Title :
A new method for segmentation of noisy, low-contrast image sequences
Author :
Chuang, Hsiao-Chiang ; Comer, Mary L.
Author_Institution :
Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
fDate :
May 30 2010-June 2 2010
Abstract :
We propose a new method for segmenting noisy image sequences in a way that imposes consistency between neighboring segmentations in the sequence. Our method uses a statistical model composed of a spatial Markov random field model and a temporal Markov chain model. Results from segmenting sequences of microscopy images of growing silicon nanowires using the proposed model and method show significant improvement over segmenting the sequences using 2D segmentation.
Keywords :
Markov processes; image segmentation; image sequences; image noise; image segmentation; low-contrast image sequences; silicon nanowires; spatial Markov random field model; temporal Markov chain model; Bayesian methods; Humans; Image segmentation; Image sequences; Lighting; Markov random fields; Microscopy; Nanowires; Silicon;
Conference_Titel :
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-5308-5
Electronic_ISBN :
978-1-4244-5309-2
DOI :
10.1109/ISCAS.2010.5536961
