1,680 research outputs found
The 3-D image recognition based on fuzzy neural network technology
Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented
LSH-RANSAC: An Incremental Scheme for Scalable Localization
This paper addresses the problem of feature-
based robot localization in large-size environments. With recent
progress in SLAM techniques, it has become crucial for a robot
to estimate the self-position in real-time with respect to a large-
size map that can be incrementally build by other mapper
robots. Self-localization using large-size maps have been studied
in litelature, but most of them assume that a complete map
is given prior to the self-localization task. In this paper, we
present a novel scheme for robot localization as well as map
representation that can successfully work with large-size and
incremental maps. This work combines our two previous works
on incremental methods, iLSH and iRANSAC, for appearance-
based and position-based localization
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