• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.6
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• pp.504-510
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• 2004

The objective of this paper is to propose the image interpolation method with pseudomedian filter for Field warping and morphing, and to evaluate and analyze its subjective image quality. The Field warping relatively gives rise to more computing overhead, but it can use the control line to control the warping result with more elaboration. Due to the working characteristics of the image warping and morphing process, various complex geometrical transformations occur and a image interpolation technique is needed to effectively process them. Of the various interpolation techniques, bilinear interpolation which shows above average performance is the most widely used. However, this technology has its limits in the reconstructivity of diagonal edges. The proposed interpolation method is to efficiently combine the bilinear interpolation and the pseudomedian filter-based interpolation which shows good performance in the reconstructivity of diagonal edges. According to the proposed interpolation method, we could get more natural warping and morphing results than other interpolation methods.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.105-113
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• 2007

In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.213-215
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• 2021

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.681-691
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• 2017

In the clutter environment, it is necessary to update the target tracking filter by detecting the target signal among many measured value data obtained via the radar system, the track does not diverge, and tracking performance is maintained. The method of associating the measurement most relevant to the target track among numerous measurement values is referred to as data association. PSNF and PSNF-m are data association methods of SN-series. In this paper, we provide an IPSNF-m(Integrated Probabilistic Strongest Neighbor Filter-m) algorithm with a track management method based on the track existence probability in PSNF-m algorithm. This algorithm considers not only the presence of the target but also the case where the target is present but not detected. Calculating the probability of each caseenables efficient management. In order to verify the performance of the proposed IPSNF-m, the track existence probability of the IPSNF algorithm applying the track management technique to PSNF, which is known to have similar performance to PSNF-m, is derived. Through simulation in the same environment, we compare and analyze the proposed algorithm with RMSE, Confirmed True Track, and Track Existence Probability that show better performance in terms of track retention and estimation than the existing PSNF-m and IPSNF algorithms.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.375-382
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• 2003

Lip-reading technique based on bimodal is to enhance speech recognition rate in noisy environment. It is most important to detect the correct lip-image. But it is hard to estimate stable performance in dynamic environment, because of many factors to deteriorate Lip-reading's performance. There are illumination change, speaker's pronunciation habit, versatility of lips shape and rotation or size change of lips etc. In this paper, we propose the IIR filtering in time-domain for the stable performance. It is very proper to remove the noise of speech, to enhance performance of recognition by digital filtering in time domain. While the lip-reading technique in whole lip image makes data massive, the Principal Component Analysis of pre-process allows to reduce the data quantify by detection of feature without loss of image information. For the observation performance of speech recognition using only image information, we made an experiment on recognition after choosing 22 words in available car service. We used Hidden Markov Model by speech recognition algorithm to compare this words' recognition performance. As a result, while the recognition rate of lip-reading using PCA is 64%, Time-domain filter applied to lip-reading enhances recognition rate of 72.4%.

• Transactions on Electrical and Electronic Materials
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• v.2 no.1
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• pp.16-21
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• 2001

A new technique to measure low level capacitance variations of a gyroscope is proposed. It is based on the improved CVC(capacitance to voltage converter) biased by a d.c. current source and the peak detector without any low pass filter. This setup of the measurement system makes it possible to provide higher speed of measurement and wide operation range. The d,c, drift of the conventional CVC and stray capacitances are automatically compensated. Key parameters that affect the performance of the measurement system are illustrated and computer simulation results are presented. The demonstrated measurement system for micromachined gyroscope applications shows a linearity of 0.99972 and a resolution of 0.67fF from 10 fF to 120 fF at 10 kHz.

• ETRI Journal
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• v.29 no.2
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• pp.237-239
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• 2007

Interference from IEEE 802.11a systems affects ultra-wideband (UWB) systems significantly. In this letter, we suggest a novel narrow-band interference (NBI) suppression technique based on the singular value decomposition (SVD) algorithm in time-hopping pulse amplitude modulation (TH-PAM) UWB systems. The SVD algorithm is used to approximate the interference which then is subtracted from the received signals. In contrast to the conventional notch filter and rake receiver, our method is more effective and the receiver complexity can be greatly reduced.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.27-35
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• 1993

In this paper, a new algorithm for high level security and quality of speech is proposed. The algorithm is based on the rearrangement of the fast fourier transform (FFT) coefficients with pre and post filter process, hamming window and adaptive pseudo spectrum insertion. Then, the pre and post filters are used for the whitening of speech spectrum and the adaptive pseudo spectrum is inserted for the unclassification of silence/speech. Also, the hamming window technique is applied for the robustness to the syncronization error in the telephone line. According to the simulation results, it can be seen that the security of scrambled signal and the quality of descrambled signal have been improved fairly in both subjective and objective performance test and the new FFT scrambler is robust to the synchronization error.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.651-658
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• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.