• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.135-144
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• 2022

In this study, we transformed 4680 type lithium-ion batteries to 3-dimensional CAD models and present a methodology to detect defects using Radon inverse transformation. Transparency was applied to the model to make it look like a CT image when viewed from the front. One normal and three defect models were created and analyzed. The models were saved as image files while rotating at a certain angle. Then, we used the Radon inverse transformation to reconstruct the original 3D geometry from the image files. Finally, we successfully found defects in the defect models for three cases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.124-129
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• 2003

A novel watermark registration method based on Radon transform for self-referencing watermark is presented. The novel method was successful in registering the watermark of the image that has undergone affine transformations and severe lossy compression, whereas the conventional method based on peak detection failed to register the watermark.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.122.2-122
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• 1999

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.661-680
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• 2016

The vehicle license plate recognition (VLPR) system analyzes and monitors the speed of vehicles, theft of vehicles, the violation of traffic rules, illegal parking, etc., on the motorway. The VLPR consists of three major parts: license plate detection (LPD), license plate character segmentation (LPCS), and license plate character recognition (LPCR). This paper presents an efficient method for the LPCS and LPCR of Korean vehicle license plates (LPs). LP tilt adjustment is a very important process in LPCS. Radon transformation is used to correct the tilt adjustment of LP. The global threshold segmentation method is used for segmented LP characters from two different types of Korean LPs, which are a single row LP (SRLP) and double row LP (DRLP). The cross-correlation matching method is used for LPCR. Our experimental results show that the proposed methods for LPCS and LPCR can be easily implemented, and they achieved 99.35% and 99.85% segmentation and recognition accuracy rates, respectively for Korean LPs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.123-131
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• 2012

As the price of traditional fuels soar, the alternatives are becoming more viable. And manufacturers are promoting the growing viability of electric and biofuel-powered vehicles through longer warranties. Now, these longer green environment (emission)warranties, sometimes called extended warranties or "super warranties," have been adapted. The main result of this paper is to present a new method to approximate a bivariate warranty function by using Radial Basis Function Network with application of Radon Transform and its inverse which is used to reduce the dimension of the warranty space. This method consist of the following stages: First, by using the Radon Transform, the bivariate warranty function can be reduced to one dimensional function. Second, each of the one dimensional functions is approximated by using neural network technique into neural sub-networks. Third, these neural sub-networks are combined together to form the final approximation neural network. Four, by using the inverse of radon transform to this final approximation neural network we get the approximation to the given function. Also, we apply the above method to some green warranty data of automotive vehicle company.

• Communications of the Korean Mathematical Society
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• v.37 no.1
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• pp.195-205
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• 2022

In this paper, we provide various characterizations for the composition operator on Lorentz spaces L(p, q), 1 < p ≤ ∞, 1 ≤ q ≤ ∞ to have finite ascent (descent) in terms of its inducing measurable transformation. At the end, in order to demonstrate our outcomes, some examples are given.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1216-1224
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• 2015

In this paper, a detection algorithm for the removal of needle in oriental clinic is presented. First, in the proposed method, the candidate areas of each needle penetrated are selected by using the RGB color information of needle head, and the false candidates are removed by considering their area size. Next, two main edges of the needle are extracted through using the edges of selected candidate areas and their radon transformation. The final verification of penetrated needle is accomplished by using the morphological analysis of these two edge lines. In the experiments, the detection rate of proposed method reaches to 99% for the 36 images containing 294 needles.

• ETRI Journal
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• v.23 no.2
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• pp.41-51
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• 2001

MPEG-7 standardization work has started with the aims of providing fundamental tools for describing multimedia contents. MPEG-7 defines the syntax and semantics of descriptors and description schemes so that they may be used as fundamental tools for multimedia content description. In this paper, we introduce a texture based image description and retrieval method, which is adopted as the homogeneous texture descriptor in the visual part of the MPEG-7 final committee draft. The current MPEG-7 homogeneous texture descriptor consists of the mean, the standard deviation value of an image, energy, and energy deviation values of Fourier transform of the image. These are extracted from partitioned frequency channels based on the human visual system (HVS). For reliable extraction of the texture descriptor, Radon transformation is employed. This is suitable for HVS behavior. We also introduce various matching methods; for example, intensity-invariant, rotation-invariant and/or scale-invariant matching. This technique retrieves relevant texture images when the user gives a querying texture image. In order to show the promising performance of the texture descriptor, we take the experimental results with the MPEG-7 test sets. Experimental results show that the MPEG-7 texture descriptor gives an efficient and effective retrieval rate. Furthermore, it gives fast feature extraction time for constructing the texture descriptor.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.170-178
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• 2019

This paper proposes a parking space detection method for autonomous parking by using the Around View Monitor (AVM) image and Light Detection and Ranging (LIDAR) sensor fusion. This method consists of removing obstacles except for the parking line, detecting the parking line, and template matching method to detect the parking space location information in the parking lot. In order to remove the obstacles, we correct and converge LIDAR information considering the distortion phenomenon in AVM image. Based on the assumption that the obstacles are removed, the line filter that reflects the thickness of the parking line and the improved radon transformation are applied to detect the parking line clearly. The parking space location information is detected by applying template matching with the modified parking space template and the detected parking lines are used to return location information of parking space. Finally, we propose a novel parking space detection system that returns relative distance and relative angle from the current vehicle to the parking space.