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DC Field | Value | Language |
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dc.contributor.author | Appiah, K | - |
dc.contributor.author | Hunter, A | - |
dc.contributor.author | Dickinson, P | - |
dc.contributor.author | Meng, H | - |
dc.date.accessioned | 2011-11-22T11:08:13Z | - |
dc.date.available | 2011-11-22T11:08:13Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Computer Vision and Image Understanding, 114(11): 1282-1291, Nov 2010 | en_US |
dc.identifier.issn | 1077-3142 | - |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6WCX-4YX002K-2/2/340a3e3970a577f22787ba65a36e341d | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/6008 | - |
dc.description | This is the preprint version of the Article - Copyright @ 2010 Elsevier | en_US |
dc.description.abstract | This paper demonstrates the use of a single-chip FPGA for the segmentation of moving objects in a video sequence. The system maintains highly accurate background models, and integrates the detection of foreground pixels with the labelling of objects using a connected components algorithm. The background models are based on 24-bit RGB values and 8-bit gray scale intensity values. A multimodal background differencing algorithm is presented, using a single FPGA chip and four blocks of RAM. The real-time connected component labelling algorithm, also designed for FPGA implementation, run-length encodes the output of the background subtraction, and performs connected component analysis on this representation. The run-length encoding, together with other parts of the algorithm, is performed in parallel; sequential operations are minimized as the number of run-lengths are typically less than the number of pixels. The two algorithms are pipelined together for maximum efficiency. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Background differencing | en_US |
dc.subject | Image segmentation | en_US |
dc.subject | Connected component labelling | en_US |
dc.subject | Object extraction | en_US |
dc.subject | FPGA | en_US |
dc.title | Accelerated hardware video object segmentation: From foreground detection to connected components labelling | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.cviu.2010.03.021 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel (Active) | - |
pubs.organisational-data | /Brunel/Brunel (Active)/School of Engineering & Design | - |
Appears in Collections: | Electronic and Electrical Engineering Publications Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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Appiah2010CVIUAcceleratedHardwareObjectExtraction.pdf | 579.3 kB | Adobe PDF | View/Open |
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