DocumentCode :
2158042
Title :
Noise reduction to enhance classification of images using textural information
Author :
Harron, Wilson ; Dony, Robert ; Miller, Stephen
Author_Institution :
Sch. of Eng., Univ. of Guelph, Guelph, ON
fYear :
2009
fDate :
3-6 May 2009
Firstpage :
243
Lastpage :
246
Abstract :
A method is presented to classify the percent intramuscular fat (%IMF) for beef cattle using ultrasound imaging. As the images captured tend to include a significant amount of noise a noise reduction algorithm was used. The effectiveness of using filtered images to calculate texture measures for the classification and prediction of the %IMF is compared to the effectiveness of using unfiltered images.
Keywords :
agricultural products; filtering theory; image classification; image texture; ultrasonic imaging; beef cattle; image classification; image filtering; noise reduction; percent intramuscular fat; textural information; ultrasound imaging; Animals; Cows; Discrete wavelet transforms; Kernel; Low-frequency noise; Muscles; Noise reduction; Ultrasonic imaging; Ultrasonic variables measurement; Wiener filter; texture measures; ultrasound imaging; wiener filtering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2009. CCECE '09. Canadian Conference on
Conference_Location :
St. John´s, NL
ISSN :
0840-7789
Print_ISBN :
978-1-4244-3509-8
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2009.5090129
Filename :
5090129
Link To Document :
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