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Object Recognition using Segmented Region and Multiple Features on Outdoor Environments

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4 Author(s)
Dae-Nyeon Kim ; Graduate Sch. of Electr. Eng., Ulsan Univ. ; Hyun-Deok Kang ; Taeho Kim ; Kang-Hyun Jo

This paper presents the method of region segmentation like six features, color, edge, straight line, geometric information, and template of tree color. The proposition of method segments region of image which is obtained by CCD camera mounted on the mobile robot. Moving robot takes database images on outdoor environment. We classify object to natural and artificial and then define their characteristics individually. In the process, we segment regions included objects by preprocessing. Objects can be recognized when we combine predefined multiple features. In addition, the feature of XCM (X co-occurrence matrix) detect region of tree, where X is information of arbitrary like intensity or hue. So the features use XCM as well as five features which we define. Our method is more effective than conventional region segmentation on outdoor environment because we present the method to combine various features in complex image. We achieved the result of region segmentation using multiple features through experiments.

Published in:

Strategic Technology, The 1st International Forum on

Date of Conference:

18-20 Oct. 2006