Interactive color image segmentation with linear programming

Image segmentation is an important and fundamental task for image and vision understanding. This paper describes a linear programming (LP) approach for segmenting a color image into multiple regions. Compared with the recently proposed semi-definite programming (SDP)-based approach, our approach has...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Machine vision and applications Ročník 21; číslo 4; s. 403 - 412
Hlavní autori: Li, Hongdong, Shen, Chunhua
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer-Verlag 01.06.2010
Predmet:
Algorithms
Color
Communications Engineering
Complexity
Computer Science
Image contrast
Image Processing and Computer Vision
Image segmentation
Mathematical analysis
Mathematical models
Networks
Original Article
Pattern Recognition
Object cutout
Linear programming
Interactive image segmentation
ISSN:0932-8092, 1432-1769
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Image segmentation is an important and fundamental task for image and vision understanding. This paper describes a linear programming (LP) approach for segmenting a color image into multiple regions. Compared with the recently proposed semi-definite programming (SDP)-based approach, our approach has a simpler mathematical formulation, and a far lower computational complexity. In particular, to segment an image of M  × N pixels into k classes, our method requires only O (( M N k ) m ) complexity—a sharp contrast to the complexity of O (( M N k ) 2 n ) if the SDP method is adopted, where m and n are the polynomial complexity of the corresponding LP solver and SDP solver, respectively (in general we have m ≪ n ). Such a significant reduction in computation readily enables our algorithm to process color images of reasonable sizes. For example, while the existing SDP relaxation algorithm is only able to segment a toy-size image of, e.g., 10 × 10 to 30 × 30 pixels in hours time, our algorithm can process larger color image of, say, 100 × 100 to 500 × 500 image in much shorter time.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0932-8092
1432-1769
DOI:10.1007/s00138-008-0171-x