H
Hamid Reza Pourreza
Researcher at Ferdowsi University of Mashhad
Publications - 142
Citations - 2241
Hamid Reza Pourreza is an academic researcher from Ferdowsi University of Mashhad. The author has contributed to research in topics: Feature extraction & Camera resectioning. The author has an hindex of 23, co-authored 136 publications receiving 1889 citations. Previous affiliations of Hamid Reza Pourreza include Amirkabir University of Technology & Islamic Azad University.
Papers
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Proceedings ArticleDOI
Intelligent video surveillance for monitoring fall detection of elderly in home environments
TL;DR: A novel method to detect various posture-based events in a typical elderly monitoring application in a home surveillance scenario by combination of best-fit approximated ellipse around the human body, projection histograms of the segmented silhouette and temporal changes of head position is proposed.
Fuzzy Running Average and Fuzzy Background Subtraction: Concepts and Application
TL;DR: Experimental results show that fuzzy approach for background modeling and background subtraction is relatively more accurate than classical approach and this method is suggested for fuzzy background modeling.
Journal ArticleDOI
Improvement of retinal blood vessel detection using morphological component analysis.
TL;DR: The proposed MCA algorithm can achieve improved detection in abnormal retinal images and decrease false positive vessels in pathological regions compared to other methods and the robustness of the method in the presence of noise is shown via experimental result.
Journal ArticleDOI
Identification of nine Iranian wheat seed varieties by textural analysis with image processing
TL;DR: In this paper, several textural feature groups of seeds images were examined to evaluate their efficacy in identification of nine common Iranian wheat seed varieties on the whole, 1080 gray scale images of bulk wheat seeds (120 images of each variety) were acquired at a stable illumination condition (florescent ring light).
Journal ArticleDOI
Automated characterization of blood vessels as arteries and veins in retinal images.
TL;DR: A novel structural and automated method is presented for artery/vein classification of blood vessels in retinal images and potentially allows for further investigation of labels of thinner arteries and veins which might be found by tracing them back to the major vessels.