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Breast density is an important cue to detect both the presence of suspicious cancerous masses and to predict future possibility for cancer development. A fast breast density classification method is presented and successfully tested on two state-of-the-art mammogram databases. The X-ray digital mammogram tissue texture is locally represented by the two-dimensional adaptive causal autoregressive spatial...
Five fully automatic methods for X-ray digital mammogram enhancement based on a fast analytical textural model are presented. These efficient single and double view enhancement methods are based on the underlying two-dimensional adaptive causal autoregressive texture model. The methods locally predict breast tissue texture from single or double view mammograms and enhance breast tissue abnormalities,...
Accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. Undected iris occlusions otherwise dramatically decrease the iris recognition rate. This paper presents a fast multispectral iris occlusions detection method based on the underlying multispectral spatial probabilistic iris textural model...
Real world materials often change their appearance over time. If these variations are spatially and temporally homogeneous then the material visual appearance can be represented by a dynamic texture which is a natural extension of classic texture concept including the time as an extra dimension. In this article we present possible way to handle multispectral dynamic textures based on a combination...
The prerequisite for the accurate iris recognition is to detect all iris occlusions which would otherwise confuse a recognition method and impair its recognition rate. This paper presents a fast multispectral eyelid, eyelash, and reflection detection method based on the underlying three-dimensional spatial probabilistic textural model. The model first adaptively learns its parameters on the flawless...
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