• ICROS
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• v.2 no.6
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• pp.21-29
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• 1996

본 논문의 구성은 2장에서는 밝기 분포로부터의 형상복구(Shape from shading)의 한 방법인 고전적인 Photometric stereo mehtod에 대해서 개략적으로 고찰해 보고 3장, 4장에서는 혼성반사모델(Hybrid reflectance model)을 기반으로 하는 2종류의 확장된 Photometric stereo 방법에 대해 설명하고, 각 경우에 대한 시뮬레이션 결과를 2.5차원 및 3차원 형상으로 보이고 고찰한다. 5장에서는 결론 및 고찰에 대해서 언급하고 논문을 마친다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.285-286
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• 2016

본 논문에서는 3D 콘테츠와 이를 가공하기 위한 기술로, 한 물체에 여러 방향으로 빛이 주어진 사진들을 이용하여 해당 물체의 3D shape를 재현해 낼 수 있는 Photometric Stereo에 대해 구현 및 테스트해 보고, 1개의 카메라를 사용하여 3D 콘텐츠를 구현해 낼수 있는 방안들에 대하여 살펴 본다.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.2
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• pp.111-119
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• 2013

This paper proposes one method on photometric stereo calibration using the constraint on light source directions in which the light sources have the unknown tilt and slant angles but the slant angles are the same. First, the constraint is analyzed based on the equation of linear ambiguity which leads to the conclusion that another constraint should be added to solve the calibration completely. Later, the combination of constraint on light source directions and the constraint that there exists at least six surface patches having known albedos is exploited to resolve the linear ambiguity up to an accurate and close-form solution. The effective performance of the proposed method is demonstrated through experiment results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.27-34
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• 2011

In this paper, we propose an active 3D shape acquisition method based on photometric stereo using camera and flash on a smartphone. Two smartphones are used as the master and slave, in which the slave projects illumination from different locations while the master captures the images and processes photometric stereo algorithm to reconstruct 3D shape. In order to reduce the error, the smartphone's camera is calibrated to overcome the effect of the lens distortion and nonlinear camera sensor response. We apply 5-point algorithm to estimate the pose between smartphone cameras and then estimate lighting direction vector to run the photometric stereo algorithm. Experimental result shows that the proposed system enables us to use smartphone as a 3D camera with low cost and high quality.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.459-464
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• 2015

An on-line quality control of hot steel products is one of the important issues in the steel industry because of cost minimization. In recent years, relative depth information of surface defects is increasingly required for strict quality control. In this paper, a 3D shape reconstruction scheme for defects on a hot steel surface based on a multi-spectral photometric stereo method is proposed. After simultaneously illuminating a hot steel surface by using vertical/horizontal linearly polarized lights of green and blue light sources, the corresponding 4 images are obtained. The photometric stereo method is then applied with the aid of a GPU (Graphic Processing Unit) to reconstruct the shape of the target surface based on these images. The proposed scheme was validated through experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1061-1066
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• 2013

In the steel industry, the detection of tiny defects including its 3D characteristics on steel surfaces is very important from the point of view of quality control. A multi-spectral photometric stereo method is an attractive scheme because the shape of the defect can be obtained based on the images which are acquired at the same time by using a multi-channel camera. Moreover, the calculation time required for this scheme can be greatly reduced for real-time application with the aid of a GPU (Graphic Processing Unit). Although a more reliable shape reconstruction of defects can be possible when the numbers of available images are increased, it is not an easy task to construct a camera system which has more than 3 channels in the visible light range. In this paper, a new 6-channel camera system, which can distinguish the vertical/horizontal linearly polarized lights of RGB light sources, was developed by adopting two 3-CCD cameras and two polarized lenses based on the fact that the polarized light is preserved on the steel surface. The photometric stereo scheme with 6 images was accelerated by using a GPU, and the performance of the proposed system was validated through experiments.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.53-62
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• 1994

This paper presents a new approach of analyzing errors resulting from nonideal general-purpose lighting environment when the Photometric Stereo Method (PSM) is applied to estimate the surface-orientation of a three-dimensional object. The approach introduces the explicit modeling of the lighting environment including a circular-disk type irradiance object plane and the direct simulation of the error distribution with the model. The light source is modeled as a point source that has a certain amount of beam angle, and the luminance distribution on the irradiance plane is modeled as a Gaussian function with different deviation values. A simulation algorithm is devised to estimate the light source orientation computing the average luminance intensities obtained from the irradiance object planes positioned in three different orientations. The effect of the nonideal lighting model is directly reflected in such simulation, because of the analogy between the PSM and the proposed algorithm. With an instrumental tool designed to provide arbitrary orientations of the object plane at the origin of the coordinate system, experiment can be performed in a systematic way for the error analysis and compensation. Simulations are performed to find out the error distribution by widely varying the light model and the orientation set of the object plane. The simulation results are compared with those of the experiment performed in the same way as the simulation. It is confirmed from the experiment that a fair amount of errors is due to the erroneous effect of the general-purpose lighting environment.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.816-820
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• 1990

This paper is pre-stage for getting EGI which can be used for modeling of an object. It discusses the construction of the vision processing system and its algorithm for getting needle diagram from tie object image. We realize the algorithm with monocular camera system, using Reflectance Map theory and photometric stereo method. We can calculate the surface normal at any point in the image if we take multiple images at the different lighting conditions. From the 3 images taken from different lighting conditions through the experiment, we get the needle diagrams of the sphere and the object. We confirm the validness of the surface, normal acquisition algorithm comparing the experimental needle diagram with the ideal one obtained from the surface normal of the known object.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1132-1140
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• 1997

In many vision tasks of the major obstacles is the specular highkight of smoth objects, which causes a misinterpretation of objects.This paper presents an dffcient algorithm for highight detection and object reconstruction, blsed on the theory of photometric stereo in which the location of highilight changes as the position of illumination source changes.Two images, referred to as base image and reference image.are sequentially taken with two different positionhs of the two images.The difference image is thresholded to detct the specular spike of the highlight.Then the specu-lar lobe around the specular spike is detected to reconstruct the object.The proposed algorithm can be applied to metals and dielectrics, regardlless of the surface chracteristics.This method can also be aplied to the case when the background is brighter than the object.

• Journal of Korea Multimedia Society
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• v.1 no.1
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• pp.26-36
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• 1998

It is very important study field in computer vision 'How we obtain 3D information from 2D image'. For this purpose, we must know position of camera, direction of light source, and surface reflectance property before we take the image, which are intrinsic information of the object in the scene. Among them, surface reflectance property presents very important clues. Most previous researches assume that objects have only Lambertian reflectance, but many real world objects have Non-Lambertian reflectance property. In this paper the new method for analyzing the properties of surface reflectance and reconstructing the shape of object through estimation of reflectance parameters is proposed. We have interest in Non-Lambertian reflectance surface that has specular reflection and diffuse reflection which can be explained by Torrance-Sparrow model. Photometric matching method proposed in this paper is robust method because it match reference image and object image considering the neighbor brightness distribution. Also in this thesis, the neural network based shaped reconstruction method is proposed, which can be performed in the absence of reflectance information. When brightness obtained by each light is inputted, neural network is trained by surface normal and can determine the surface shape of object.