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Shape Recognition Based on Projected Edges and Global Statistical Features
Joint Authors
Stubendek, Attila
Karacs, Kristóf
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-19
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
A combined shape descriptor for object recognition is presented, along with an offline and online learning method.
The descriptor is composed of a local edge-based part and global statistical features.
We also propose a two-level, nearest neighborhood type multiclass classification method, in which classes are bounded, defining an inherent rejection region.
In the first stage, global features are used to filter model instances, in contrast to the second stage, in which the projected edge-based features are compared.
Our experimental results show that the combination of independent features leads to increased recognition robustness and speed.
The core algorithms map easily to cellular architectures or dedicated VLSI hardware.
American Psychological Association (APA)
Stubendek, Attila& Karacs, Kristóf. 2018. Shape Recognition Based on Projected Edges and Global Statistical Features. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1207679
Modern Language Association (MLA)
Stubendek, Attila& Karacs, Kristóf. Shape Recognition Based on Projected Edges and Global Statistical Features. Mathematical Problems in Engineering No. 2018 (2018), pp.1-18.
https://search.emarefa.net/detail/BIM-1207679
American Medical Association (AMA)
Stubendek, Attila& Karacs, Kristóf. Shape Recognition Based on Projected Edges and Global Statistical Features. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1207679
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207679