• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1718-1721
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• 1997

An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. to recognize the type of cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the simularity mehod is used to recognize the numbers on plates.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1113-1118
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• 2002

In recognition system of the car license plate, the most important is to extract the image of the license plate from a car image. In this paper, we use ACL (Adaptive Color Luminance) algorithm to extract the license plate image from a car image. The ACL algorithm that uses color and luminance information of a car image is used to extract the image of the license plate. In this paper, color, luminance and other related information of a car image are used to extract the image of the license plate from that of a car. In this reason, we call it the ACL algorithm. The ACL algorithm uses color, luminance information and other related information of a license plate. These informations are avaliable to exact the image of the license plate. The rate of extracting the image of the license plate from a car is 97%. The experimental result of the ACL algorithm for the character region is 92%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.423-426
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• 1995

An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. To recognize the type af cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the similarity method is used to recognize the numbers on the plates.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.415-421
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• 1997

A car driving trainer for beginners developed under PC-based environment is described in this paper. For this trainer, a hardware is implemented as a practice car, and a trainer program is designed by computer image generation method to display 3-dimensional images on a CRT monitor. The trainer program consists of 3 main parts, that is, a speed estimate part, a wheel trace calculation part and a driving image generation part. Furthermore, a map editor is also installed for taking any test drive. After comparing this driving trainer to specify it was verified that the developed car driving trainer showed has good performances, such as lower cost, higher resolution and better image display speed.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.303-312
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• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.76-86
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• 1999

In this paper, it is shown that the car number plate are segmented and extracted more efficiently by using wavelet transform. A car image is decomposed by wavelet transform, and the high frequency image of the decomposed image are selected as feature images. Three selected feature images are synthesized of a single feature image, and a region including the plate is segmented by the correlation coefficient between the feature image and the synthesized image. For segmented plate region, the car plate region is extracted by deciding the Y-axis region composed by vertical region, the car plate region is extracted by deciding the Y-axis region composed by vertical histogram and the X-axis region composed by the variance histogram. Some experiment results of the various image and shown. It has been shown from the results with the high rate of 96% that the car number plates can be segmented and extracted more extractly and efficiently than converntional method.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.356-367
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• 2011

In this paper, we proposed a new car engine sealing inspection system based on image processing and understanding. The car engine sealing inspection plays very important role for protecting leakage caused by inappropriate sealing, which is a crucial point for productivity of car engines. The proposed inspection system has been aimed to enhance the previously proposed sealing inspection systems based on image processing, which have high computation complexity and low performance for correctly inspecting some contamination by oil with similar color with that of sealing. Moreover, the previously proposed system has a difficulty in installing the camera system on the sealing machine. The proposed system considers a difference of images before and after sealing obtained from one static camera. By utilizing a difference of images, the proposed system shows very robust performance using a proposed simple depth checking algorithm for some contamination cases by oil with similar color with that of sealing and the total inspection system is simple and cheap to implement. According to the experiments conducted in a real car product line, the proposed inspection system shows better inspection performance and needs smaller implementation cost than three other previously proposed system working in current car sealing inspection systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1527-1540
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• 2004

In this paper, velocity measurement of fast moving object for traffic information acquisition using line sampling of image is proposed. Velocity measurement for traffic information acquisition of moving object is that the first sample line and second sample line on the road is set, then car is detected by using difference image method between time-variance hue data of image when car is passing two sample lines and hue data of the reference image, and velocity of the car is measured by using frame number of video which is occupied by two sample lines. Identification of the car is performed by hue of the detected car between the first sample line and second sample line, respectively To examine the propriety of the proposed algorithm, identification and velocity measurement for driving car is evaluated. The evaluated results is that it is identified by hue data of car passing two sample lines, and the velocity measurement for driving car is less than 3% comparing with X-band speed gun.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.447-451
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• 2011

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purposes such as CAN and MOST. Especially, the MOST network is usually adapted to provide entertainment service. The car navigation system is also widely used for guiding driving paths to driver. The position for the navigation system is usually acquired by GPS technology. However, the GPS technique has two serious problems. The first is unavailability in urban canyons. The second is inherent positional error rate. The problems have been studied in many literatures. However, the second still leads to incorrect locational information in some area, especially parallel roads. This paper proposes a performance tuning method of image matching algorithm for the car navigation system. The method utilizes images obtained from in-vehicle MOST network and a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. In order to accuracy improvement of image matching algorithm, three conditions are applied. The experimental tests show that the proposed system increases the accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.1-10
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• 2016

In this paper, a car model recognition system using image processing and machine learning is proposed and it's performance is also evaluated. The system recognizes the front of car because the front of car is different for every car model and manufacturer, and difficult to remodel. The proposed method extracts HOG features from training data set, then builds classification model by the HOG features. If user takes photo of the front of car, then HOG features are extracted from the photo image and are used to determine the model of car based on the trained classification model. Experimental results show a high average recognition rate of 98%.