Argyrios Christodoulidis

Proliferative diabetic retinopathy is an important public health issue with deteriorating impact on the vision of its patient. In this study, a novel approach is proposed for the characterization of abnormal vessels based on a spatial point pattern method. Points of interest corresponding to vascular junctions are detected by a perceptual organization technique, and then second-order statistical measures are computed. Significant differences (p<;0.05) between healthy retinal regions and areas with neovascularizations were obtained, which suggests that the second-order statistics could be used as a relevant feature to discriminate the abnormal from the normal vasculature. The relevance of the new measures was also evaluated with respect to an existing set of features using classification. The inclusion of a new second-order measure increases the characterization sensitivity against the already existing features from 75.76% to 84.85%.

The automated human behavior modeling is highly desired in the context of an assistive environment. In this paper, we describe a software video processing and analysis system to assist the near real time detection of human activity. The video data are acquired indoors from fixed cameras in the living environment. The proposed system uses image-processing techniques to segment the human figure from the background, suppress the appearance of its shadow and detect the path and velocity of its motion. Detail performance measurements of the proposed algorithm are given in terms of execution time. Initial results are presented for a small number of video sequences.