Cigla, Cevahir
Alatan, Abdullah Aydın
A graph theoretic color image segmentation algorithm is proposed, in which the popular normalized cuts image segmentation method is improved with modifications on its graph structure. The image is represented by a weighted undirected graph, whose nodes correspond to over-segmented regions, instead of pixels, that decreases the complexity of the overall algorithm. In addition, the link weights between the nodes are calculated through the intensity similarities of the neighboring regions. The irregular distribution of the nodes, as a result of such a modification, causes a bias towards combining regions with high number of links. This bias is removed by limiting the number of links for each node. Finally, segmentation is achieved by bipartitioning the graph recursively according to the minimization of the normalized cut measure. The simulation results indicate that the proposed segmentation scheme performs quite faster than the traditional normalized cut methods, as well as yielding better segmentation results due to its region-based representation.


Image segmentation with unified region and boundary characteristics within recursive shortest spanning tree
Esen, E.; Alp, Y. K. (2007-06-13)
The lack of boundary information in region based image segmentation algorithms resulted in many hybrid methods that integrate the complementary information sources of region and boundary, in order to increase the segmentation performance. In compliance with this trend, we propose a novel method to unify the region and boundary characteristics within the canonical Recursive Shortest Spanning Tree algorithm. The main idea is to incorporate the boundary information in the distance metric of RSST with minor cha...
Multi-image region growing for integrating disparity maps
Leloglu, UĞUR MURAT; Halıcı, Uğur (1999-01-01)
In this paper, a multi-image region growing algorithm to obtain planar 3-D surfaces in the object space from multiple dense disparity maps, is presented. A surface patch is represented by a plane equation and a set of pixels in multiple images. The union of back projections of all pixels in the set onto the infinite plane, forms the surface patch. Thanks to that hybrid representation of planar surfaces, region growing (both region aggregation and region merging) is performed on all images simultaneously. Pl...
MRF Based Image Segmentation Augmented with Domain Specific Information
Karadag, Ozge Oztimur; Yarman Vural, Fatoş Tunay (2013-09-13)
A Markov Random Field based image segmentation system which combines top-down and bottom-up segmentation approaches is proposed in this study. The system is especially proposed for applications where no labeled training set is available, but some priori general information referred as domain specific information about the dataset is available. Domain specific information is received from a domain expert and formalized by a mathematical representation. The type of information and its representation depends o...
Recursive shortest spanning tree algorithms for image segmentation
Bayramoglu, NY; Bazlamaçcı, Cüneyt Fehmi (2005-11-24)
Image segmentation has an important role in image processing and the speed of the segmentation algorithm may become a drawback for some applications. This study analyzes the run time performances of some variations of the Recursive Shortest Spanning Tree Algorithm (RSST) and proposes simple but effective modifications on these algorithms to improve their speeds. In addition, the effect of link weight cost function on the run time performance and the segmentation quality is examined. For further improvement ...
Erdem, Erkut; Tarı, Zehra Sibel; Vese, Luminita (2009-01-01)
This paper presents a new image segmentation framework which employs a shape prior in the form of an edge strength function to introduce a higher-level influence on the segmentation process. We formulate segmentation as the minimization of three coupled functionals, respectively, defining three processes: prior-guided segmentation, shape feature extraction and local deformation estimation. Particularly, the shape feature extraction process is in charge of estimating an edge strength function from the evolvi...
Citation Formats
C. Cigla and A. A. Alatan, “REGION-BASED IMAGE SEGMENTATION VIA GRAPH CUTS,” 2008, Accessed: 00, 2020. [Online]. Available: