Pixel-level similarity fusion for image classification

Alex Pappachen James

doi:10.1109/SSD.2010.5585518

Pixel-level similarity fusion for image classification

Alex Pappachen James

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recent research shows that local similarity calculations play a significant role in improving the recognition performance of template matching systems. We present a new scheme for parametric similarity calculation and fusion for image classification. State-of-the-art recognition results are obtained using the proposed method for a difficult task involving face images.

Original language	English
Title of host publication	2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10
DOIs	https://doi.org/10.1109/SSD.2010.5585518
Publication status	Published - 2010
Event	2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10 - Amman, Jordan Duration: Jun 27 2010 → Jun 29 2010

Publication series

Name	2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10

Other

Other	2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10
Country	Jordan
City	Amman
Period	6/27/10 → 6/29/10

Keywords

Classification
Similarity
Template matching

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Control and Systems Engineering

Access to Document

10.1109/SSD.2010.5585518

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James, AP 2010, Pixel-level similarity fusion for image classification. in 2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10., 5585518, 2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10, 2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10, Amman, Jordan, 6/27/10. https://doi.org/10.1109/SSD.2010.5585518

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abstract = "Recent research shows that local similarity calculations play a significant role in improving the recognition performance of template matching systems. We present a new scheme for parametric similarity calculation and fusion for image classification. State-of-the-art recognition results are obtained using the proposed method for a difficult task involving face images.",

keywords = "Classification, Similarity, Template matching",

author = "James, {Alex Pappachen}",

note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; 2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10 ; Conference date: 27-06-2010 Through 29-06-2010",

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