Title :
The Classification Gradient
Author :
Kovalev, Vassili A. ; Petrou, Maria
Author_Institution :
Centre for Vision, Speech & Signal Process., Surrey Univ., Guildford
Abstract :
We propose a method that uses bootstraping to classify the pixels in the two halves of a sliding window, assuming that if there is a real image boundary separating the two halves, the pixels in the two halves will be classified in two separate classes. The accuracy of the classification is used as a local "gradient". High values of this gradient allow us to detect weak statistical borders in 2D and 3D images
Keywords :
image classification; bootstraping; classification accuracy; classification gradient; real image boundary; sliding window; weak statistical borders detection; Computed tomography; Educational institutions; Higher order statistics; Histograms; Humans; Lungs; Pixel; Signal processing; Speech processing; Tumors;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.1116
