Recursive shortest spanning tree algorithms for image segmentation

Date

2005-11-24

Author

Bayramoglu, NY
Bazlamaçcı, Cüneyt Fehmi

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

154
views

0
downloads

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 in the run time performance of the fastest sequential method, a distributed RSST algorithm is also proposed and evaluated.

Subject Keywords

Distributed segmentation, Image segmentation, Recursive shortest spanning tree (RSST)

URI

https://hdl.handle.net/11511/54201

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

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...
Edge strength functions as shape priors in image segmentation Erdem, Erkut; Erdem, Aykut; Tarı, Zehra Sibel (2005-12-01) Many applications of computer vision requires segmenting out of an object of interest from a given image. Motivated by unlevel-sets formulation of Raviv, Kiryati and Sochen [8] and statistical formulation of Leventon, Grimson and Faugeras [6], we present a new image segmentation method which accounts for prior shape information. Our method depends on Ambrosio-Tortorelli approximation of Mumford-Shah functional. The prior shape is represented by a by-product of this functional, a smooth edge indicator functi...
REGION-BASED IMAGE SEGMENTATION VIA GRAPH CUTS Cigla, Cevahir; Alatan, Abdullah Aydın (2008-01-01) 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 distri...
AUTOMATIC MULTI-SCALE SEGMENTATION OF HIGH SPATIAL RESOLUTION SATELLITE IMAGES USING WATERSHEDS Sahin, Kerem; Ulusoy, İlkay (2013-07-26) An automatic segmentation algorithm that is based on watersheds and region merging type multi-scale segmentation (MSS) is proposed, which can be used as the initial step of an object-based classifier. First, the image is segmented using watershed segmentation. Then, primitive segments are merged to create meaningful objects by the proposed hybrid region merging algorithm. During these steps, an unsupervised segmentation accuracy metric is considered so that best performing parameters of the proposed algorit...
Object recognition and segmentation via shape models Altınoklu, Metin Burak; Ulusoy, İlkay; Tarı, Zehra Sibel; Department of Electrical and Electronics Engineering (2016) In this thesis, the problem of object detection, recognition and segmentation in computer vision is addressed with shape based methods. An efficient object detection method based on a sparse skeleton has been proposed. The proposed method is an improved chamfer template matching method for recognition of articulated objects. Using a probabilistic graphical model structure, shape variation is represented in a skeletal shape model, where nodes correspond to parts consisting of lines and edges correspond to pa...

Citation Formats

N. Bayramoglu and C. F. Bazlamaçcı, “Recursive shortest spanning tree algorithms for image segmentation,” 2005, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54201.