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Proceedings Paper

Wavelet-based image analysis system for soil texture analysis
Author(s): Yun Sun; Zhiling Long; Ping-Rey Jang; M. John Plodinec
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Paper Abstract

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Paper Details

Date Published: 28 May 2003
PDF: 9 pages
Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); doi: 10.1117/12.477737
Show Author Affiliations
Yun Sun, Mississippi State Univ. (United States)
Zhiling Long, Mississippi State Univ. (United States)
Ping-Rey Jang, Mississippi State Univ. (United States)
M. John Plodinec, Mississippi State Univ. (United States)

Published in SPIE Proceedings Vol. 5014:
Image Processing: Algorithms and Systems II
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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