• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1097-1107
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• 2001

In this paper, the wall following navigation algorithm of the mobile robot using a mono vision system is described. The key points of the mobile robot navigation system are effective acquisition of the environmental information and fast recognition of the robot position. Also, from this information, the mobile robot should be appropriately controlled to follow a desired path. For the recognition of the relative position and orientation of the robot to the wall, the features of the corridor structure are extracted using the mono vision system, then the relative position, the offset distance and steering angle of the robot from the wall, is derived for a simple corridor geometry. For the alleviation of the computation burden of the image processing, the Kalman filter is used to reduce search region in the image space for line detection. Next, the robot is controlled by this information to follow the desired path. The wall following control scheme by the PD control scheme is composed of two control parts, the approaching control and the orientation control, and each control is performed by steering and forward-driving motion of the robot. To verify the effectiveness of the proposed algorithm, the real time navigation experiments are performed. Through the result of the experiments, the effectiveness and flexibility of the suggested algorithm are verified in comparison with a pure encoder-guided mobile robot navigation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1231-1238
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• 2005

This paper presents a new fast encoding algorithm for image vector quantization that incorporates the partial distances of multiple features with a multidimensional look-up table (LUT). Although the methods which were proposed earlier use the multiple features, they handles the multiple features step by step in terms of searching order and calculating process. On the other hand, the proposed algorithm utilizes these features simultaneously with the LUT. This paper completely describes how to build the LUT with considering the boundary effect for feasible memory cost and how to terminate the current search by utilizing partial distances of the LUT Simulation results confirm the effectiveness of the proposed algorithm. When the codebook size is 256, the computational complexity of the proposed algorithm can be reduced by up to the $70\%$ of the operations required by the recently proposed alternatives such as the ordered Hadamard transform partial distance search (OHTPDS), the modified $L_2-norm$ pyramid ($M-L_2NP$), etc. With feasible preprocessing time and memory cost, the proposed algorithm reduces the computational complexity to below the $2.2\%$ of those required for the exhaustive full search (EFS) algorithm while preserving the same encoding quality as that of the EFS algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.365-371
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• 2009

A intelligent mobile hexapod robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1431-1437
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• 2011

This paper proposes a novel watermarking algorithm that protects digital copyrights and is robust to attacks. Watermarks are embedded in the subband including the significant part of the signal such as a pitch. Generally, the subband containing the pitch has the biggest energy. In order to find this subband, wavelet packet transform is used to decompose the subbands and their energy are calculated. The signal of the selected subbands is transformed in frequency domain using FFT. The watermarks are embedded using QIM for samples higher than a certain threshold. The blind detection uses the Euclidean distance. The proposed method shows less than 5% BER in the audio watermark benchmarking.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.460-465
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• 2021

In active sonar, time delay estimation is used to find the distance between the target and the sonar. Among the time delay estimation methods for active sonar, estimation in the frequency domain is widely used. When estimating in the frequency domain, the time delay can be thought of as a frequency estimator, so it can be used relatively easily. However, this method is prone to rapid increase in error due to noise. In this paper, we propose a new method which applies weighted dictionary and sparsity in order to reduce this error increase and we extend it to two receivers to propose an algorithm for estimating the time delay between two receivers. And the case of applying the proposed method and the case of not applying the proposed method including the conventional frequency domain algorithm and Generalized Cross Correlation-Phase transform (GCC-PHAT) in a white noise environment were compared with one another. And we show that the newly proposed method has a performance gain of about 15 dB to about 60 dB compared to other algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.104-113
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• 2022

In this paper, we propose deep learning-based target distance and velocity estimation technique for OFDM radar systems. In the proposed technique, the 2D periodogram is obtained via 2D fast Fourier transform (FFT) from the reflected signal after removing the modulation effect. The periodogram is the input to the conventional and proposed estimators. The peak of the 2D periodogram represents the target, and the constant false alarm rate (CFAR) algorithm is the most popular conventional technique for the target's distance and speed estimation. In contrast, the proposed method is designed using the multiple output convolutional neural network (CNN). Unlike the conventional CFAR, the proposed estimator is easier to use because it does not require any additional information such as noise power. According to the simulation results, the proposed CNN improves the mean square error (MSE) by more than 5 times compared with the conventional CFAR, and the proposed estimator becomes more accurate as the number of transmitted OFDM symbols increases.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• Journal of ILASS-Korea
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• v.7 no.4
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• pp.23-31
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• 2002

In this study, the sizes and velocities of droplets in sprays were measured by image processing method from digital images of local region of sprays. The morphological method based on the Euclidean distance transform, Watershed separation, and perimeter image was adopted for the recognition and separation of overlapped particles. The match probability method was used for the particle tracking and pairing. The measurement results show that the present method may be reliable for the analysis of the motion and distribution of droplets produced by spray and atomization devices.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.04a
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• pp.98-105
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• 1998

In this study, the boundary element analysis in dynamics for the multilayered semi-infinite plane is developed using the fundamental solution for moving loads. Also the indirect method and superposition method are introduced to consider the multilayered systems and moving loads. At each layer the fundamental solution can be obtained by solving the governing equation which is transformed by the Fourier transform. The governing equation can be solved by three conditions; continuity conditions of displacement and stress, the traction free condition at the surface and the radiation condition at the surface and the radiation condition at the infinite distance. To verify the solution and the developed algorithm, the theoretical solution for the homogeneous layer and commercial FEM program is compared with the results of this study.