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Object Extraction in Cluttered Environments via a P300-Based IFCE
Mao, Xiaoqian; Li W(李伟); He, Huidong; Xian, Bin; Zeng, Ming; Zhou, Huihui; Niu, Linwei; Chen, Genshe
Department水下机器人研究室
Source PublicationCOMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
ISSN1687-5265
2017
Volume2017Pages:1-12
Indexed BySCI ; EI
EI Accession number20172903943598
WOS IDWOS:000405282900001
Contribution Rank2
Funding OrganizationNational Natural Science Foundation of China [61473207] ; CAS Hundred Talent Program, Shenzhen [JCYJ20151030140325151, KQTD20140630180249366]
AbstractOne of the fundamental issues for robot navigation is to extract an object of interest from an image. The biggest challenges for extracting objects of interest are how to use a machine to model the objects in which a human is interested and extract them quickly and reliably under varying illumination conditions. This article develops a novel method for segmenting an object of interest in a cluttered environment by combining a P300-based brain computer interface (BCI) and an improved fuzzy color extractor (IFCE). The induced P300 potential identifies the corresponding region of interest and obtains the target of interest for the IFCE. The classification results not only represent the human mind but also deliver the associated seed pixel and fuzzy parameters to extract the specific objects in which the human is interested. Then, the IFCE is used to extract the corresponding objects. The results show that the IFCE delivers better performance than the BP network or the traditional FCE. The use of a P300-based IFCE provides a reliable solution for assisting a computer in identifying an object of interest within images taken under varying illumination intensities.
Language英语
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS SubjectMathematical & Computational Biology ; Neurosciences
WOS KeywordIMAGE SEGMENTATION ; RECOGNITION
WOS Research AreaMathematical & Computational Biology ; Neurosciences & Neurology
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20800
Collection水下机器人研究室
Corresponding AuthorLi W(李伟)
Affiliation1.School of Electrical Engineering and Automation, Tianjin University, Tianjin, 300072, China
2.Department of Computer and Electrical Engineering and Computer Science, California State University, Bakersfield, CA, 93311, United States
3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Shenyang, Liaoning, 110016, China
4.Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
5.Department of Math and Computer Science, West Virginia State University, 5000 Fairlawn Ave, WV, 25112, United States
6.Intelligent Fusion Technology Inc., Germantown, MD, 20876, United States
Recommended Citation
GB/T 7714
Mao, Xiaoqian,Li W,He, Huidong,et al. Object Extraction in Cluttered Environments via a P300-Based IFCE[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2017,2017:1-12.
APA Mao, Xiaoqian.,Li W.,He, Huidong.,Xian, Bin.,Zeng, Ming.,...&Chen, Genshe.(2017).Object Extraction in Cluttered Environments via a P300-Based IFCE.COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2017,1-12.
MLA Mao, Xiaoqian,et al."Object Extraction in Cluttered Environments via a P300-Based IFCE".COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2017(2017):1-12.
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