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Behzad Mirmahboub
Researcher at University of Southern Brittany
Publications - 17
Citations - 271
Behzad Mirmahboub is an academic researcher from University of Southern Brittany. The author has contributed to research in topics: Tree (data structure) & Region growing. The author has an hindex of 7, co-authored 17 publications receiving 221 citations. Previous affiliations of Behzad Mirmahboub include Istituto Italiano di Tecnologia & Isfahan University of Technology.
Papers
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Journal ArticleDOI
Automatic Monocular System for Human Fall Detection Based on Variations in Silhouette Area
TL;DR: This paper proposes to use variations in silhouette area that are obtained from only one camera to find the silhouette, and shows that the proposed feature is view invariant.
Journal ArticleDOI
Image retargeting using depth assisted saliency map
TL;DR: A novel energy function which combines the information from saliency map, depth map and gradient map is proposed which reduces shape deformations and visual artifacts in salient regions of images and produces better quality output images.
Proceedings ArticleDOI
Liver Segmentation in Abdominal CT Images Using Probabilistic Atlas and Adaptive 3D Region Growing
Shima Rafiei,Nader Karimi,Behzad Mirmahboub,Kayvan Najarian,Banafsheh Felfeliyan,Shadrokh Samavi,S. M. Reza Soroushmehr +6 more
TL;DR: This paper proposes innovative pre-processing and adaptive 3D region growing methods with subject-specific conditions with effective contrast enhancement algorithm to obtain strong edges and high contrast.
Proceedings ArticleDOI
Bone extraction in X-ray images by analysis of line fluctuations
S. Kazeminia,Nader Karimi,Behzad Mirmahboub,S.M.R. Soroushmehr,Shadrokh Samavi,Kayvan Najarian +5 more
TL;DR: A new bone segmentation method in which an image goes through preprocessing steps such as noise cancellation and edge detection and analysis of intensity fluctuations in all rows of the image results in more accurate segmentation of bone regions.
Proceedings ArticleDOI
Image seam carving using depth assisted saliency map
TL;DR: The visual artifacts that cause shape deformation in salient objects and deteriorates geometrical consistency of the scene are considerably reduced in the proposed algorithm.