Title :
Image classification based on focus
Author :
Patel, Mehul B. ; Rodriguez, Jeffrey J. ; Gmitro, Arthur F.
Author_Institution :
Dept. of ECE, Univ. of Arizona, Tucson, AZ
Abstract :
The performance of most image classification algorithms deteriorates in the presence of out-of-focus blur. Thus, it is essential to either correct the focus of the input images or leave them out of the training set. There exist many focus metrics for auto-focusing, but they generally give a relative focus value. Our technique combines some of the best performing focus metrics to obtain a new focus measure using which we can separate in-focus images from out-of-focus ones. We also compare our technique with the existing ones and show that it performs better. The classifier was tested on a dataset of ovarian images obtained using confocal microendoscopy.
Keywords :
image classification; auto-focusing; confocal microendoscopy; focus metrics; image classification; out-of-focus blur; ovarian images; Cancer detection; Classification algorithms; Focusing; Image classification; Instruments; Lenses; Noise reduction; Performance evaluation; Principal component analysis; Testing; Focus detection; image classification;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4711775