NDLI: Image measures for segmentation algorithm evaluation of automatic target recognition system

Content Provider	IEEE Xplore Digital Library
Author	Min Li Gui Lin Zhang
Copyright Year	2006
Description	Author affiliation: Inst. of Pattern Recognition & Artificial Intelligence, Huazhong Univ. of Sci. & Technol., Wuhan (Min Li; Gui Lin Zhang)
Abstract	Image measure is a very important part of automatic target recognition algorithm performance evaluation. Whether the image measure accurately relates with algorithm performance will affect directly evaluations. In this paper current image measures are introduced, and the deficiency of the target to background contrast (TBC) measure is analyzed, which is the best single measure and the representative of current general measures. A new texture-based image clutter measure (TIC) is derived from gray level cooccurrence (GLC) matrices, which embody important texture information. The result of testing two measures TBC and TIC shows that the relation between TBC and segmentation algorithm performance is monotonic rising in given scenario condition, but in complex condition it will fail, and that in both conditions TIC has very good monotonic relation with the segmentation algorithm performance. TIC is a fairly robust indicator of segmentation algorithm performance and better suited than TBC
Starting Page	6
Ending Page	679
File Size	6185571
Page Count	674
File Format	PDF
ISBN	0780393953
DOI	10.1109/ISSCAA.2006.1627424
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Image segmentation Histograms Image analysis Target recognition Image databases Current measurement System performance Robustness Performance analysis
Content Type	Text
Resource Type	Article

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