• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.1-9
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• 2008

One of the problems for implementing the spot detection phase in the 2-DE gel image analysis program is the eliminating noises in the image. Remained noises after the preprocessing phase cause the over-segmented regions by the segmentation phase. To identify and exclude the over-segmented background regions, if we use the fixed thresholding method that is choosing an intensity value for the threshold, the spots that is invisible by the eyes but mean a very small amount proteins which have important role in the biological samples could be eliminated. This paper propose an adaptive thresholding method that come from an idea that is got on statistical analysing for the prominences of the peaks. The adaptive thresholding method works as following. Firstly we calculate an average prominence value curve and fit it to exponential function curve, as a result we get parameters for the exponential function. And then we calculate a threshold value by using the parameters and probability distribution of errors. Lastly we apply the threshold value to the region for determining the region is a noise or not. According to the probability distribution of errors, the reliability is 99.85% and we show the correctness of the proposed method by representing experiment results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.148-158
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• 2008

This paper proposes an efficient signal to noise ratio (SNR) estimation algorithm and its hardware implementation for adaptive transmission system using M-ary modulation scheme. In this paper, we present the implementation results of the proposed algorithm for the second generation digital video broadcasting via satellite (DVB-S2) system, and the proposed algorithm can be tailored to the other communication systems using adaptive transmissions. We built a look-up table (LUT) using the theoretical background of the received signal distribution, and by using this LUT we need just two comparators and a counter for the hardware implementation. For this reason, the hardware of the proposed scheme produces accurate estimation results even with extremely low complexity. The simulation results investigated in this paper reveal that the proposed method can produce estimation results within the specified SNR range in the DVB-S2 system, and it requires a few hundreds of samples for average estimation error of about 1 dB.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.610-619
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• 2015

*In this paper, we propose a real-time face tracking system using an adaptive face detector and a tracking algorithm. An image is divided into the regions of background and face candidate by a real-time updated skin color identifying system in order to accurately detect facial features. The facial characteristics are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted by Principal Component Analysis (PCA), and the interpreted principal components are processed by Support Vector Machine (SVM) that classifies into facial and non-facial areas. The movement of the face is traced by Kalman filter and Mean shift, which use the static information of the detected faces and the differences between previous and current frames. The proposed system identifies the initial skin color and updates it through a real-time color detecting system. A similar background color can be removed by updating the skin color. Also, the performance increases up to 20% when the background color is reduced in comparison to extracting features from the entire region. The increased detection rate and speed are acquired by the usage of Kalman filter and Mean shift.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• Journal of the Ergonomics Society of Korea
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• v.36 no.2
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• pp.145-156
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• 2017

Objective: This study aims to compare the usability of the adaptive touch design method with that of the height adjustable design method that are applied to the Korean QWERTY keyboard and Naratgul keyboard on smartphones, examine the results, and present practical implications. Background: Smartphone manufacturers have failed to satisfy every user with their uniform touch keyboard designs that do not consider the high use rates of keypad use. In reality, touch keyboard designing customized for every individual is impossible, but there need to be researches on was to improve usability by having touch areas changed automatically depending on user behaviors or having users adjust the keyboard height depending on their hand size. Method: As for the design methods, an object group was given smartphones with the adaptive touch design method and the other group those with the height adjustable design method. As they entered the same characters in the smartphones, typing error rates and text input speed were measured and the average values were compared. 35 individuals who would frequently use smartphones in daily life participated in the experiment. The group variable was the type of touch keyboards, and the test variables were typing error rates and text input speed, for which a T-test was implemented. Results: As for the QWERTY keyboard, the significant improvement effect was verified as the typing error rate of the adaptive touch design method was 4.21% but that of the height adjustable design method was 3.28% although there was no significant difference in terms of text input speed. As for the Naratgul keyboard, in contrast, the typing error rate of the adaptive touch design method was 2.5% while that of the height adjustable design method was 1.48%, which indicates a measure of improvement, but the effect was not significant. On the other hand, the text input speed per minute was improved as much as 22.2%, which is significant. Conclusion: First, the Korean touch keyboard usability of the adaptive touch design method and that of the height adjustable design method, when applied to Model A of Company L, showed significant difference from each other. Second, the height adjustable design method was applied to the QWERTY keyboard, the typing error rate was improved significantly. This indicates that as the keyboard height was raised, the number of buttons within the range of fingering decreased, decreasing the touch bias was reduced. Third, the height adjustable design method was applied to the Naratgul keyboard, the text input speed was improved. Application: When the QWERTY keyboard was applied to a smartphone as small as 5.5inch or less, it is highly probably that the height adjustable design method decreases the typing error rate. It may be considered to develop additional UX functions to make the keyboard font larger or give users the option to adjust button intervals in utilization of the SW advantages of the height adjustable design method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.28-36
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• 2009

