NDLI: Environment Understanding using Segmented Region by Multiple Features

Content Provider	IEEE Xplore Digital Library
Author	Dae-Nyeon Kim Kang-Hyun Jo
Copyright Year	2006
Description	Author affiliation: Graduate Sch. of Electr.-Electro. Inf. Syst. Eng., Ulsan Univ. (Dae-Nyeon Kim; Kang-Hyun Jo)
Abstract	Image segmentation is widely used as a preprocessing of image. We propose the method that segments and recognizes the region of image which is obtained by CCD camera mounted on the mobile robot. Region segmentation uses the image to be input in the outdoor environment when the robot travels. We use the features which contains color, line, edge, geometric information and template of color. We classify the object to segment and define as the characteristic which the object has. After, we segment the regions from the image previously defined as objects by those feature. In addition, we add two types of information such as intensity co-occurrence matrix (ICM) and hue co-occurrence matrix (HCM). We use ICM and HCM as well as those information previous descriptions. This method is more effective than conventional region segmentation in outdoor environment. We segment the region as mixture using the proposed features and methods. We achieved the result of efficient region segmentation using multiple features through the experiments implemented in our campus
Starting Page	2958
Ending Page	2963
File Size	6983204
Page Count	6
File Format	PDF
ISBN	8995003847
DOI	10.1109/SICE.2006.314961
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-18
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	The Institute of Control, Automation and Systems
Subject Keyword	Image segmentation Data mining Feature extraction Humans Frequency Information systems Systems engineering and theory Image recognition Charge coupled devices Robot vision systems Hue Co-occurrence Matrix (HCM) Region Segmentation Color Geometric Information Intensity Co-occurrence Matrix (ICM)
Content Type	Text
Resource Type	Article

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