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Kobayashi M.,Environmental Planning Bureau | Nakano K.,University of Electro - Communications
IEEJ Transactions on Industry Applications | Year: 2012

Ground-penetrating radar is a tool for imaging the subsurfaces with radar pulses. Since a variety of media including buried objects give different dielectric constants, the positions of the buried objects can be detected on the basis of variations in the reflected return signals. This paper presents a denoising method based on the 2D-Gabor wavelet transform method to solve the pending problems in extracting the signals reflected from buried objects. The validity of our method is demonstrated by comparing it with the f-k filtering method. © 2012 The Institute of Electrical Engineers of Japan.


Kobayashi M.,Environmental Planning Bureau | Nakano K.,University of Electro - Communications
IEEJ Transactions on Industry Applications | Year: 2012

Ground-penetrating radar (GPR) is a useful tool for performing subsurface imaging by using radar pulses. In previous paper, we proposed a method for denoising GPR signals by using 2D Gabor wavelet transforms. In this paper, we present a new method for emphasizing GPR reflected waves from buried objects. We can evaluate the results of the time-frequency analysis of the reflection waves on the basis of the Markov Chain Monte Carlo (MCMC) and the Infinite Gaussian Mixture Model (IGMM) methods. Our proposed methods are effective as pre-processing method for detecting the positions of buried metal pipes. © 2012 The Institute of Electrical Engineers of Japan.


Kobayashi M.,Environmental Planning Bureau | Uchikado T.,University of Electro - Communications | Nakano K.,University of Electro - Communications
International Conference on Wavelet Analysis and Pattern Recognition | Year: 2012

There are many metal pipes under paved roads in modern cities. For example, before installing a traffic signal post, underground mapping must take place to avoid hitting buried pipes. We use a ground-penetrating radar (GPR) to resolve this issue. The goal of this research is to detect the positions of buried pipes with GPR signals automatically. In this paper, we propose a new detection method for locating buried pipes. The proposed method consists of two-dimensional Gabor wavelet transform (2D GWT), Delaunay triangulation (DT), particle filter (PF) and polynomial regression (PR). 2D GWT results represent angle information of GPR signals called B-scan. The GWT results are used as a likelihood function for the PF, and the particles ride on and follow the target signal in B-scan. The DT is used for initial particle generation of the PF, and the positions of pipes are detected by using the PR model for expectations of the PF. We show that most positions of pipes are found by using our method. However, the problem of inaccuracy of some detections needs to be enhanced for automatic detection. © 2012 IEEE.


Uchikado T.,University of Electro - Communications | Kobayashi M.,Environmental Planning Bureau | Nakano K.,University of Electro - Communications | Shin S.,University of Electro - Communications
International Conference on Wavelet Analysis and Pattern Recognition | Year: 2012

When digging paved ground, it is necessary to check in advance the location of buried pipes without damaging them. Ground-penetrating radar (GPR), which can be used for imaging without destroying underground structures, has been commonly used. However it becomes a burden for the user of GPR to visually check the location of the buried pipes from the signal received from a GPR. We have already proposed a wavelet-based method to solve this problem. We introduced a "clustering technique" for emphasizing reflected waves from pipes. Since it is based on a statistical procedure, we have the problem of showing different results for each trial. In this paper, we propose a new method for reducing the dispersion of clustering results by implementing the original method several times. This method is not for detecting the location of buried pipes, but it aims at an improvement of the precision in comparison to the original method. © 2012 IEEE.


Kobayashi M.,Environmental Planning Bureau | Nakano K.,University of Electro - Communications
Proceedings of the 2013 10th International Conference on Information Technology: New Generations, ITNG 2013 | Year: 2013

Wavelet packet transform (WPT) is a useful tool for time-frequency analysis. The WPT based on discrete wavelet transform (DWT) has a well-known problem. It is called shift-variance behavior. It varies the energy of DWT result and fails to detect a changing-point even when an original signal shifts only by one sample. Although the solution of multi-resolution analysis (MRA) by using the complex DWT has been released, many reports about the WPT do not accomplish shift-invariance. In this paper, we describe the reason not to complete the shift-invariance for the WPT. In the complex MRA, it constructs a theoretical structure of a parallel DWT with one sample delayed. However the WPT partly achieves it. In addition, the WPT evenly divides a frequency band into 2n parts where n is the decomposition level. Each band is placed in the wrong frequency order. Whenever high-pass filtered signals are down sampled, the origin of the frequency axis is translated to π. We show how to make the correct order. The two problems of the shift-invariance and the wrong frequency order are solved. © 2013 IEEE.


Kobayashi M.,Environmental Planning Bureau | Nakano K.,University of Electro - Communications
Proceedings, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society | Year: 2014

There are many pipes buried underground in urban areas. An installation of signal posts requires information about actual underground conditions in order not to crack any pipes. However, some areas do not have the accurate pipe layouts because the constructions make a gap between the layouts and the results. Using a ground-penetrating radar (GPR) is a solution for preventing damage to the pipes regardless of the accuracy of layouts. Our goal is to propose an automatic pipes-detection method using the GPR signals. The achievement provides the following two things: streamlining a survey of the underground without expert's experience and reducing a burden on the users. In this paper, we propose a new detection method based on the Dirichlet process mixture (DPM) model. This paper aims at examining the estimation accuracy of our method. First of all, the method of our previous work reduces noises of the GPR signals. Secondly, the two-dimensional Gabor wavelet (2D-GWT) is applied for the denoised signals. Next, samples are drawn from the 2D-GWT result which we regard as a probability distribution. Finally, we obtain the partition of samples by using the fixed DPM model to be proposed. We call it the Dirichlet Process Crescent-signal Mixture model. We estimate the positions of buried pipes from the partitions. Some estimated positions are close to the true ones. However, the estimated depths tend to be greater than the true ones because the relative permittivity of underground is apt to increase. We find that the constant relative permittivity is an erroneous assumption. This issue for precise estimation will be addressed in our future research. © 2014 IEEE.

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