• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.191-197
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• 2007

Vision system is an object recognition system analyzing image information captured through camera. Vision system can be applied to various fields, and vehicle recognition is ole of them. There have been many proposals about algorithm of vehicle recognition. But have complex calculation processing. So they need long processing time and sometimes they make problems. In this research we suggested vehicle type recognition system using vision bpx based on embedded platform. As a result of testing this system achieves 100% rate of recognition at the optimal condition. But when condition is changed by lighting, noise and angle, rate of recognition is decreased as pattern score is lowered and recognition speed is slowed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2489-2496
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• 2014

The existing ship repair tool management system based on hand writing has many problems such as frequent loss of tool and overdue. To solve this problem, same systems have adopted the bar-code system. However, the systems can't cope with a problem to substitute spurious tool for genuine one on bar-code damage. Therefore, additional validation steps are necessary in order to manage expensive ship repair tool. In this paper, we propose an image comparison method for ship repair tool management. To be more concrete, we propose a normalization method and determination conditions for image comparison to use characteristics of mobile device. The normalization method makes use of the characteristics of mobile device that provides functions of real time recording, overlapping and cropping images. The proposed method applies three conditions(sum of inner angles, size of angle, position of corner coordinates) into the comparison module. The implemented system shows good performance on change direction, lighting, size and etc. The accuracy is more than 95%.

• Journal of Power System Engineering
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• v.15 no.1
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• pp.72-77
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• 2011

The handling ability of containers at the terminal strongly depends on the performance of the cargo handling system such as RTGC(Rubber Tired Gantry Crane). This paper introduces a new guide line position measurement method using a camera for the RTGC which plays a important role in the harbor area. Because the line tracking is the basic technique for control system design of RTGC, it is necessary to develop a useful and reliable measurement system. If the displacement and angle of the RTGC relative to a guide line as trajectory to follow is obtained, the position of RTGC is calculated. Therefore, in this paper, a camera-based measurement system is introduced. The proposed measurement system is robust against light fluctuation and cracks of the guideline. This system consists of a camera and a PC which are installed at the lower side of the RTGC. Two edges of the guide line are detected from an input image taken by the camera, and these positions are determined in a Hough parameter space by using the Hough transformation method. From the experimental results, high accurate standard deviations were found as 0.98 pixel of the displacement and 0.24 degree of the angle, including robustness against lighting fluctuation and cracks of the guide line also.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.116-120
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• 2012

There has been increased interest for building energy-saving for worldwide. There is continuing research on IT technology for efficient management of BEMS. Recently, It be able to control of LED and to maximize energy savings to the development of LED lighting technology. We propose the security image processing system to improve efficiency and we implement the real-time status monitoring system to surveil the object in the building energy management system. In this paper, we proposed the system of LED control using IP camera and Adaptive Gaussian Mixture Model for BEMS. We implement LED light control software on the based of the security camera image processing so the reliable controling based on the security camera is possible efficiently.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.598-608
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• 2020

In this paper, we propose a color correction technique for images acquired through a multi-view camera system for acquiring a 3D model. It is assumed that the 3D volume is captured indoors, and the position and intensity of the light is constant over time. 8 multi-view cameras are used, and converging toward the center of the space, so even if the lighting is constant, the intensity and angle of light entering each camera may be different. Therefore, a color optimization function is applied to a color correction chart taken from all cameras, and a color conversion matrix defining a relationship between the obtained 8 images is calculated. Using this, the images of all cameras are corrected based on the standard color correction chart. This paper proposed a color correction method to minimize the color difference between cameras when acquiring an image using 8 cameras of 3D objects, and experimentally proved that the color difference between images is reduced when it is restored to a 3D image.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.159-164
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• 2019

Detecting wildfire using only color in image information is a very difficult issue. This paper proposes an algorithm to detect forest fire area by analyzing color and motion of the area in the video including forest fire. The proposed algorithm removes the background region using the Gaussian Mixture based background segmentation algorithm, which does not depend on the lighting conditions. In addition, the RGB channel is changed to an HSV channel to extract flame candidates based on color. The extracted flame candidates judge that it is not a flame if the area moves while labeling and tracking. If the flame candidate areas extracted in this way are in the same position for more than 2 minutes, it is regarded as flame. Experimental results using the implemented algorithm confirmed the validity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.186-195
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• 2017

Recently, autonomous vehicles have been studied actively. There are various technologies such as ITS, Connected Car, V2X and ADAS in order to realize such autonomous driving. Among these technologies, it is particularly important to recognize where the vehicle is on the road in order to change the lane and drive to the destination. Generally, it is done through GPS and camera image processing. However, there are limitations on the reliability of the positioning due to shaded areas such as tunnels in the case of GPS, and there are limitations in recognition and positioning according to the state of the road lane and the surrounding environment when performing the camera image processing. In this paper, we propose that LED lights should be installed for autonomous vehicles in tunnels which are shaded area of the GPS. In this paper, we show that it is possible to measure the position of the current lane of the autonomous vehicle by analyzing the color temperature after constructing the tunnel LED lighting simulation environment which illuminates light of different color temperature by lane. Based on the above, this paper proposes a lane positioning technique using tunnel LED lights.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.53-62
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• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.117-126
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• 2010

In the case of failure images with controlling lighting like backlighting and excessive frontlinghting, the compensation scheme for a specific area in an image is required. The interested region is first selected by user in our method to compensate the first frame. Then we define the matching function of brightness and energy function is proposed with weight of matching function and the relationship among the neighbors. Finally, the energy is minimized by the graph-cut algorithm to compensate the brightness of the first frame. Other frames are straightforwardly compensated using the results of the first frame. The brightness variations of the previous frame is transmitted to the next frame via motion vectors. The reliability of the brightness variation is calculated based on the motion vector reliability. Video compensation result is achieved by the process of the image case. Simulation show that the proposed algorithm provides more natural results than the conventional algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.155-160
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• 2014

There are many image processing based algorithms and applications that fail when illumination change occurs. Therefore, the illumination change has to be detected then the illumination change occurred images need to be enhanced in order to keep the appropriate algorithm processing in a reality. In this paper, a new method for detecting illumination changes efficiently in a real time by using local region information and fuzzy logic is introduced. The effective way for detecting illumination changes in lighting area and the edge of the area was selected to analyze the mean and variance of the histogram of each area and to reflect the changing trends on previous frame's mean and variance for each area of the histogram. The ways are used as an input. The changes of mean and variance make different patterns w hen illumination change occurs. Fuzzy rules were defined based on the patterns of the input for detecting illumination changes. Proposed method was tested with different dataset through the evaluation metrics; in particular, the specificity, recall and precision showed high rates. An automatic parameter selection method was proposed for contrast limited adaptive histogram equalization method by using entropy of image through adaptive neural fuzzy inference system. The results showed that the contrast of images could be enhanced. The proposed algorithm is robust to detect global illumination change, and it is also computationally efficient in real applications.