NDLI: Combining color histogram and gradient orientation histogram for vision based global localization

Content Provider	IEEE Xplore Digital Library
Author	Hong Liu Xiaojia Yu Haitao Yu
Copyright Year	2009
Description	Author affiliation: Key Laboratory of Integrated Microsystem, Key Laboratory of Machine Perception and Intelligence, Shenzhen Graduate School, Peking University, China (Xiaojia Yu; Haitao Yu) \|\| Key Laboratory of Machine Perception and Intelligence, Key Laboratory of Integrated Microsystem, Shenzhen Graduate School, Peking University, China (Hong Liu)
Abstract	Global image features and local image features are comprehensively used in mobile robot's localization. In this paper, we proposed a geometric approach based on the combination of global image features. Considering the deficiency of the Weighted Gradient Orientation Histograms (WGOHs) for similar structure environments, color histograms are integrated as one vector for the localization. Besides the improving of weight and division for WGOH and color histogram, another weight for different emphasis on color and gradient orientation is carried out. A normalizing process is performed to better integrate the two global features. This combining approach is tested by means of locations recognition. Experimental results show that the proposed combining approach is efficient for indoor environments.
Starting Page	4043
Ending Page	4047
File Size	186127
Page Count	5
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346684
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Mobile robots Laboratories Machine intelligence Particle filters Motion planning Cybernetics USA Councils Intelligent robots Robot localization Global localization Color histogram WGOH
Content Type	Text
Resource Type	Article

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