DocumentCode :
3223725
Title :
A new technique for color image segmentation
Author :
Amoroso, C. ; Ardizzone, E. ; Morreale, V. ; Storniolo, P.
Author_Institution :
Dipt. di Ingegneria Autom. e Inf., Palermo Univ., Italy
fYear :
1999
fDate :
1999
Firstpage :
352
Lastpage :
357
Abstract :
A novel technique for segmentation of color images is proposed. The technique implements a thresholding approach based on the analysis of the hue histogram; a new function for detecting valleys of the histogram has been devised and tested. A new blurring algorithm for noise reduction that works effectively when used over the hue image, has been also developed. A feedforward neural network that learns to recognize the hue ranges of meaningful objects completes the segmentation process. Experimental results show that the proposed technique is reliable and robust even in presence of changing environmental conditions. Extended experimentation has been carried within the framework of the Robot Soccer World Cup Initiative (RoboCup). The approach is fully general and may be successfully employed in any intermediate-level image-processing task, where the color is a meaningful descriptor
Keywords :
feedforward neural nets; image colour analysis; image recognition; image segmentation; learning (artificial intelligence); statistical analysis; RoboCup; Robot Soccer World Cup Initiative; blurring algorithm; color image segmentation; feedforward neural network; hue histogram analysis; hue range recognition; intermediate-level image processing; learning; meaningful objects; noise reduction; thresholding approach; valley detection; Data mining; Electrical capacitance tomography; Image analysis; Image color analysis; Image segmentation; Layout; Neural networks; Robot vision systems; Shape; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Processing, 1999. Proceedings. International Conference on
Conference_Location :
Venice
Print_ISBN :
0-7695-0040-4
Type :
conf
DOI :
10.1109/ICIAP.1999.797620
Filename :
797620
Link To Document :
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