• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.410-414
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• 2013

In this paper, we propose a 3D display method combining a pickup process using axially recorded multiple images and an integral imaging display process. First, we extract the color and depth information of 3D objects for displaying 3D images from axially recorded multiple 2D images. Next, using the extracted depth map and color images, elemental images are computationally synthesized based on a ray mapping model between 3D space and an elemental image plane. Finally, we display 3D images optically by an integral imaging system with a lenslet array. To show the usefulness of the proposed system, we carry out optical experiments for 3D objects and present the experimental results.

• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.746-749
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• 2003

Alignment of 2D-gel images of biological samples can visualize the difference of expression profiles and also inform us candidates of protein spots to be further analyzed. However, comparison of two proteome images between case and control does not always successfully identify differentially expressed proteins due to sample-to-sample variation. Because of poor reproducibility of 2D-gel electrophoresis, sample-by-sample variations and inconsistent electrophoresis conditions, multiple number of 2D-gel image must be processed to align each other to visualize the difference of expression profiles and to deduce the protein spots differentially expressed with reliability. Alignment of multiple 2D-Gel images and their clustering were carried out by applying various algorithms and statistical methods. In order to align multiple images, multiresolution-multilevel algorithm was found out to be suitable for fast alignment and for distorted images. Clustering of 12 different images implementing a k-means algorithm gives a phylogenetic tree of distance map of the proteomes. Microsoft Visual C++ was used to implement the algorithms in this work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2251-2259
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• 2009

We propose an algorithm and system which generates 3D stereo image by composition of 2D image from 4 multiple clusters which 1 cluster was composed of 4 multiple cameras based on network. Proposed Schemes have a network-based client-server architecture for load balancing of system caused to process a large amounts of data with real-time as well as multiple cluster environments. In addition, we make use of JPEG compression and RAM disk method for better performance. Our scheme first converts input images from 4 channel, 16 cameras to binary image. And then we generate 3D stereo images after applying edge detection algorithm such as Sobel algorithm and Prewiit algorithm used to get disparities from images of 16 multiple cameras. With respect of performance results, the proposed scheme takes about 0.05 sec. to transfer image from client to server as well as 0.84 to generate 3D stereo images after composing 2D images from 16 multiple cameras. We finally confirm that our scheme is efficient to generate 3D stereo images in multiple view and multiple clusters environments with real-time.

• Journal of the Korean Society of Costume
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• v.53 no.5
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• pp.1-12
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• 2003

This paper proposes a system for measuring the 3D human bodies using the multiple 2D images. The system establishes the multiple image input circumstance from the digital camera for image measurement. The algorithm considering perspective projection leads us to estimate the 3D human bodies from the multiple 2D images such as frontal. side and rear views. The results of the image measurement is compared those of the direct measurement and the 3D scanner for the total 40 items (12 heights, 15 widths and 13 depths). Three persons measure the 40 items using the three measurement methods. In comparison of the results obtained among the measurement methods and the persons, the results between the image measurement and the 3D scanner are very similar. However, the errors for the direct measurement are relatively larger than those between the image measurement and the 3D scanner. For example, the maximum errors between the image measurement and the 3D scanner are 0.41cm in height, 0.39cm in width and 0.95cm in depth. The errors are acceptable in body measurement. Performance of the image measurement is superior to the direct. because the algorithm estimates the 3D positions using the perspective projection. In above comparison, the image measurement is expected as a new method for measuring the 3D body, since it has the various advantages of the direct measurement and 3D scanner in performance for measurement as well as in the devices, cost, Portability and man power.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Journal of the Optical Society of Korea
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• v.12 no.2
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• pp.98-102
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• 2008

