DocumentCode
2426033
Title
VLSI Implementation of Fast Connected Component Labeling Using Finite State Machine Based Cell Network
Author
Roy, Pradipta ; Biswas, P.K.
Author_Institution
Optronics Centre, Integrated Test Range, Chandipur
fYear
2008
fDate
16-19 Dec. 2008
Firstpage
238
Lastpage
243
Abstract
Connected component labeling of a binary image is an indispensable task for image segmentation and analysis. For real time video object segmentation, total processing time to label all the objects of an entire image is critical as it is constrained by inter frame temporal difference. Parallel dedicated hardware is necessary to solve this problem in real time. In this paper we have proposed a parallel VLSI architecture for fast connected component labeling of a binary video frame image. We have adopted a seeded region-growing algorithm, which is implemented in a state machine based cell network. The design is verified in XILINX FPGA with real time video image data containing different objects with different shapes and sizes. The worst-case labeling time for a full video frame is 5 ms (using a 32 MHz clock), which is well below the required inter frame timing interval of 40 ms.
Keywords
VLSI; field programmable gate arrays; finite state machines; image segmentation; parallel machines; video signal processing; XILINX FPGA; binary video frame image; connected component labeling; finite state machine based cell network; image analysis; image segmentation; parallel VLSI architecture; parallel dedicated hardware; real time video object segmentation; seeded region-growing algorithm; Automata; Clocks; Field programmable gate arrays; Hardware; Image analysis; Image segmentation; Labeling; Object segmentation; Shape; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, Graphics & Image Processing, 2008. ICVGIP '08. Sixth Indian Conference on
Conference_Location
Bhubaneswar
Print_ISBN
978-0-7695-3476-3
Electronic_ISBN
978-0-7695-3476-3
Type
conf
DOI
10.1109/ICVGIP.2008.50
Filename
4756077
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