• Journal of IKEEE
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• v.22 no.1
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• pp.68-73
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• 2018

In this paper, we propose an efficient algorithm for mapping a $360^{\circ}$ circular image to a planar image. The proposed algorithm consists of obtaining size of the planar image, calculating the distance between the camera and the planar image, calculating horizontal angle of camera and planar image, calculating vertical angle between camera and planar image, calculating the position of a pixel that matches pixels in a $360^{\circ}$ circular image to pixels in a planar image. Experiments were performed to evaluate the efficient algorithm for mapping the proposed $360^{\circ}$ circular image to the plane image. The reconstruction rate of the mapped plane image was confirmed 99% and the image quality of the mapped plane image was confirmed 72%. Since the results were higher than the standard values of commercial software, the effectiveness of the algorithm was confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4405-4418
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• 2016

Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.804-809
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• 2004

It is essential to calibrate a camera in order to recover 3-dimensional reconstruction from uncalibrated images. This paper proposes a new technique of the camera calibration using a homography between the planar patterns image taken by the camera, which is located at the three planar patterns image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented more easily and simply to recover 3D object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate the examples of 3D reconstruction using the proposed algorithm from image sequence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3842-3855
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• 2018

A novel image completion method is proposed that uses the advantage of planar structural information to fill corrupted portions of an image. First, in estimating parameters of the projection plane, the image is divided into several planes, and their planar structural information is analyzed. Second, in calculating the a priori probability of patch and patch offset regularity, this information is converted into a constraint condition to guide the process of filling the hole. Experimental results show that the proposed algorithm is fast and effective, and ensures the structure continuity of the damaged region and smoothness of the texture.

• Current Optics and Photonics
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• v.3 no.4
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• pp.329-335
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• 2019

Wide FOV imaging systems are important for acquiring rich visual information. A conventional catadioptric imaging system deploys a camera in front of a curved mirror to acquire a wide FOV image. This is a cumbersome setup and causes unnecessary occlusions in the acquired image. In order to reduce both the burden of the camera deployment and the occlusions in the images, this study uses a secondary planar mirror in the catadioptric imaging system. A compact design of the catadioptric imaging system and a condition for the position of the secondary planar mirror to satisfy the central imaging are presented. The image acquisition model of the catadioptric imaging system with a secondary planar mirror is discussed based on the principles of geometric optics in this study. As a backward mapping, the acquired image is restored to a distortion-free image in the experiments.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.120-127
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• 2003

A novel three degrees of freedom sensing method utilizing binary grid pattern image and vision camera is presented. The binary grid pattern image is designed by Pseudo-Random Binary Arrays and referenced to encode in-plane position of a moving stage of the contact-free planar actuator. First, the yaw motion of the stage is detected using fast image processing and then the other planar positions, x and y, are decoded with a sequence of images. This method can be applied to the system that needs feedback of in-plane position, with advantages of a good accuracy and high resolution comparable with the encoder, a relatively compact structure, no friction, and a low cost. In this paper, all the procedures of the above sensing mechanism are described in detail, including simulation and experiment results.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.153-164
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• 2017

In spherical panoramic images, SURF, a feature description method for planar patterns, does not work correctly due to heavy spherical distortion. Since a plane pattern is distorted in a spherical image, the pattern search and replacement in a spherical panoramic image should be treated differently from the case of the planar image. This paper proposes a planar texture replacement method, which transforms a spherical panoramic image into a cubemap panoramic image, searches a pattern using SURF, replaces a plane pattern, and then converts it into a spherical panoramic image.

• Journal of KIISE
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• v.42 no.10
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• pp.1185-1194
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• 2015

A spherical panoramic image does not conform to the pin-hole camera model, and, hence, it is not possible to utilize previous techniques consisting of plane-to-plane transformation. In this paper, we propose a new method to estimate the planar geometric transformation between the planar image and a spherical panoramic image. Our proposed method estimates the transformation parameters for latitude, longitude, rotation and scaling factors when the matching pairs between a spherical panoramic image and a planar image are given. A planar image is projected into a spherical panoramic image through two steps of nonlinear coordinate transformations, which makes it difficult to compute the geometric transformation. The advantage of using our method is that we can uncover each of the implicit factors as well as the overall transformation. The experiment results show that our proposed method can achieve estimation errors of around 1% and is not affected by deformation factors, such as the latitude and rotation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1758-1763
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• 1991

This paper describes a new method to determine the 3D-shape of objects consisting of specular planar surfaces. This method exploits a light source which is made of a diffuse plane with a grid pattern encoded in an M-sequence and uses a single image of the light source reflected by the objects to acquiring orientations and positions of the surfaces of the objects. When grid lines of the light source are reflected by a specular planar surface and perspectively projected on an image plane, a set of lines vanishing at a point are obtained on the image plane. The orientation of the specular planar surface is determined by using the vanishing point, and the position is determined by using the correspondence between lines on the image and lines on the light source, which is obtained by employing a characteristic regularity of the M-sequence. Before the vanishing points are calculated, the lines on the image are classified and correlated with the surfaces of objects by using slopes and positions of the lines and the regularity of the M-sequence. This method requires only a single image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.381-390
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• 2006

This paper proposes a new technque of the camera calibration to be computed a homography between the planar patterns taken by a single image to be located at the three planar patterns from uncalibrated images. It is essential to calibrate a camera for 3-dimensional reconstruction from uncalibrated image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented to more easily and simply to recover 3D reconstruction of an object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate examples of recovering 3D reconstruction using the proposed algorithm from uncalibrated images.