کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
525841 | 869030 | 2010 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Accelerated hardware video object segmentation: From foreground detection to connected components labelling Accelerated hardware video object segmentation: From foreground detection to connected components labelling](/preview/png/525841.png)
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.
Journal: Computer Vision and Image Understanding - Volume 114, Issue 11, November 2010, Pages 1282–1291