Title :
Defocus-based image segmentation
Author :
Swain, Cassandra ; Chen, Tsuhan
Author_Institution :
Vanderbilt Univ., Nashville, TN, USA
Abstract :
Foreground and background features are focused (or defocused) differently in an image because corresponding objects are at different depths in the scene. This paper presents a novel approach for segmenting foreground and background in video images based on feature defocus. A modified defocus measurement that distinguishes between high-contrast defocused edges and low-contrast focused edges is presented. Defocus-based segmentation is desirable because defocus techniques are computationally simple. Results indicate that the foreground is easily segmented from moving background. This approach, coupled with motion detection, can segment complex scenes containing both moving background and stationary foreground
Keywords :
feature extraction; image segmentation; image sequences; motion estimation; video coding; background features; complex scenes; defocus-based segmentation; feature defocus; foreground features; high-contrast defocused edges; image segmentation; low-contrast focused edges; modified defocus measurement; motion detection; moving background; stationary foreground; video images; Focusing; Frequency measurement; Image edge detection; Image segmentation; Integrated circuit modeling; Layout; Lenses; Motion detection; Video coding; Video sequences;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479977