Title :
Boundary extraction using statistical shape descriptor
Author :
Choi, Hae Chul ; Kim, Seong Dae
Author_Institution :
Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
fDate :
10/24/2002 12:00:00 AM
Abstract :
An algorithm is proposed for extracting an object boundary from a low-quality image obtained by infrared sensors. With the training data set, the global shape is modelled by incorporating the statistical curvature model into the point distribution model (PDM). Simulation results show better performance than the PDM in the sense of computation speed and distortion under noise, pose variation and some kinds of occlusions.
Keywords :
feature extraction; infrared imaging; statistical analysis; Bayesian objective function; global shape; infrared sensors; low-quality image; object boundary extraction; occlusions; pattern recognition; point distribution model; pose variation; statistical curvature model; statistical shape descriptor; training data set;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20020918
