DocumentCode :
811219
Title :
Tracking of tubular molecules for scientific applications
Author :
Parvin, B.A. ; Peng, C. ; Johnston, W. ; Maestre, F.M.
Author_Institution :
Div. of Comput. Sci. & Eng., Lawrence Berkeley Nat.Lab., CA, USA
Volume :
17
Issue :
8
fYear :
1995
fDate :
8/1/1995 12:00:00 AM
Firstpage :
800
Lastpage :
805
Abstract :
In this paper, we present a system for detection and tracking of tubular molecules in images. The automatic detection and characterization of the shape, location, and motion of these molecules can enable new laboratory protocols in several scientific disciplines. The uniqueness of the proposed system is twofold: At the macro level, the novelty of the system lies in the integration of object localization and tracking using geometric properties; at the micro level, in the use of high and low level constraints to model the detection and tracking subsystem. The underlying philosophy for object detection is to extract perceptually significant features from the pixel level image, and then use these high level cues to refine the precise boundaries. In the case of tubular molecules, the perceptually significant features are antiparallel line segments or, equivalently, their axis of symmetries. The axis of symmetry infers a coarse description of the object in terms of a bounding polygon. The polygon then provides the necessary boundary condition for the refinement process, which is based on dynamic programming. For tracking the object in a time sequence of images, the refined contour is then projected onto each consecutive frame
Keywords :
dynamic programming; macromolecules; object detection; physics computing; tracking; antiparallel line segments; automatic detection; bounding polygon; characterization; dynamic programming; geometric properties; object detection; object localization; scientific applications; symmetry axis; time sequence; tubular molecule tracking; Boundary conditions; Feature extraction; Image segmentation; Laboratories; Motion detection; Object detection; Pixel; Protocols; Shape; Solid modeling;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.400570
Filename :
400570
Link To Document :
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