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This paper proposes a technique for restoring the motion blurred images. Restoration of blurred images is very important problem in tracking and identification of criminals, where image of a human face or number plate of a running vehicle taken in hit and run situation gets blurred due to relative motion between the imaging system and object/face. For(More)
In this paper, a method for robust image registration based on M-estimator Correlation Coefficient (MCC) is presented. A real valued correlation mask function is computed using Huber and Tukey's robust statistics and is used as a similarity measure for registering image windows. The mask function suppresses the influence of outlier points and makes the(More)
Classification is a major problem of study that involves formulation of decision boundaries based on the training data samples. The limitations of the single neural network approaches motivate the use of multiple neural networks for solving the problem in the form of ensembles and modular neural networks. While the ensembles solve the problem redundantly,(More)
In automatic segmentation of leukocytes from the complex morphological background of tissue section images, a vast number of artifacts/noise are also extracted causing large amount of multivariate data generation. This multivariate data degrades the performance of a classifier to discriminate between leukocytes and artifacts/noise. However, the selection of(More)
Automatic quantification and classification of leukocytes in microscopic images are of paramount importance in the perspective of disease identification, its progress and drugs development. Extracting numerical values of leukocytes from microscopic images of blood or tissue sections represents a tricky challenge. Research efforts in quantification of these(More)