In this paper, we propose a frame-rate up-conversion method for temporal quality enhancement. The proposed method adaptively changes search range during hierarchical motion estimation and reconstructs hole regions using the proposed bi-direction prediction and linear interpolation. In order to alleviate errors due to inaccurate motion vector estimation, search range is adaptively changed based on reliability and for more accurate, motion estimation is performed in descending order of block variance. After segmentation of background and object regions, for filling hole regions, the pixel values of background regions are reconstructed using linear interpolation and those of object regions are compensated based on the proposed hi-directional prediction. The proposed algorithm is evaluated in terms of PSNR with original uncompressed sequences. Experimental results show that the proposed algorithm is better than conventional methods by around 2dB, and blocky artifacts and blur artifacts are significantly diminished.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4
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• pp.288-295
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• 2004

Detection and localization of a slow and quiet target in shallow water environments is a challenging problem for which it is well known that snapshot is deficient because of a fast and strong interferer. This paper presents waveguide interference filtering technique that mitigate strong interferer problems in adaptive matched field processing. MCM (multiple constraint method) based on NDC (null direction constraint) has been proposed for new spatial interferer filter. MCM-NDC using replica force a interferer component to be filtered through CSDM (cross-spectral density matrix). This filtering have an effect on sidelobe reduction and restoring of signal gain of a quiet target. This technique was applied to a simulation on Pekeris waveguide and vertical array data from MAPLE03 (matched acoustic properties and localization experiment) in the East Sea and was shown to improve SBNR (signal-to-background-and-noise ratio) over the standard MVDR (minimum-variance distortionless response) and NSP (null space projection) technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.165-173
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• 2012

In this paper, we propose a random backoff scheme for Emergency Warning Messages (EWMs) in the vehicle-to-vehicle environment. The EWMs are disseminated from a vehicle that detects an emergency situation to other vehicles in a multi-hop fashion. Since the vehicle-to-vehicle communication based on IEEE 802.11 adapts CSMA/CA, the density of vehicles increase the probability of collisions between transmissions. Moreover, in the presence of background traffic, the EWM should have a higher priority than that of other messages in neighboring vehicles. To that end, we propose the Distant-Dependent Adaptive Backoff (DDAB) scheme, which set a different contention window for random backoff depending on the distance from the sender to the receiver. In the case when a vehicle is expected to located in the outskirts of the communication boundary, the proposed scheme makes the contention window size small in order to compete the background traffic transmission. Otherwise the contention window is set to a large number to reduce the collision possibility among the EWM transmissions. Via simulations, we show that the proposed scheme performs better than the previous schemes for EWM.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.13-19
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• 2011

In this paper, a visual surveillance system using SOPC based NIOS II embedded processor and C2H compiler was implemented. In this system, the IP is constructed by C2H compiler for the output of the camera images, image processing, serial communication and network communication, then, it is implemented to effectively control each IP based on the SOPC and the NIOS II embedded processor. And, an algorithm which updates the background images for high speed and robust detection of the moving objects is proposed using the Adaptive Gaussian Mixture Model(AGMM). In results, it can detecte the moving objects(pedestrians and vehicles) under day-time and night-time. It is confirmed that the proposed AGMM algorithm has better performance than the Adaptive Threshold Method(ATM) and the Gaussian Mixture Model(GMM) from our experiments.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.176-183
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• 2013

We propose a rolled fingerprint merging algorithm that effectively merges plain fingerprints in consecutive frame units that are fed through rolling and detects more fingerprint minutiae in order to increase the fingerprint recognition rate. The proposed rolled fingerprint merging algorithm uses a adaptive projection mask; it contains a detector that separates plain fingerprints from the background and a projection mask generator that sequentially projects the detect ed images. In addition, in the merging unit, the pyramid-shaped projection method is used to detect merged rolled fingerprints from the generated variable projective mask, starting from the main images. Simulations show that the extracted minutia e are 46.79% more than those from plain fingerprints, and the proposed algorithm exhibits excellent performance by detecting 52.0% more good fingerprint minutiae that are needed for matching.