• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.313-315
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• 2011

Smart phone camera module are mounted on the focus are 2 types depending on the behavior. AF (Auto focus) camera module and the FF (Fixed focus) camera module two are different types. AF camera module to move the location of the lens and is a way to automatically focus, FF camera module lens position of the focus is the way to a fixed state. EDOF camera module the location of the lens as a frozen state EDOF AF module using the algorithm to focus on applied technology is a module. In this paper, optimization EDOF camera module implementation of the resolution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.429-430
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• 2012

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.245-259
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• 2010

We have developed mathematically precise image-processing algorithms for extracting panoramic images from fisheye images. Furthermore, we have successfully built a DSP-based panoramic camera employing single fisheye lens.

• ETRI Journal
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• v.31 no.6
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• pp.695-702
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• 2009

We propose a lens-drive unit composed of an ionic polymer-metal composite (IPMC) for an auto-focus compact camera module in cellular phones to solve the power consumption problem of voice coil motors which are widely used in commercial products. In this research, an IPMC incorporated into a lens-drive unit is designed to implement a large displacement in low-power consumption by using an anisotropic plasma treatment. Experimental results show that a camera module containing IPMCs can control and maintain the position of the lens by using proportional integral derivative control with a photo-reflective position sensor despite the non-linear actuation behavior of IPMCs. We demonstrate that the fabrication and commercialization of a lens actuator that has a large displacement and low power consumption using IPMCs is possible in the near future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.250-255
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• 2003

The position of a 3-dimensional(3D) point can be measured by using calibrated stereo camera. To obtain more accurate measurement ,more accurate camera calibration is required. There are many existing methods to calibrate camera. The simple linear methods are usually not accurate due to nonlinear lens distortion. The nonlinear methods are accurate more than linear method, but it increase computational cost and good initial guess is needed. The multi step methods need to know some camera parameters of used camera. Recent years, these explicit model based camera calibration work with the development of more precise camera models involving correction of lens distortion. But these explicit model based camera calibration have disadvantages. So implicit camera calibration methods have been derived. One of the popular implicit camera calibration method is to use neural network. In this paper, we propose implicit stereo camera calibration method for 3D reconstruction using support vector machine. SVM can learn the relationship between 3D coordinate and image coordinate, and it shows the robust property with the presence of noise and lens distortion, results of simulation are shown in section 4.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.989-992
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• 2005

This paper is about the assembly of camera modules for mobile phones. We have particularly researched the assembly process proper for mega-pixel lens assemblies in the camera modules. Herein, we propose that self-adjustment function makes it possible to assemble these lens assemblies without fraction of components. In advance, we observed the assembly process of the lens assemblies to verify the possibility, and checked out it through experiments based on some assumptions.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.596-601
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• 2000

In a robot/vision system, the vision sensor, typically a CCD array sensor, is mounted on the robot hand. The problem of determining the relationship between the camera frame and the robot hand frame is refered to as the hand-eye calibration. In the literature, various methods have been suggested to calibrate camera and for sensor registration. Recently, one-step approach which combines camera calibration and sensor registration is suggested by Horaud & Dornaika. In this approach, camera extrinsic parameters are not need to be determined at all configurations of robot. In this paper, by modifying the camera model and including the lens distortion effect in the perspective transformation matrix, a new one-step approach is proposed in the hand-eye calibration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.267-277
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• 2019

Photogrammetry and computer vision are identical in determining the three-dimensional coordinates of images taken with a camera, but the two fields are not directly compatible with each other due to differences in camera lens distortion modeling methods and camera coordinate systems. In general, data processing of drone images is performed by bundle block adjustments using computer vision-based software, and then the plotting of the image is performed by photogrammetry-based software for mapping. In this case, we are faced with the problem of converting the model of camera lens distortions into the formula used in photogrammetry. Therefore, this study described the differences between the coordinate systems and lens distortion models used in photogrammetry and computer vision, and proposed a methodology for converting them. In order to verify the conversion formula of the camera lens distortion models, first, lens distortions were added to the virtual coordinates without lens distortions by using the computer vision-based lens distortion models. Then, the distortion coefficients were determined using photogrammetry-based lens distortion models, and the lens distortions were removed from the photo coordinates and compared with the virtual coordinates without the original distortions. The results showed that the root mean square distance was good within 0.5 pixels. In addition, epipolar images were generated to determine the accuracy by applying lens distortion coefficients for photogrammetry. The calculated root mean square error of y-parallax was found to be within 0.3 pixels.

• Journal of the Optical Society of Korea
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• v.18 no.1
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• pp.23-31
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• 2014

Recently, the number of camera companies that produce commercializing interchangeable lens systems such as digital single lens reflex (DSLR) and compact system camera (CSC) lenses has been gradually increasing. These interchangeable lenses have various kinds of lenses with distinct specifications. In particular, the distance window among these specifications is the function most preferred by customers. Mechanical manual zoom and manual focus in these high end camera lenses with a distance window are in particular desirable specifications and are required for product quality. However, the AF lens group is linked to the zoom cam and moves. Because the AF lens group moves along with the object distance, we can not realize the distance window with only zoom locus calculation. In this paper, in order to solve the problem, we suggest an optical calculation method for a corrected AF zoom cam for an interchangeable lens with a distance window to achieve product differentiation and analyze the error in the calculation.

• Journal of the Korea Computer Graphics Society
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• v.3 no.1
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• pp.9-15
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• 1997

Most rendering research has concentrated on two sub-problems: modeling the reflection of light sources, and calculating the direct and indirect illumination from light sources and other surfaces. As Kolb wrote in [1], the camera and lens model is an important key component of a rendering system. In this paper we describe a bump-mapping method using camera lens. It allows another level of control in rendering. We developed an efficient framework to develop customized bump mapping lens and combine with other sequence of lens elements to create various effects as shown in Figure 2,3,4,5.