Segmentation Assisted Object Distinction For Direct Volume Rendering
Ray casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a suff...
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| Format: | Thesis |
| Language: | English |
| Published: |
2013
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| Online Access: | http://eprints.usm.my/43239/ http://eprints.usm.my/43239/1/ARASH%20AZIM%20ZADEH%20IRANI24.pdf |
| _version_ | 1848879769970540544 |
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| author | Irani, Arash Azim Zadeh |
| author_facet | Irani, Arash Azim Zadeh |
| author_sort | Irani, Arash Azim Zadeh |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Ray casting is a direct volume rendering technique for visualizing 3D arrays
of sampled data. It has vital applications in medical and biological imaging.
Nevertheless, it is inherently open to cluttered classification results. It suffers from
overlapping transfer function values and lacks a sufficiently powerful voxel parsing
mechanism for object distinction. In this research work, we are proposing an image
processing based approach towards enhancing ray casting technique’s object
distinction process. The ray casting architecture is modified to accommodate object
membership information generated by a K-means based hybrid segmentation
algorithm. Object membership information is assigned to cubical vertices in the form
of ID tags. An intra-object buffer is devised and coordinated with inter-object buffer,
allowing the otherwise global rendering module to embed multiple local (secondary)
rendering processes. A local rendering process adds two advantageous aspects to
global rendering module. First, depth oriented manipulation of interpolation and
composition operations that lead to freedom of interpolation method choice based on
the number of available objects in various volumetric depths, improvement of LOD
(level of details) for desired objects and reduced number of required mathematical
computations. Second, localization of transfer function design that enables the
utilization of binary (non-overlapping) transfer functions for color and opacity
assignment. A set of image processing techniques are creatively employed in the
design of K-means based hybrid segmentation algorithm. |
| first_indexed | 2025-11-15T17:52:30Z |
| format | Thesis |
| id | usm-43239 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:52:30Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-432392019-04-12T05:26:13Z http://eprints.usm.my/43239/ Segmentation Assisted Object Distinction For Direct Volume Rendering Irani, Arash Azim Zadeh QA75.5-76.95 Electronic computers. Computer science Ray casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this research work, we are proposing an image processing based approach towards enhancing ray casting technique’s object distinction process. The ray casting architecture is modified to accommodate object membership information generated by a K-means based hybrid segmentation algorithm. Object membership information is assigned to cubical vertices in the form of ID tags. An intra-object buffer is devised and coordinated with inter-object buffer, allowing the otherwise global rendering module to embed multiple local (secondary) rendering processes. A local rendering process adds two advantageous aspects to global rendering module. First, depth oriented manipulation of interpolation and composition operations that lead to freedom of interpolation method choice based on the number of available objects in various volumetric depths, improvement of LOD (level of details) for desired objects and reduced number of required mathematical computations. Second, localization of transfer function design that enables the utilization of binary (non-overlapping) transfer functions for color and opacity assignment. A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm. 2013-06 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/43239/1/ARASH%20AZIM%20ZADEH%20IRANI24.pdf Irani, Arash Azim Zadeh (2013) Segmentation Assisted Object Distinction For Direct Volume Rendering. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Irani, Arash Azim Zadeh Segmentation Assisted Object Distinction For Direct Volume Rendering |
| title | Segmentation Assisted Object Distinction For Direct
Volume Rendering |
| title_full | Segmentation Assisted Object Distinction For Direct
Volume Rendering |
| title_fullStr | Segmentation Assisted Object Distinction For Direct
Volume Rendering |
| title_full_unstemmed | Segmentation Assisted Object Distinction For Direct
Volume Rendering |
| title_short | Segmentation Assisted Object Distinction For Direct
Volume Rendering |
| title_sort | segmentation assisted object distinction for direct
volume rendering |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/43239/ http://eprints.usm.my/43239/1/ARASH%20AZIM%20ZADEH%20IRANI24.pdf |