• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.395-401
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• 2020

In this paper, a motion-based ROI extraction algorithm from a high resolution fisheye image is proposed for multi-view monitoring systems. Lately fisheye cameras are widely used because of the wide angle-of-view and they basically provide a lens correction functionality as well as various viewing modes. However, since the distortion-free angle of conventional algorithms is quite narrow due to the severe distortion ratio, there are lots of unintentional dead areas and they require much computation time in finding undistorted coordinates. Thus, the proposed algorithm adopts an image decimation and a motion detection methods, that can extract the undistorted ROI image with a standard angle-of-view for the fast and intelligent surveillance system. In addition, a mesh-type ROI is presented to reduce the lens correction time, so that this independent ROI scheme can parallelize and maximize the processor's utilization.

• Journal of Sensor Science and Technology
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• v.14 no.4
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• pp.278-285
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• 2005

This paper describes techniques of camera calibration and artificial landmarks detection for the automatic charging of a mobile robot, equipped with a fish-eye camera in the direction of its operation for movement or surveillance purposes. For its identification from the surrounding environments, three landmarks employed with infrared LEDs, were installed at the charging station. When the robot reaches a certain point, a signal is sent to the LEDs for activation, which allows the robot to easily detect the landmarks using its vision camera. To eliminate the effects of the outside light interference during the process, a difference image was generated by comparing the two images taken when the LEDs are on and off respectively. A fish-eye lens was used for the vision camera of the robot but the wide-angle lens resulted in a significant image distortion. The radial lens distortion was corrected after linear perspective projection transformation based on the pin-hole model. In the experiment, the designed system showed sensing accuracy of ${\pm}10$ mm in position and ${\pm}1^{\circ}$ in orientation at the distance of 550 mm.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.634-640
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• 2015

This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.560-566
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• 2005

In this paper, a practical technique for correction of a distorted image for vision-based localization of ubiquitous mobile robot. The localization of mobile robot is essential and is realized by using camera vision system. In order to wide the view angle of camera, the vision system includes a fish-eye lens, which distorts the image. Because a mobile robot moves rapidly, the image processing should he fast to recognize the localization. Thus, we propose the practical correction technique for a distorted image, verify the Performance by experimental test.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.96-110
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• 2017

Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.89-99
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• 2016

One of the fundamental elements in developing mixed reality applications is to effectively analyze and apply the environmental lighting information to image synthesis. In particular, interactive applications require to process dynamically varying lighting sources in real-time, reflecting them properly in rendering results. Previous related works are not often appropriate for this because they are usually designed to synthesize photorealistic images, generating too many, often exponentially increasing, light sources or having too heavy a computational complexity. In this paper, we present a fast light source estimation technique that aims to search for primary light sources on the fly from a sequence of video images taken by a camera equipped with a fisheye lens. In contrast to previous methods, our technique can adust the number of found light sources approximately to the size that a user specifies. Thus, it can be effectively used in Phong-illumination-model-based direct illumination or soft shadow generation through light sampling over area lights.

• Journal of Korea Game Society
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• v.6 no.2
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• pp.45-50
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• 2006

In order to generate a photo-realistic synthesized image, we should reconstruct light environment by 3D analysis of scene. This paper presents a novel method for identifying the positions and characteristics of the lights-the global and local lights-in the real image, which are used to illuminate the synthetic objects. First, we generate High Dynamic Range(HDR) radiance map from omni-directional images taken by a digital camera with a fisheye lens. Then, the positions of the camera and light sources in the scene are identified automatically from the correspondences between images without a priori camera calibration. Types of the light sources are classified according to whether they illuminate the whole scene, and then we reconstruct 3D illumination environment. Experimental results showed that the proposed method with distributed ray tracing makes it possible to achieve photo-realistic image synthesis. It is expected that animators and lighting experts for the film and animation industry would benefit highly from it.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.543-548
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• 2017

$360^{\circ}$panoramic image can give people an unprecedented visual experience, and there are many different ways to make a $360^{\circ}$panoramic image. In this paper, we will introduce two easy and effective methods from those many ways. The first one is through 48 photos to make a $360^{\circ}$panoramic image, the second way is through 6 photos to make a $360^{\circ}$panoramic image. We will compare those methods and tell the audience which one suits themselves. Through those easy design methods introduced above, we can see VR works design became easy and popular, normal people can also make $360^{\circ}$panoramic image, and it promotes the industry of VR image contents.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.35-44
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• 2007

Since the omnidirectional camera system with a very large field of view could take many information about environment scene from few images, various researches for calibration and 3D reconstruction using omnidirectional image have been presented actively. Most of line segments of man-made objects we projected to the contours by using the omnidirectional camera model. Therefore, the corresponding contours among images sequences would be useful for computing the camera transformations including rotation and translation. This paper presents a novel two step minimization method to estimate the extrinsic parameters of the camera from the corresponding contours. In the first step, coarse camera parameters are estimated by minimizing an angular error function between epipolar planes and back-projected vectors from each corresponding point. Then we can compute the final parameters minimizing a distance error of the projected contours and the actual contours. Simulation results on the synthetic and real images demonstrated that our algorithm can achieve precise contour matching and camera motion estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.125-132
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• 2008

Omnidirectional camera system with a wide view angle is widely used in surveillance and robotics areas. In general, most of previous studies on estimating a projection model and the extrinsic parameters from the omnidirectional images assume corresponding points previously established among views. This paper presents a novel omnidirectional camera calibration based on automatic contour matching. In the first place, we estimate the initial parameters including translation and rotations by using the epipolar constraint from the matched feature points. After choosing the interested points adjacent to more than two contours, we establish a precise correspondence among the connected contours by using the initial parameters and the active matching windows. The extrinsic parameters of the omnidirectional camera are estimated minimizing the angular errors of the epipolar plane of endpoints and the inverse projected 3D vectors. Experimental results on synthetic and real images demonstrate that the proposed algorithm obtains more precise camera parameters than the previous method.