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ANALYSIS OF VERY LARGE SCALE IMAGE DATA USING OUT-OF-CORE TECHNIQUE AND AUTOMATED 3D RECONSTRUCTION USING CALIBRATED IMAGES

Hassan Raju, Chandrashekara
http://rave.ohiolink.edu/etdc/view?acc_num=wright1189785164

Abstract Details

2007, Master of Science (MS), Wright State University, Computer Science.
Analysis of large scale volumetric data sets is very important from the researcher's and technological point of view as it helps in understanding and analyzing the original data. For example, when analyzing volumetric images from cast arteries of pigs, it is essential to apply a suitable segmentation in order to retrieve morphometric data from the scanned image. Due to improved scanning technology, such as MicroCT, these scanned images can get as large as several gigabytes in size. In order to analyze such large scale data sets on common desktop computers is a challenge due to limited main memory. By using out-of-core techniques, where the hard disk is used as main storage medium while the main memory serves as cache, it is possible to process any size data efficiently on a off-the-shelf PC with limited memory. Filters have been implemented and are applied to the original data to process and transform the original data into another form which can be further analyzed. The presented method is not limited in terms of data set size. The data set size that can be processed is only limited by the size of the hard disk. Hence, the novelty of the described technique is the ability to apply the implemented filters to data sets of almost unlimited size using common, off-the-shelf desktop computers. In the second part of the thesis work, an effort has been made to automate the 3-D reconstruction of bi-planar images using epipolar approach. The standard approach would be to find the matching features in both the images called corresponding points. Then, from such a correspondence, depth can be easily calculated using standard triangulation method. This type of classical method would require careful selection of the matching features. Here we propose a technique which does not involve selection of matching features which requires manual intervention thereby automating the process. This approach produces reasonable results for the calibrated images due to the projection.
Thomas Wischgoll (Advisor)
81 p.
Computer Science
Memory Mapping; Calibrated Images; Out-of-Core Technique; 3D Reconstruction

Recommended Citations

Citations

  • Hassan Raju, C. (2007). ANALYSIS OF VERY LARGE SCALE IMAGE DATA USING OUT-OF-CORE TECHNIQUE AND AUTOMATED 3D RECONSTRUCTION USING CALIBRATED IMAGES [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1189785164

    APA Style (7th edition)

  • Hassan Raju, Chandrashekara. ANALYSIS OF VERY LARGE SCALE IMAGE DATA USING OUT-OF-CORE TECHNIQUE AND AUTOMATED 3D RECONSTRUCTION USING CALIBRATED IMAGES. 2007. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1189785164.

    MLA Style (8th edition)

  • Hassan Raju, Chandrashekara. "ANALYSIS OF VERY LARGE SCALE IMAGE DATA USING OUT-OF-CORE TECHNIQUE AND AUTOMATED 3D RECONSTRUCTION USING CALIBRATED IMAGES." Master's thesis, Wright State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1189785164

    Chicago Manual of Style (17th edition)

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© 2007, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.