Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems
In this paper, feature extraction based on data-wave is proposed. The concept of data-wave is introduced to describe the rising and falling trends of the data over the long-term which are detected based on ripple and wave filters. Supported by data-wave, a novel symbol identifier with significant st...
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2012-12-01
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/54930 |
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doaj-35c0b321c49549cbac32e51829bc50872020-11-25T03:24:08ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142012-12-01910.5772/5493010.5772_54930Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot SystemsXilong Liu0Hanbo Qian1Zhiqiang Cao2Chao Zhou3Yuequan Yang4Min Tan5 State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China The Center of Coordination & Support of SASTIND, Beijing, China State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China College of Information Engineering, Yangzhou University, Yangzhou, China State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, ChinaIn this paper, feature extraction based on data-wave is proposed. The concept of data-wave is introduced to describe the rising and falling trends of the data over the long-term which are detected based on ripple and wave filters. Supported by data-wave, a novel symbol identifier with significant structure features is designed and these features are extracted by constructing pixel chains. On this basis, the corresponding recognition and positioning approach is presented. The effectiveness of the proposed approach is verified by experiments.https://doi.org/10.5772/54930 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xilong Liu Hanbo Qian Zhiqiang Cao Chao Zhou Yuequan Yang Min Tan |
spellingShingle |
Xilong Liu Hanbo Qian Zhiqiang Cao Chao Zhou Yuequan Yang Min Tan Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems International Journal of Advanced Robotic Systems |
author_facet |
Xilong Liu Hanbo Qian Zhiqiang Cao Chao Zhou Yuequan Yang Min Tan |
author_sort |
Xilong Liu |
title |
Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems |
title_short |
Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems |
title_full |
Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems |
title_fullStr |
Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems |
title_full_unstemmed |
Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems |
title_sort |
data-wave-based features extraction and its application in symbol identifier recognition and positioning suitable for multi-robot systems |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2012-12-01 |
description |
In this paper, feature extraction based on data-wave is proposed. The concept of data-wave is introduced to describe the rising and falling trends of the data over the long-term which are detected based on ripple and wave filters. Supported by data-wave, a novel symbol identifier with significant structure features is designed and these features are extracted by constructing pixel chains. On this basis, the corresponding recognition and positioning approach is presented. The effectiveness of the proposed approach is verified by experiments. |
url |
https://doi.org/10.5772/54930 |
work_keys_str_mv |
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1724603114510614528 |