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Haralick's Texture Features Computed by GPUs for Biological Applications
| Content Provider | Semantic Scholar |
|---|---|
| Author | Gipp, Markus Marcus, Guillermo Harder, Nathalie Suratanee, Apichat Rohr, Karl König, Rainer Männer, Reinhard |
| Copyright Year | 2009 |
| Abstract | This paper presents an approach to speedup the computation of co-occurrence matrices and Haralick texture features, as used for analyzing microscopy images of cells, by general-purpose graphics processing units (GPUs). The sequence of computation steps for the features is analyzed based on a graph and an optimized version of the software is derived. Afterwards, a massive parallel software version for GPUs is designed and implemented. On a single node of a cluster, a speedup of a factor of 360 was obtained compared to the original software version, and a speedup of a factor of 32 was achieved compared to the optimized software version. |
| Starting Page | 66 |
| Ending Page | 75 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| Volume Number | 36 |
| Alternate Webpage(s) | http://www.iaeng.org/IJCS/issues_v36/issue_1/IJCS_36_1_09.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |