DocumentCode
383454
Title
Image flows and one-liner graphical image representation
Author
Makhervaks, Vadim ; Barequet, Gill ; Bruckstein, Alfred
Author_Institution
Fac. of Comput. Sci., Israel Inst. of Technol., Haifa, Israel
Volume
1
fYear
2002
fDate
2002
Firstpage
640
Abstract
In this paper we introduce a novel graphical image representation comprising a single curve - the one-liner The first step involves the detection and linking of image edges. We use a new technique, so-called "edge exploration", to simultaneously perform both tasks. This process is based on "image flows". It uses a gradient vector field and a new operator to explore image edges. Estimating the derivatives of the image is performed by using local Taylor expansions in conjunction with a weighted least-squares estimation method. This process finds all the possible image edges without any pruning, and collects information that allows us to prioritize the found edges. This enables us to select the most important edges, that form a "skeleton" of the sought representation. The next step connects the selected edges into one continuous curve - the one-liner It orders the selected edges and finds curves connecting them. We solve the two problems separately. Since the abstract graph setting of the first problem is NP-complete, we reduce it to a variant of TSP and compute an approximate solution. We solve the second problem by using Dijkstra\´s shortest-path algorithm. We have a full software implementation for the entire one-liner determination process.
Keywords
edge detection; gradient methods; image representation; image sequences; image thinning; least squares approximations; travelling salesman problems; Dijkstra shortest-path algorithm; NP-complete problem; abstract graph setting; approximate solution; edge exploration; edge-exploration operator; gradient vector field; image derivative estimation; image edge detection; image edge linking; image flows; local Taylor expansions; one-liner graphical image representation; selected edge ordering; skeleton; weighted least-squares estimation; Computer science; Detectors; Filters; Image edge detection; Image representation; Joining processes; Labeling; Noise reduction; Pixel; Smoothing methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1044827
Filename
1044827
Link To Document