Optical Coherence Tomography (OCT) is an important noninvasive medical imaging technique that can reveal subsurface structures of biological tissue. OCT has demonstrated a good correlation with histology in sufficient resolution to identify morphological changes in articular cartilage to differentiate normal through progressive stages of degenerative joint disease. Current OCT systems provide individual cross-sectional images that are representative of the tissue directly under the scanning beam, but they may not fully demonstrate the degree of degeneration occurring within a region of a joint surface. For a full understanding of the nature and degree of cartilage degeneration within a joint, multiple OCT images must be obtained and an overall assessment of the joint surmised from multiple individual images. This study presents frequency domain three-dimensional (3-D) OCT imaging of degenerative joint cartilage extracted from bovine knees. The 3-D OCT imaging of articular cartilage enables the assembly of 126 individual, adjacent, rapid scanned OCT images into a full 3-D image representation of the tissue scanned, or these may be viewed in a progression of successive individual two-dimensional (2-D) OCT images arranged in 3-D orientation. A fiber-based frequency domain OCT system that provides cross-sectional images was used to acquire 126 successive adjacent images for a sample volume of $6{\times}3.2{\times}2.5\;mm^3$. The axial resolution was $8\;{\mu}m$ in air. The 3-D OCT was able to demonstrate surface topography and subsurface disruption of articular cartilage consistent with the gross image as well as with histological cross-sections of the specimen. The 3-D OCT volumetric imaging of articular cartilage provides an enhanced appreciation and better understanding of regional degenerative joint disease than may be realized by individual 2-D OCT sectional images.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.285-292
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• 2000

A new method for the 3D automatic registration of the multiple range images has been developed for the 3D scanners(non-contact coordinates measurement systems). In the existing methods, the user usually has to input more than 3 pairs of corresponding points for the iterative registration process. The major difficulty of the existing systems lies in that the input corresponding points must be selected very carefully because the optimal searching process and the registration results mostly depend upon the accuracy of the selected points. In the proposed method, this kind of difficulty is greatly mitigated even though it needs only 2 pairs of the corresponding input points. Several registration examples on the 3D measured data have been presented and discussed with the introduction to the proposed algorithm.

• KSBB Journal
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• v.20 no.2 s.91
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• pp.71-75
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• 2005

Alignment of 2D-gel images of biological samples can visualize the difference of expression profiles and also inform us candidates of protein spots to be further analyzed. However, comparison of two proteome images between the case and control does not always successfully identify differentially expressed proteins because of sample-to-sample variation, poor reproducibility of 2D-gel electrophoresis and inconsistent electrophoresis conditions. Multiple alignment of 2D-gel image must be preceded before visualizing the difference of expression profiles or clustering proteome images. Thus, a software for the alignment of multiple 2D-Gel images and their clustering was developed by applying various algorithms and statistical methods. Microsoft Visual C++ was used to implement the algorithms in this work. Multiresoultion-multilevel algorithm was found out to be suitable for fast alignment and for largely distorted images. Clustering of 10 different proteome images of Fetal Alcohol Syndrome, was carried out by implementing a k-means algorithm and it gave a phylogenetic tree of proteomic distance map of the samples. However, the phylogenetic tree does not discriminate the case and control. The whole image clustering shows that the proteomic distance is more dependent to age and sex.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1205-1212
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• 2014

In this paper, we propose a high-quality stitching method of 3D multiple dental CT images. First, a weighted function is generated using the difference of two distance functions that calculate a distance from the nearest edge of an overlapped region to each position. And a blending ratio propagation function for two gradient vectors is parameterized by the difference and magnitude of gradient vectors that is also applied by the weighted function. When the blending ratio is propagated, an improved region growing scheme is proposed to decide the next position and calculate the blending intensity. The proposed method produces a high-quality stitching image. Our method removes the seam artifact caused by the mean intensity difference between images and vignetting effect. And it removes double edges caused by local misalignment. Experimental results showed that the proposed method produced high-quality stitching images for ten patients. Our stitching method could be usefully applied into the stitching of 3D or 2D multiple images.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.78-82
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• 2007

This paper propose a building reconstruction method of urban area for a 3D GIS with stereo images. The 3D reconstruction is performed by the grouping 3D line segments extracted from the stereo matching of salient edges which are derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.