The effect of rainfall on feature points extraction and image stitching
Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Health, Engineering and Science
School
School of Engineering
RAS ID
19210
Abstract
The aim of this paper is to investigate the effects of rainfall on image stitching by measuring the performance of the Harris corner detector, Scale-Invariant Feature Transform (SIFT) detector, and the Speeded Up Robust Feature (SURF) detector. A set of images were captured by using two cameras during light rain and during heavy rain. The number of detected features points was used as the performance measure. The results indicate that all the detectors are capable to extract a substantial amount of feature points. However, the rainfall does reduce the number of detected feature points by 48 and 67% when the Harris corner detector and the SURF detector were adopted respectively. At the end, the images were stitched together based on the feature points extracted by using the Harris corner detector. The results indicate that the effect of rainfall is negligible as long as there is a substantial amount of distinctive feature points.
DOI
10.1109/InfoSEEE.2014.6946146
Access Rights
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Comments
Chia W.C., Yeong L.S., Ch'Ng S.I., Seng K.P., & Ang L.-M. (2014). The effect of rainfall on feature points extraction and image stitching. ISEEE 2014 - Proceedings: 2014 International Conference on Information Science, Electronics and Electrical Engineering. (pp. 1382-1386). Sapporo, Japan. IEEE . © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. .. Available here