• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.107-109
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• 2004

In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile information. The proposed system focuses on improving recognition performance of 3D object. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse these informations. Tactual signals are obtained from the reaction force by the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of teaming iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though visual information has a defect. The experimental results show that the proposed system can improve recognition rate and reduce learning time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme of 3D object.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.811-816
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• 2016

In light of recently developed 3D printers for rapid prototyping, there is increasing attention on the 3D scanner as a 3D data acquisition system for an existing object. This paper presents a prototypical 3D scanner based on a striped laser light image. In order to solve the problem of shadowy areas, the proposed 3D scanner has two cameras with one laser light source. By using a horizontal rotation table and a rotational arm rotating about the latitudinal axis, the scanner is able to scan in all directions. To remove an additional optical filter for laser light pixel extraction of an image, we have adopted a differential image method with laser light modulation. Experimental results show that the scanner's 3D data acquisition performance exhibited less than 0.2 mm of measurement error. Therefore, this scanner has proven that it is possible to reconstruct an object's 3D surface from point cloud data using a 3D scanner, enabling reproduction of the object using a commercially available 3D printer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1659-1665
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• 2009

In this paper, we propose an implementation method of 3D image correlator using integral imaging technique. In the proposed method, elemental images of the reference and signal 3D objects are recorded by lenslet arrays and then reference and signal output plane images with high resolution are optically reconstructed on the output plane by displaying these elemental images into a display panel. Through cross-correlations between the reconstructed reference and the single plane images, 3D object recognition is performed. The proposed method can provide a precise 3D object recognition by using the high-resolution output plane images compared with the previous methods and implement all-optical structure for real-time 3D object recognition system. To show the feasibility of the proposed method, optical experiments are carried out and the results are presented.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.400-410
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• 2012

In recent years, 3D displays are used in many media including 3D movies, TV, mobile phones, and PC games. Although 3D displays provide realistic viewing experience as compared with 2D displays, they also carry issues such as visual fatigue or size distortion. Focusing on the latter, we developed prediction function of object size perception as a function of object depth in 3D display. In Experiment 1, subjects observed 3D square of a fixed size of varying depth, and manipulated 2D square to make it as large as the 3D square. Conversely, in Experiment 2, subjects observed 2D square of a fixed size, and manipulated 3D square of varying depth to make it as large as the 2D square. In both Experiments 1 and 2, we found that size perception of 3D square linearly changed depending on depth of the square, and the linear relationship between depth and size was identical in both experiments. The predictive regression function, which predicts object size perception based on object depth, obtained in this research will be very useful in the creation of 3D media contents.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.555-563
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• 2011

In this paper, we propose an object based 2D image to 3D conversion algorithm by using motion estimation, color labeling and non-local mean filtering methods. In the proposed algorithm, we first extract the motion vector of each object by estimating the motion between frames and then segment a given image frame with color labeling method. Then, combining the results of motion estimation and color labeling, we extract object regions and assign an exact depth value to each object to generate the right image. While generating the right image, occlusion regions occur but they are effectively recovered by using non-local mean filter. Through the experimental results, it is shown that the proposed algorithm performs much better than conventional conversion scheme by removing the eye fatigue effectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.9
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• pp.727-738
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• 1991

This paper presents a new approach to explicityly use surface normal images (SNIs) in 3-D object model description and recognition procedure. The surface normal images of an object are defined as the projected images obtained from view angles facing normal to each surface of the object. The proposed approach can significantly alleviate the difficulty of obtaining correspondence between models and scene objects by explicitly providing a transform for the matching. The proposed approach is applied to the construction of a model-based 3-D object recognition system for the selected five objects. Synthetic images are used in the experiment to show the operation of the overall recognition system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.108-113
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• 2008

Virtual construction (VC) system enables project manager to visually check mistakes in design materials by using virtual reality technology. In using VC system, to make 3D object by each construction element is still tedious work. This study suggests an improved method to make 3D object by using parameter-based 3D generation function. The IDEFO model to organize the process for the function. A VC system by this function was developed in this study and the function was verified by a bridge project in this system.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.69-72
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• 1991

This paper proposes an efficient algorithm that constructs 3 dimensional solid object from orthographic views. The 3D object construction algorithm inputs vertices and edges information of 3 orthogonal views, generates 2 dimensional surfaces of input views, 3 dimensional possible vertices, possible edges and possible surfaces, compares 2 dimensional projections of 3 dimensional possible surface with two dimensional surfaces from orthogonal views and then determines the solution. This algorithm has been proved to be efficient in reducing the time taken and is useful for CAD system, 3 dimensional scene analysis system and object modellings for 3D graphics. The algorithm has been implemented in C language on the IBM PC/AT.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.26-34
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• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• Current Optics and Photonics
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• v.6 no.6
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• pp.598-607
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• 2022

In this paper, a simple nondestructive technology is used to investigate unstained biological blood cells in three dimensions (3D). The technology employs a reflective phase-only spatial light modulator (SLM) for displaying the phase hologram of the object being tested, and a Fourier lens for its reconstruction. The phase hologram is generated via superposing a digital random phase on the 2D image of the object. The phase hologram is then displayed by the SLM with 256 grayscale levels, and reconstructed by a Fourier lens to present the object in 3D. Since noise is the main problem in this method, the windowed Fourier filtering (WFF) method is applied to suppress the noise of the reconstructed object. The quality of the reconstructed object is refined and the noise level suppressed by approximately 40%. The technique is applied to objects: the National Institute of Standards (NIS) logo, and a film of unstained peripheral blood. Experimental results show that the proposed technique can be used for rapid investigation of unstained biological blood cells in 3D for disease diagnosis. Moreover, it can be used for viewing unstained white blood cells, which is still challenging with an optical microscope, even at large magnification.