• Proceedings of the KSRS Conference
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• v.2
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• pp.684-687
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• 2006

Airborne imagery must be precisely orthorectified to be used as geographical information data. GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) data were employed to automatically orthorectify airborne images. In this study, 154 frame airborne images and LIDAR vector data were acquired. LIDAR vector data were converted to raster image for employing as reference data. To derive images with constant brightness, flat field correction was applied to the whole images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated using 50 ground control points collected in arbitrary selected five images and LIDAR intensity image. In validation results, RMSE (Root Mean Square Error) was 0.365 smaller then two times of pixel spatial resolution at the surface. It is possible that the derived mosaicked airborne image by this automatic orthorectification method is employed as geographical information data.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.907-917
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• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.130-134
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• 2015

The automobile industry is ubiquitous and involved in the handling of metal, machines, electricity, electron, and chemistry including the products of many types of processes. In the process of installing engines as a part of the car assembly line, the measurement and correction of the position of the stud bolts consumes a great deal of time. Additionally, defective parts must be manually removed. In the process of engine installation, the speed of the operation, related to the economics of vehicle assembly, is dependent upon measuring the precise position of the stud bolt, reducing the length of correction time, and increasing the working rate. This paper deals with securing the economic feasibility of the manufacturing process, increasing the safety by removing risk factors in the working area, and improving and equalizing the quality by developing an automatic system for the process involving a stud bolt.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.77-85
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• 2006

The last target of this study is to develop ship's Digital Compass that can be substitute with conventional ship's Magnetic Compass. At first, new Digital Compass system was developed with three-axis high accuracy Flux-gate sensors and small sized step motor. Then after, new deviation correction theory without ship's swinging procedures was proposed to provide automatic deviation analysis, correction and renewal. Throughout the performance evaluation tests on the training ship 'SAE-NU-RI', the effectiveness of developed Digital Compass and proposed deviation correction theory are verified.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.67-80
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• 2011

On an automated business document processing system maintaining financial data, errors on query based retrieval of numbers are critical to overall performance and usability of the system. Automatic spelling correction methods have been emerged and have played important role in development of information retrieval system. However scope of the methods was limited to the symbols, for example alphabetic letter strings, which can be reserved in the form of trainable templates or custom dictionary. On the other hand, numbers, a sequence of digits, are not the objects that can be reserved into a dictionary but a pure markov sequence. In this paper we proposed a new OCR model for spelling correction for numbers using the multiple streams and the context based correction on top of probabilistic information retrieval framework. We implemented the proposed error correction model as a sub-module and integrated into an existing automated invoice document processing system. We also presented the comparative test results that indicated significant enhancement of overall precision of the system by our model.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.1-6
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• 2010

The lens distortion in the machine vision system is inevitable phenomenon. Distortion is getting worse, due to the selection of lens in the trend of reducing prices and size of the system. In this trend, the distortion correction becomes more important. But, the traditional correction methods has problems, such as complexity and requiring more operations. Effective distorted digital image correction is the precondition of target detection and recognition based on vision inspection. To overcome the disadvantage of traditional distortion correction algorithms, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on photogrammetry method is proposed in this paper. In our method, we use the lattice image as the measurement target. Through the experimental results, we could find that we can reduce the processing time by 4ms. And also the inspection failure rate of our method was reduced by 2.3% than human-eyes inspection method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.6
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• pp.630-637
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• 2003

This paper explains the impact of frequency error on the performance of WCDMA mobile communication systems and what brings about the frequency error between the base station and the mobile station, and then presents automatic frequency error correction method in mobile receiver. On the basis of system requirement related to frequency stability, the integration test between the base station and the mobile station was accomplished. After applying automatic frequency error correction to mobile receiver, 4 Hz of frequency error at transmitting frequency was obtained. The result met frequency error requirement of ${\pm}$0.1 ppm(about ${\pm}$200 ㎐). Performance degradation due to frequency error was measured by means of Error Vector Magnitude(EVM) at transmitter and Ec/Io at receiver, respectively and then the interface requirement between Modem control signal and RF was suggested to improve the correctness of frequency error control.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.323-329
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• 2009

This paper presents an automatic LCD gamma control system using gamma curve optimization. It controls automatically gamma adjustment registers in mobile LCD driver IC to reduce gamma correction error and adjusting time. The proposed gamma system contains Module-Under-Test (MUT, LCD module), PC installed with program, multimedia display tester for measuring luminance, and control board for interface between PC and LCD module. Proposed algorithm and program are applicable for most of the LCD modules. It is realized to calibrate gamma values of 1.8, 2.0, 2.2 and 3.0. The control board is designed with DSP and FPGA, and it supports various interfaces such as RGB and CPU. Developed automatic gamma control system showed significantly reduced gamma adjusting time of 240 sec. and much less average gamma error of 11% than 42h and 27% with conventional manual method. We believe that the proposed system is very useful to provide high-quality LCD and to improve production process.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.17-22
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• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.