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Accelerated Image Processing in Hardware

Alexander Bochem

Published by LAP Lambert Academic Publishing
ISBN 10: 3848410575 / ISBN 13: 9783848410576
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Title: Accelerated Image Processing in Hardware

Publisher: LAP Lambert Academic Publishing

Binding: Paperback

Book Condition: New

Book Type: Paperback

Description:

Paperback. 116 pages. Dimensions: 8.7in. x 5.9in. x 0.3in.This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783848410576

About this title:

Synopsis: This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision.

About the Author: M.Sc. Autonomous Systems 2010Bonn-Rhein-Sieg University of Applied SciencesSankt Augustin, Nordrhein-Westfalen, GermanyM.Sc. Computer Science 2010University of New Brunswick, Faculty of Computer ScienceFredericton, New Brunswick, Canada

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