Segmenting a low-depth-of-field image using morphological filters and region merging

Cited 54 time in webofscience Cited 0 time in scopus
  • Hit : 381
  • Download : 2824
We propose a novel algorithm to partition an image with low depth-of-field (DOF) into focused object-of-interest (OOI) and defocused background. The proposed algorithm unfolds into three steps. In the first step, we transform the low-DOF image into an appropriate feature space, in which the spatial distribution of the high-frequency components is represented. This is conducted by computing higher order statistics (HOS) for all pixels in the low-DOF image. Next, the obtained feature space, which is called HOS map in this paper, is simplified by removing small dark holes and bright patches using a morphological filter by reconstruction. Finally, the OOI is extracted by applying region merging to the simplified image and by thresholding. Unlike the previous methods that rely on sharp details of OOI only, the proposed algorithm complements the limitation of them by using morphological filters, which also allows perfect preservation of the contour information. Compared with the previous methods, the proposed method yields more accurate segmentation results, supporting faster processing.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2005-10
Language
English
Article Type
Article
Keywords

SEGMENTATION

Citation

IEEE TRANSACTIONS ON IMAGE PROCESSING, v.14, no.10, pp.1503 - 1511

ISSN
105-77149
DOI
10.1109/TIP.2005.846030
URI
http://hdl.handle.net/10203/10684
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
000232084000009.pdf(1.85 MB)Download
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 54 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0