NDLI: Performance evaluation of feature detection in using subsampled images for image stitching

Content Provider	IEEE Xplore Digital Library
Author	Wai Chong Chia Li-Minn Ang Kah Phooi Seng
Copyright Year	2010
Description	Author affiliation: Department of Electrical and Electronic Engineering, The University of Nottingham Malaysia Campus, Jalan Broga, 43500, Semenyih, Selangor, Malaysia (Wai Chong Chia; Li-Minn Ang; Kah Phooi Seng)
Abstract	Image stitching is a technique being used to stitch multiple images together to form a stitched image with higher resolution and larger field of view. It has been adopted in many research areas such as computer vision and medical applications. The first step in stitching is to first determine the overlap region or similarity. This can be done using feature extraction, follow by comparing the feature points in the images. Once the similarity is determined, the images are transformed into the same coordinate system that agreed by each other. Finally, the images can be pasted together. In this paper, the performance of various type of feature detector in extracting feature points from the subsampled version of the original images will be evaluated. The advantage of using the subsampled images is to reduce the memory requirement, and processing time.
Starting Page	60
Ending Page	64
File Size	1444064
Page Count	5
File Format	PDF
ISBN	9781424455379
e-ISBN	9781424455409
DOI	10.1109/ICCSIT.2010.5564525
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature Detector Image resolution Feature Extraction Image Stitching World Wide Web Subsampled Image Mosaicing Radio access networks
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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