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ASME Press Select Proceedings
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Editor
ISBN-10:
0791802655
No. of Pages:
650
Publisher:
ASME Press
Publication date:
2007
eBook Chapter
82 Adaptive Grayscale Morphological Operators for Image Analysis
By
Z. Cheng
Dept. of Soil & Atmospheric Sci. University of Missouri Columbia, MO 65211
,
Z. Cheng
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S. H. Anderson
Dept. of Soil & Atmospheric Sci. University of Missouri Columbia, MO 65211
S. H. Anderson
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Page Count:
6
-
Published:2007
Citation
Cheng, Z, & Anderson, SH. "Adaptive Grayscale Morphological Operators for Image Analysis." Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17. Ed. Dagli, CH. ASME Press, 2007.
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Grayscale morphological operators are often used for image structure analysis. Normally these operators use the maximum (dilation) or minimum (erosion) of nearest neighbor values. This study introduces the use of an adaptive structural element for use as a grayscale morphological operator in image analysis. The structural element introduces changes with grayscale pixel value. Simple and more complex synthetic sets are presented along with their dilation and erosion analyses. This adaptive operator permits calculation of the image surface area with changing resolution. The surface area is estimated from the adaptive operator through dilation or erosion with differencing of constructed images. Results...
Abstract
Introduction
I. Mathematical Definitions of Signatures
II. Procedures to Estimate Signatures Using Image Processing
Conclusions
References
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