including TuSimple and CULane. As a result, our method achieved up to 1.80%p and 17.27% better results than using a fixed threshold in the perspectives of accuracy and distance error between the ground truth key-point and the predicted point.

• Journal of the Korean Chemical Society
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• v.59 no.5
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• pp.407-412
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• 2015

A preconcentration procedure for determination of palladium by laser thermal lens spectrometry (TLS) is proposed. It is based on cloud point extraction of palladium(II) ions as 2-(3,5-dichloro-2-pyridylazo)-5-dimethylaminoaniline (3,5-diCl-PADMA) complexes using octylphenoxypolyethoxyethanol (Triton X-114) as surfactant. The effects of various experimental conditions such as pH, concentration of ligand and surfactant, equilibration temperature and time on cloud point extraction were studied. Under the optimized conditions, the calibration graph was linear in the range of 0.15~6 ng mL⁻¹, and the detection limit was 0.04 ng mL⁻¹ with an enrichment factor of 22. The sensitivity was enhanced by 846 times when compared with the conventional spectrophotometric method. The recovery of palladium was in the range of 96.6%~104.0%. The proposed method was applied to the determination of palladium in water samples.

• Bulletin of the Korean Chemical Society
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• v.25 no.8
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• pp.1133-1136
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• 2004

The need for highly reliable methods for the determination of trace metals is recognized in analytical chemistry and environmental science. A method based on the cloud-point extraction (CPE) technique for the trace analysis of Pb and Cu in water samples is described in this study. The analytes in the initial aqueous solution are complexed with pyrogallol, and 0.1%(w/v) Triton X-114 is added as surfactant. Following phase separation at $50^{\circ}C$, based on the cloud point of the mixture and dilution of the surfactant-rich phase with acidified methanolic solution, the enriched analytes are determined by flame atomic absorption spectrometry. After optimization of the complexation and extraction conditions, the enrichment factors of Pb and Cu were found to be 72 and 85, respectively. Under optimum conditions, the preconcentration of 60 mL of samples in the presence of 0.1%(w/v) Triton X-114 permitted the detection of 0.4 ${\mu}gL^{?1}$ of Pb and 0.05 ${\mu}gL^{?1}$ of Cu. The proposed method was applied successfully to the determination of Pb and Cu in water samples.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.85-92
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• 2019

In this paper, we propose a efficient feature point extraction method that can solve the problem of performance degradation by introducing a preprocessing process when extracting feature points by utilizing the characteristics of 360-degree realistic media. 360-degree realistic media is composed of images produced by two or more cameras and this image combining process is accomplished by extracting feature points at the edges of each image and combining them into one image if they cover the same area. In this production process, however, the stitching process where images are combined into one piece can lead to the distortion of non-seamlessness. Since the realistic media of 4K-class image has higher resolution than that of a general image, the feature point extraction and matching process takes much more time than general media cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1855-1860
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• 2009

This paper caused a distribution utility to generation of analysis fault several cases on the ground of substation in a energy meter three phase current, voltage data measurement to fault type and characteristics. Mother wavelet transformation of suitable to method algorithm from the distribution utility to generation of fault in image impedance etc several parameter for utility characteristics effective to probatory fault point extraction.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.262-270
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• 2002

Although most image indexing schemes ate based on global image features, they have limited discrimination capability because they cannot capture local variations of the image. In this paper, we propose a new region-based image retrieval system that can extract important regions in the image using salient point extraction and image segmentation techniques. Our experimental results show that color and texture information in the region provide a significantly improved retrieval performances compared to the global feature extraction methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.465-472
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• 2015

This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1137-1139
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• 2003

This paper proposed a practical method for building detection and extraction using airborne laser scanning data. The proposed method consists mainly of two processes: low and high level processes. The major distinction from the previous approaches is that we introduce a concept of pseudogrid (or binning) into raw laser scanning data to avoid the loss of information and accuracy due to interpolation as well as to define the adjacency of neighboring laser point data and to speed up the processing time. The approach begins with pseudo-grid generation, noise removal, segmentation, grouping for building detection, linearization and simplification of building boundary , and building extraction in 3D vector format. To achieve the efficient processing, each step changes the domain of input data such as point and pseudo-grid accordingly. The experimental results shows that the proposed method is promising.

• Smart Media Journal
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• v.5 no.4
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• pp.26-40
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• 2016

Recent researches have been conducted for a user of the position acquisition and analysis since the mobile devices was developed. Trajectory data mining of location analysis method for a user is used to extract the meaningful information based on the user's trajectory. It should be preceded by a process of extracting Stay Point. In order to carry out trajectory data mining by analyzing the user of the GPS Trajectory. The conventional Stay Point extraction algorithm is low confidence because the user to arbitrarily set the threshold values. It does not distinguish between staying indoors and outdoors. Thus, the ambiguity of the position is increased. In this paper we proposed extraction method of Stay Point using a statistical analysis. We proposed algorithm improves position accuracy by extracting the points that are staying indoors and outdoors using Gaussian distribution. And we also improve reliability of the algorithm since that does not use arbitrarily set threshold.