We propose a new approach for image segmentation based on a hierarchical and spatially
variant mixture model. According to this model, the pixel labels are random variables and a …

Recognizing human activities from video sequences or still images is a challenging task
due to problems, such as background clutter, partial occlusion, changes in scale, viewpoint, …

New methods for detecting shot boundaries in video sequences and for extracting key frames
using metrics based on information theory are proposed. The method for shot boundary …

In this study, heartbeat time series are classified using support vector machines (SVMs).
Statistical methods and signal analysis techniques are used to extract features from the signals. …

In this paper, we present a fully automated method for cell nuclei detection in Pap smear
images. The locations of the candidate nuclei centroids in the image are detected with …

A new Bayesian model is proposed for image segmentation based upon Gaussian mixture
models (GMM) with spatial smoothness constraints. This model exploits the Dirichlet …

Classification of cervical cells in Pap smear images is a challenging task due to the limitations
these images exhibit and the complexity of the morphological changes in the structural …

Vast collections of documents available in image format need to be indexed for information
retrieval purposes. In this framework, word spotting is an alternative solution to optical …

In this work, we present an automated method for the detection and boundary determination
of cells nuclei in conventional Pap stained cervical smear images. The detection of the …

A method for the segmentation of overlapping nuclei is presented, which combines local
characteristics of the nuclei boundary and a priori knowledge about the expected shape of the …