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Efficient Trademark Retrieval Using Weighted Image Features

Madeena Sultana

Published by VDM Verlag
ISBN 10: 3639375696 / ISBN 13: 9783639375695
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Title: Efficient Trademark Retrieval Using Weighted...

Publisher: VDM Verlag

Binding: Paperback

Book Condition: New

Book Type: Paperback

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Paperback. 76 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.Large image databases find diverse applications in real-life situations. It is essential to develop an efficient technique to grasp required information from these databases. Fast retrieval and robustness are two main criteria for efficient recognition of an object using image databases. Keeping this in mind, the present research work describes a hybrid method using a weighted combination of multiple image features mainly color histogram, distance, and moment parameters for trademark recognition. The computational power is accelerated by employing a low cost NVIDIAs Compute Unified Device Architecture (CUDA) enabled GPU. Our experimental results show that this new technique provides more robust performance than either of the individual methods and our GPU implementation requires less than 50 of the CPU computation time. This experimentation demonstrates that the method based on multiple weighted images features with cooperative implementation between the CPU and GPU is an effective way of image retrieval from large databases. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783639375695

About this title:

Synopsis: Large image databases find diverse applications in real-life situations. It is essential to develop an efficient technique to grasp required information from these databases. Fast retrieval and robustness are two main criteria for efficient recognition of an object using image databases. Keeping this in mind, the present research work describes a hybrid method using a weighted combination of multiple image features mainly color histogram, distance, and moment parameters for trademark recognition. The computational power is accelerated by employing a low cost NVIDIA's Compute Unified Device Architecture (CUDA) enabled GPU. Our experimental results show that this new technique provides more robust performance than either of the individual methods and our GPU implementation requires less than 50% of the CPU computation time. This experimentation demonstrates that the method based on multiple weighted images features with cooperative implementation between the CPU and GPU is an effective way of image retrieval from large databases.

About the Author: Madeena Sultana: Received her M.S. and B.Sc. in Computer Science and Engineering(CSE) from Jahangirnagar University, Bangladesh in 2011 and 2008, respectively. She is a faculty member at the Dept. of CSE in the University of Liberal Arts Bangladesh. Mohammad Shorif Uddin, PhD: Professor, Dept. of CSE, Jahangirnagar University, Bangladesh.

Madeena Sultana: Received her M.S. and B.Sc. in Computer Science and Engineering(CSE) from Jahangirnagar University, Bangladesh in 2011 and 2008, respectively. She is a faculty member at the Dept. of CSE in the University of Liberal Arts Bangladesh. Mohammad Shorif Uddin, PhD: Professor, Dept. of CSE, Jahangirnagar University, Bangladesh.

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