NDLI: A new recognition and interpretation system of the blurred image

Content Provider	IEEE Xplore Digital Library
Author	Xu Zhiqian Yan Xiangzhen Yang Xiujuan
Copyright Year	2011
Description	Author affiliation: College of Pipeline and Civil Engineering, China University of Petroleum, Dongying, China (Yan Xiangzhen; Yang Xiujuan) \|\| College of Mechanical and Electronic Engineering, China University of Petroleum, Dongying, China (Xu Zhiqian)
Abstract	A new image recognition and interpretation system for the blurred image is proposed in this paper. Some important rules of complex moments for the blurred image are presented and proofed. The proposed system is composed of regional segmentation, image recognition and image interpretation process. As a pre-processing in the regional segmentation process, an input image is divided into some proper regions using techniques based on attention-driven approach. Fuzzy inference neural networks are employed in both the image recognition and the interpretation processes. The graphs under the blurring effect are presented. The experiment has shown that the proposed system can be successfully used in recognition of the blurred images.
Starting Page	958
Ending Page	961
File Size	337909
Page Count	4
File Format	PDF
ISBN	9781457702891
e-ISBN	9781457702907
DOI	10.1109/ICETCE.2011.5775932
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image recognition Regional segmentation FINN Face recognition Merging Image interpretation Humans Artificial neural networks Object recognition Blurred image
Content Type	Text
Resource Type	Article

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