• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

• ETRI Journal
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• v.18 no.2
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• pp.61-74
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• 1996

We propose two new rate control schemes to improve MPEG-2 rate control in view of visual quality when scene changes happen. Two proposed schemes are characterized by real-time and non real-time improvement to reduce the impact of scene changes. We also propose a new target-bit prediction method using spatial activity of pictures and present a simple and efficient scene change detection scheme using signed difference of mean absolute difference (MAD). Computer simulation results show that the proposed real-time algorithm effectively alleviates visual quality degradation after scene changes. The proposed non real-time algorithm gives maximum 2 dB improvement in peak signal-to-noise ratio (PSNR) at a scene-changed picture, compared with MPEG-2 rate control scheme and it shows better quality than the real-time one.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1130-1132
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• 2007

In this research, 3D position exploring system was developed to detect direction and position of radiation source by using two general CCD camera. This system consists of a radiation detection device, a controlling device, and a monitoring device. A radiation detection device is composed of a collimator, a scintillator, CCD sensor, and radiation shielding part. Incident radiation is firstly collimated with direction and converted into visual lights in a scintillator. The CCD sensor detect the converted visual light and send a signal as an image. This can explore a radiation source with direction and distance from geometrical structure of two sensors. From these information, the developed 3D position exploring system can provide 3D radiation source information. This research will be useful for managing and processing radioactive materials in remote.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.222-229
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• 2001

Many techniques have been proposed for digital image enlargement, which use spatially neighbored pixels information in a still image. In this paper, we propose the digital image interpolation method that improves edge characteristics by selectively transposing the sub-windows of pseudomedian filter, which results in relatively better performance than others. We have simulated the proposed algorithm using Visual C++ and verified performance of the algorithm by PSNR(Peak signal Noise Ratio) and edge characteristics. Finally, we have designed the adaptive pseudomedian by using synopsys VHDL(Very high speed integrated circuit Hardware Description Language).

• MALSORI
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• no.44
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• pp.83-92
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• 2002

Speech recognition performance is severly degraded under noisy envrionments. One approach to cope with this problem is audio-visual speech recognition. In this paper, we discuss the experiment results of bimodal speech recongition based on enhanced speech feature vectors using lip information. We try various kinds of speech features as like linear predicion coefficient, cepstrum, log area ratio and etc for transforming lip information into speech parameters. The experimental results show that the cepstrum parameter is the best feature in the point of reconition rate. Also, we present the desirable weighting values of audio and visual informations depending on signal-to-noiso ratio.

• Journal of the Korea Computer Industry Society
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• v.3 no.12
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• pp.1725-1736
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• 2002

We describe a characteristic behavior of edge signal intensity, the strictly monotonic variation of intensity across edges and propose a new algorithm for edge detection based on it. We define an extended directional derivatives, which is nonlocal and beyond scaling in the pixel space, to describe that the algorithm is adaptive to the various widths of edges and relevant as an optimal edge detection algorithm. As an industrial application of the algorithm, we discuss a simple computer vision procedure for an example of visual inspection.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.784-792
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• 1990

In this paper, attempts have been made to compare the subjective performance of sub-band coding (SBC) techniques incorporating four representative modulation transfer functions (MTF's) of th human visual system(HVS): Sakrison, Nill, Ngan, and Rao. In SBC, the frequency band of input signal is split into 16 equal sub-bands. In addition, 28 sub-band splitting schemd which splits more sub-bands in low spatial frequency is considered to compare the 4 MTF's effectively. In encoding of each sub-band, the weight of each sub-band obtained from the MTF of HVS is applied to bit allocation process which minimize the weighted mean square error (WMSE). The differential pulse code modulation(DPCM) coder is used to encode the lowest sub-band and the pulse code modulation(PCM) coder is used for the rest of sub-bands. It is found that the images incorporating the MTF of Rao yields the best results in subjective criteria, followed by Ngan, Nill, Sakrison, and the images not employing the HVS.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.385-399
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• 2007

In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.486-490
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• 1989

In this paper, a program controlling an auto-audio media - cassette deck - by a 16 bit personal computer is studied in order to execute audio and visual learning in CAI. The results of this study are as follows. 1. Audio and visual learning is executed efficiently in CAI. 2. Access rate of voice information to text/image information is about 98% and 60% in "play" and "fast forward" respectively. 3. In "fast forward", quality of a cassette tape affects voice information access rate in propotion to motor driving speed. 4. Synchronizing signal may be mistaken by defects of tape itself.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.6-13
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• 2012

An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.