• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1275-1283
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• 1990

Perception of surfaces from range images plays a key role in 3-D object recognition. Recognition of 3-D objects from range images is performed by matching the perceived surface descriptions with stored object models. The first step of the 3-d object recognition from range images is image segmentation. In this paper, an approach for segmenting 3-D range images into symbolic surface descriptions using spatial Gabor filter is proposed. Since the phase of data has a lot of important information, the phase information with magnitude information can effectively segment the range imagery into regions satisfying a common homogeneity criterion. The phase and magnitude of Gabor filter can represent a unique featur vector at a point of range data. As a result, range images are trnasformed into feature vectors in 3-parameter representation. The methods not only to extract meaningful features but also to classify a patch information from range images is presented.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.39-45
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• 2017

In this paper, we propose three compensation methods to solve problems in high-resolution airborne infrared camera and to improve long-range target information acquisition performance. First, image motion and temporal noise reduction technique which is caused by atmospheric turbulence. Second, thermal blurring image correction technique by imperfect performance of NUC(Non Uniformity Correction) or raising the internal temperature of the camera. Finally, DRC(Dynamic Range Compression) and flicker removing technique of 14bits HDR(High Dynamic Range) infrared image. Through this study, we designed techniques to improve the acquisition performance of long-range target information of high-resolution airborne infrared camera, and compared and analyzed the performance improvement result with implemented images.

• ETRI Journal
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• v.43 no.1
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• pp.120-132
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• 2021

A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.420-425
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• 2001

The information content is determined by establishing the system range for each of the FRs and by determing the overlap between system range and the design range (i.e the designer-specified range). However, conventional information content doesn't include designer's intention sufficiently. In this paper, the satisfaction function is presented to embody designer's intention by calculating information contents. The satisfaction function is created in order to deal with the uncertanties involved in determining the design range and the system range in terms of a given physical parameter. So, the satisfaction function help designer to choose the optimal design among many proposed design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.597-618
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• 2019

Categorical range aggregation, which is conceptually equivalent to running a range aggregation query separately on multiple datasets, returns the query result on each dataset. The challenge is when the number of dataset is as large as hundreds or thousands, it takes a lot of computation time and I/O. In previous work, only a single dimension of the range restriction has been solved, and in practice, more applications are being used to calculate multiple range restriction statistics. We proposed MCRI-Tree, an index structure designed to solve multi-dimensional categorical range aggregation queries, which can utilize main memory to maximize the efficiency of CRA queries. Specifically, the MCRI-Tree answers any query in $O(nk^{n-1})$ I/Os (where n is the number of dimensions, and k denotes the maximum number of pages covered in one dimension among all the n dimensions during a query). The practical efficiency of our technique is demonstrated with extensive experiments.

• Journal of Sensor Science and Technology
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• v.30 no.2
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• pp.76-81
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• 2021

In this study, we propose a machine vision system with a high object recognition rate. By utilizing a multiple-exposure image sensing technique, the proposed deep learning-based machine vision system can cover a wide light intensity range without further learning processes on the various light intensity range. If the proposed machine vision system fails to recognize object features, the system operates in a multiple-exposure sensing mode and detects the target object that is blocked in the near dark or bright region. Furthermore, short- and long-exposure images from the multiple-exposure sensing mode are synthesized to obtain accurate object feature information. That results in the generation of a wide dynamic range of image information. Even with the object recognition resources for the deep learning process with a light intensity range of only 23 dB, the prototype machine vision system with the multiple-exposure imaging method demonstrated an object recognition performance with a light intensity range of up to 96 dB.

• Korean Institute of Interior Design Journal
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• v.20 no.6
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• pp.183-191
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• 2011

This study is to set up the appropriate range of observation time through contemplating the characteristics of observation time run for the information acquisition of space. The conclusions reached through this study are as the followings. First, this study could find out that even though the evaluation elements on the three types for image evaluation were the same, the information acquisitions were different as those types varied. On the other hand, the change of the average run-time by type for the information acquisition was found not to be big, in other words, even though the run-time was alike, the information acquisitions varied depending on the type. Second, he evaluation by language media showed the average value by element had the order of [shape>position>number>existence] and the range of their run-time was 94.6~102.9 seconds. The average rate of information acquisition shown at the visual media had the order of [composition>shape>material&color] and the range of run-time was 93.1~99.7 seconds. Third, the evaluation by language media showed that for male subjects the range of information acquisition rate was 39.1~91.4% and that of run-time 85.1~106.0 seconds and for female ones 46.0~94.6% and 96.3~112.3 seconds respectively. In case of the visual media, male subjects showed the range of information acquisition rate was 40.3-66.7% and the range of run-time 82.4~97.9 seconds and the female ones, 42.2~71.0% and 94.0~115.1 seconds respectively, through which we could see that at the evaluation by language media and visual media both the female's range of information acquisition and that of observation time were higher than the male's.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.33-42
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• 2013

This paper presents a multihop range-free localization algorithm to estimate the physical location of a normal node with local connectivity information in anisotropic sensor networks. In the proposed algorithm, a normal node captures the detour degree of the shortest path connecting an anchor pair and itself by comparing the measured hop count and the expected hop count, and the node estimates the distances to the anchors based on the detour degree. The normal node repeats this procedure with all anchor combinations and pinpoints its location using the obtained distance estimates. The proposed algorithm requires fewer anchors and less communication overhead compared to existing range-free algorithms. We showed the superiority of the proposed algorithm over existing range-free algorithms through MATLA simulations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.185-190
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• 2006

The correct estimation of the ionospheric delays is very important for the precise kinematic positioning especially in case of the long baseline. In case of triple frequency system, the ionospheric delays can be estimated from the measurements, but, in case of dual frequency system, the situation is not so simple. The precision of those supplied by the external information source such as IONEX is not sufficient. The high frequency component is neglected, and the precision of the low frequency component is not sufficient for the long baseline positioning. On the other hand, the high frequency component can be estimated from the phase range measurements. If the low frequency components are estimated by using the external information source or pseudo range measurements, a more reasonable estimation of the ionospheric delays may be possible. It has already been discussed by the author that the estimation of the low frequency components by using the external information source is not sufficient but fairly effective. The estimation using the pseudo range measurements is discussed in the present paper. The accuracy is not sufficient at present because of the errors in the pseudo range measurements. It is clarified that the bias errors in the pseudo range measurements are responsible for the poor accuracy of the ionospheric delays. However, if the accuracy of the pseudo range measurements is improved in future, the method would become very promising.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.711-714
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• 1989

Autonomous mobile robot Yamabico and his newly developed ultrasonic range finding module(URF) are described. Yamabico is a self-contained autonomous robot for in-door environment. It has a modularized architecture, which consists of master module, ultrasonic range finding module, locomotion module, voice synthesizer module and console. Newly developed ultrasonic range finding module has a 68000 processor and Dual-port memory for communication. It controls the ultrasonic transmitters and receivers and calculate the range distances for 12-direction, simultaneously within every 60 milliseconds.