• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.3010-3023
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• 1998

GA has a fast convergence speed in searching the one point around optimal value. But it's convergence time increase in searching the region around optimal value because it has no regional searching mechanism. BP has the tendency to converge the local minimum because it has global searching mechanism. To overcome these problems, a method in which a genetic algorithm and a back propagation are applied in turn is proposed in this paper. By using a genetic algorithm, we compute optimal synaptic strength and offset value. And then, these values are fed to the input of the back propagation. This proposed method is superior to each above method in improving the convergence speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.1
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• pp.164-169
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• 2003

In this paper, we investigate recognition of human faces in a meeting room. The major challenges of identifying human faces in this environment include low quality of input images, poor illumination, unrestricted head poses and continuously changing facial expressions and occlusion. In order to address these problems we propose a novel algorithm, Dynamic Space Warping (DSW). The basic idea of the algorithm is to combine local features under certain spatial constraints. We compare DSW with the eigenface approach on data collected from various meetings. We have tested both front and profile face images and images with two stages of occlusion. As a result from the experiment, we obtained 82.7% for PCA algotithm, and 89.4% for DSW. We get to obtain 6.9% better result from conductive DSW approach rather than PCA. It turned out to be that it shows more original and unique facial image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.424-442
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• 2014

Most recent research on iterative solutions for interference alignment (IA) presents solutions assuming channel reciprocity based on the suppression of interference from undesired sources by using an appropriate decoding matrix also known as a receiver combining matrix for multiple input multiple output (MIMO) interference channel networks and reciprocal networks. In this paper, we present an alternative solution for IA by designing precoding and decoding matrices based on the concept of signal leakage (the measure of signal power that leaks to unintended users) on each transmit side. We propose an iterative algorithm for an IA solution based on maximization of the signal-to-leakage-and-noise ratio (SLNR) of the transmitted signal from each transmitter. In order to make an algorithm removing the requirement of channel reciprocity, we deploy maximization of the signal-to-interference-and-noise ratio (SINR) in the design of the decoding matrices. We show through simulation that minimizing the leakage in each transmission can help achieve enhanced performance in terms of aggregate sum capacity in the system.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.21-26
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• 2015

In this paper, we propose a system which can detect the smoke in real time from the high-quality IP camera. For real-time processing, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. To recognize smoke, color information and morphological characteristics of smoke, as well as the dynamic characteristics of the smoke also considered for candidate regions. To combine the characteristics of the various smoke effectively, the Adaboost algorithm, was used as the boosting algorithm finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect smokes.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.430-443
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• 2003

The objective of this paper is to evaluate most useful feature vector space using the angle, velocity and location features from gesture trajectory which extracted hand regions from consecutive input images and track them by connecting their positions. For this purpose, the gesture tracking algorithm using color and motion information is developed. The recognition module is a HMM model to adaptive time various data. The proposed algorithm was applied to a database containing 4,800 alphabetical handwriting gestures of 20 persons who was asked to draw his/her handwriting gestures five times for each of the 48 characters.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.271-280
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• 2009

In this paper, we propose a smoke detection method using region growing method in outdoor video sequences. Our proposed method is composed of three steps; the initial change area detection step, the boundary finding and expanding step, and the smoke classification step. In the first step, we use a background subtraction to detect changed areas in the current input frame against the background image. In difference images of the background subtraction, we calculate a binary image using a threshold value and apply morphology operations to the binary image to remove noises. In the second step, we find boundaries of the changed areas using labeling algorithm and expand the boundaries to their neighbors using the region growing algorithm. In the final step, ellipses of the boundaries are estimated using moments. We classify whether the boundary is smoke by using the temporal information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.73-81
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• 2006

This paper proposes the improved orthogonal projection method as a new technique advancing the performance of the acoustic echo canceller. Comparing with the widely used NLMS adaptive algorithm which is simple and stable, it shows that this method has the improvement of the convergence speed for signals with the large auto-correlation, and has small computational quantities. In order to testify performances of the orthogonal projection method whom this paper proposes, we have coded a simulation program md executed computer simulations. We observed convergence curves by using two adaptive algorithm for noises and speeches. From simulation results for two input signals, the proposed method shows the high ERLE and the fast convergence and the stable operation in case of using speeches as well as noises.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.137-145
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• 1998

In this paper, we propose a tube-hole center detection vision algorithm verifying the position of a tele-controlled robot and providing visual information for increasing reliability and efficiency in the diagnosis of steam generator (SG) tubes in nuclear power plant. A tele-controlled robot plays a role in carrying the probe used in inspecting the integrity of SG tubes. Thus accurately locating a tele-controlled robot on the desired tube-hole center is important issue for reliability of inspection. To do this work, we have to find the tube-hole center locations from the input image. At first, we apply the three-class segmentation method modified for this application. WE extract minimum bounding rectangles (MBRs) in the theresholded binary image. Second, for discriminating between MBR by tube and MBR by noise, we introduce the MBR rejection rules as knowledge-based rule set. MBRs are divided into the very dark region MBRs and the very bright region MBRs. In order to describe the region of complete tube-hole, the MBRs need a process of pairing each other. We then can find the tube-hole center from the paired MBR. For more accurately finding the tube-hole center in several sequential images, the centers of some frames need to be averaged. We tested the performance of our method using hundreds of real images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.585-594
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• 2000

The exact path following of an autonomous mobile robot in a factory and an unreliable environment has many disadvantages in case of a classical control algorithm. In this paper, a neural network control approach based on an error back propagation algorithm is proposed for controlling a mobile robot to follow a line installed on the road. Since not only the three recognized informations from three sensors attached on a mobile robot but also the ten detailed informations in non recognition area are learned with input patterns, a mobile robot moves smoothly an installed line in spite of non perception space. The mobile robot has an effect of error minimization with a short time till a destination. To test an effectiveness of the proposed controller, the two motor velocity changes which is affected from a moving angle change of a mobile robot are simulated with computer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1191-1202
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• 1999

We propose an efficient vehicle detection and classification algorithm for an electronic toll collection using the feature which is robust to abrupt intensity change between consecutive frames. The local correlation coefficient between wavelet transformed input and reference images is used as such a feature, which takes advantage of textural similarity. The usefulness of the proposed feature is analyzed qualitatively by comparing the feature with the local variance of a difference image, and is verified by measuring the improvements in the separability of vehicle from shadowy or shadowless road for a real test image. Experimental results from field tests show that the proposed vehicle detection and classification algorithm performs well even under abrupt intensity change due to the characteristics of sensor and occurrence of shadow.