• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.11-21
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• 2011

This study intends to construct scenic byway database and to examine and suggest social experiment of scenic byway. As basis work for the experiment of the scenic byway, we build database by using ITS standard node link management system. The DB includes scenic byway routes of Korea and Japan. The analyses show that the scenic byway in both nations consists of roads, reservation, road sign, vehicle number plate, and it was found that infrastructure and system are inadequate for scenic byway. These experiment can be effectively used for scenic byway in Korea and Japan as the basis data. The results of this experiment will be useful for plan and develop a scenic byway.

• Journal of The Korean Association of Information Education
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• v.8 no.4
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• pp.489-500
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• 2004

In this paper, an investigation on internet safety of 244 national or public elementary schools' web sites was performed with two points of view : inappropriate material posting and personal information exposure. The investigation results showed that obscene materials and commercial advertisements were uploaded into the bulletin board(67.2%) and students' personal information such as photograph, address, telephone number were exposed(87.3%). Most of the inappropriate materials were posted by auto-register programs. This problem was occurred due to reckless bulletin board opening and inappropriate management. On the contrary, personal information was exposed by teachers and students. They didn't not care about their personal information. It shows the fact that they have not recognized the danger of personal information exposure. Therefore managing real-name membership and enforcing permission to bulletin board were required to construct and use a safe school web site. Teachers have to understand not only negative effects appeared in a school web site but also latent dangerous factors.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.268-277
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• 2016

IoT (Internet of Things) technologies have largely contributed to our smart living environment. The smart parking system is one of the prominent services that IoT supports. To identify the parked vehicles, the previous parking system use special identifying devices, the RFID tags carried by the users, and the high quality camera to recognize the vehicle license numbers. However, the previous methods cause cost inefficiency and unfriendly usages. To address these problems, we propose a smart parking system based on ultrasonic sensors and Bluetooth communication. The proposed system decides the available slots by using the sensor motes located in the parking spaces. Also it recognizes the location of the parked vehicle using Bluetooth RSSI between a Smartphone and the sensor motes. In addition, based on these converging technologies, it can support the parked routes of vehicles for users. To evaluate the implemented smart parking system, we applied the RSSI transform equations and the recognition rate for parked vehicles. As a result, the accurate rate of transformed distances could be measured.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.406-412
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• 2001

In this paper, a new fuzzy single layer learning algorithm is proposed, which shows improved learning time and convergence property than that of the conventional fuzzy single layer perceptron algorithms. First, we investigate the structure of physiological neurons of the nervous system and propose new neuron structures based on fuzzy logic. And by using the proposed fuzzy neuron structures, the model and learning algorithm of Physiological Fuzzy Single Layer Perceptron(P-FSLP) are proposed. For the evaluation of performance of the P-FSLP algorithm, we applied the conventional fuzzy single layer perceptron algorithms and the P-FSLP algorithm to three experiments including Exclusive OR problem, the 3-bit parity bit problem and the recognition of car licence plates, which is an application of image recognition, and evaluated the performance of the algorithms. The experimentation results showed that the proposed P-FSLP algorithm reduces the possibility of local minima more than the conventional fuzzy single layer perceptrons do, and enhances the time and convergence for learning. Furthermore, we found that the P-FSLP algorithm has the great capability for image recognition applications.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.490-495
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• 1999

In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron structure. This method is applied to the XOR Problem, n bit parity problem which is used as the benchmark in neural network structure, and recognition of digit image in the vehicle plate image for practical image application. As a result of the experiments, it does not always guarantee the convergence. However, the network showed improved the teaming time and has the high convergence rate. The proposed network can be extended to an arbitrary layer Though a single layer structure Is considered, the proposed method has a capability of high speed 3earning even on large images.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1531-1540
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• 2016

In this paper, we propose vehicle license plate recognition system based on Radial Basis Function Neural Networks (RBFNNs) with the use of local binarization functions and canny edge algorithm. In order to detect the area of license plate and also recognize license plate numbers, binary images are generated by using local binarization methods, which consider local brightness, and canny edge detection. The generated binary images provide information related to the size and the position of license plate. Additionally, image warping is used to compensate the distortion of images obtained from the side. After extracting license plate numbers, the dimensionality of number images is reduced through Principal Component Analysis (PCA) and is used as input variables to RBFNNs. Particle Swarm Optimization (PSO) algorithm is used to optimize a number of essential parameters needed to improve the accuracy of RBFNNs. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. Image data sets are obtained by changing the distance between stationary vehicle and camera and then used to evaluate the performance of the proposed system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.142-149
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• 2016

This paper proposes a method to detect LP(License Plate) of vehicles in indoor and outdoor parking lots. In restricted environment, there are many conventional methods for detecting LP. But, it is difficult to detect LP in natural and complex scenes with background clutters because several patterns similar with text or LP always exist in complicated backgrounds. To verify the performance of LP text detection in natural images, we apply MB-LGP feature by combining with ensemble machine learning algorithm in purpose of selecting optimal features of small number in huge pool. The feature selection is performed by adaptive boosting algorithm that shows great performance in minimum false positive detection ratio and in computing time when combined with cascade approach. MSER is used to provide initial text regions of vehicle LP. Throughout the experiment using real images, the proposed method functions robustly extracting LP in natural scene as well as the controlled environment.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.511-519
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• 1997

This paper presents the automatic recognition algorithm of the license number in on vehicle image. The proposed algorithm uses the correlation coefficient and Hough transform to detect license plate. The m/n ratio reduction is performed to save time and memory. By the correlation coefficient between the standard pattern and the target pattern, licence plate area is roughly extracted. On the extracted local area, preprocessing and binarization is performed. The Hough transform is applied to find the extract outline of the plate. If the detection fails, a smaller or a larger standard pattern is used to compute the correlation coefficient. Through this process, the license plate of different size can be extracted. Two algorithms to each separate number are proposed. One segments each number with projection-histogram, and the other segments each number with the label. After each character is separated, it is recognized by the neural network. This research overlomes the problems in conventional methods, such as the time requirement or failure in extraction of outlines which are due to the processing of the entire image, and by processing in real time, the practical application is possible.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.42-51
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• 2009

Korean government is managing a system that appoints various type of cars into lanes based on the number of lanes. The institution has been abolished and enacted time and again. This paper analyzes ten sections of express way to clarify the efficiencies of the system. The result shows that violation rate and the number of accident have a positive correlation. This paper suggests regulation of violating cars and controlment by perceiving car registration number for efficient operation of the institution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1167-1174
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• 2006

Text region detection from a natural scene is useful in many applications such as vehicle license plate recognition. Therefore, in this paper, we propose a text region extraction method using pattern histogram of character-edge maps. We create 16 kinds of edge maps from the extracted edges and then, we create the 8 kinds of edge maps which compound 16 kinds of edge maps, and have a character feature. We extract a candidate of text regions using the 8 kinds of character-edge maps. The verification about candidate of text region used pattern histogram of character-edge maps and structural features of text region. Experimental results show that the proposed method extracts a text regions composed of complex background, various font sizes and font colors effectively.