A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Blood Images Using Morphological Operators
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
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Video-based autofocus has become a viable option for microscopes due to the availability of fast microcomputers and cameras that provide high frame rates. The methods proposed plot a measure of the focus vs. the frame number, commonly referred to as focus function which results in a peak when the in focus frame is reached. Recently, generic wavelet-based schemes have been proposed that offer varying degrees of performance depending on the specimens being observed. The performance of these methods can be improved if the nature of the specimen being observed is known. One such scheme for blood smears based on segmentation is presented in this paper. It exploits the fact that the primary objects of interest, the Red Blood Cells (RBC), have a smooth texture. It segments the RBCs and then applies the wavelet-based focus measure. This results in a smooth focus function which permits accurate detection of the in focus frame. The proposed scheme is evaluated using several videos taken from blood smears and the results show that segmentation step improves the wavelet-based measure.