Fusion of Image Segmentations under Markov Random Fields

Date

2014-08-28

Author

Karadag, Ozge Oztimur
Yarman Vural, Fatoş Tunay

Metadata

Show full item record

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

Item Usage Stats

220
views

0
downloads

In this study, a fast and efficient consensus segmentation method is proposed which fuses a set of baseline segmentation maps under an unsupervised Markov Random Fields (MRF) framework. The degree of consensus among the segmentation maps are estimated as the relative frequency of co-occurrences among the adjacent segments. Then, these relative frequencies are used to construct the energy function of an unsupervised MRF model. It is well-known that MRF framework is commonly used for formulating the spatial relationships among the super-pixels, under the Potts model. In this study, the Potts model is reorganized to represent the degree of consensus among the spatially adjacent segments (super-pixels). The proposed segmentation fusion method, called, Boosted-MRF, is tested in various experimental setups, and its performance is compared to the state of the art segmentation methods and satisfactory results are obtained.

Subject Keywords

Computer Science, Artificial Intelligence, Computer Science, Theory & Methods, Engineering, Electrical & Electronic

URI

https://hdl.handle.net/11511/39641

DOI

https://doi.org/10.1109/icpr.2014.170

Conference Name

22nd International Conference on Pattern Recognition (ICPR)

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts Kama, Batuhan; ÖZTÜRK, MURAT; Karagöz, Pınar; Toroslu, İsmail Hakkı; Ozay, Ozcan (2016-09-08) In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the featu...
The limit of sum of Markov Bernoulli variables in system reliability evaluation Şahinoğlu, Mehmet (Institute of Electrical and Electronics Engineers (IEEE), 1990-4) For 2-state maintainable and repairable systems modeled by nonstationary Markov chains, a limiting compound Poisson distribution is derived for the sum of Markov Bernoulli random variables. The result is useful for estimating the distribution of the sum of negative-margin hours in a boundary-crossing scenario involving any physical system with interarrival times of system failures that are negative-exponentially distributed, where the positive- and negative-margin states denote desirable and undesirable ope...
Observability Through a Matrix-Weighted Graph Tuna, Sezai Emre (Institute of Electrical and Electronics Engineers (IEEE), 2018-07-01) Observability of an array of identical linear time-invariant systems with incommensurable output matrices is studied, where an array is called observable when identically zero relative outputs imply synchronized solutions for the individual systems. It is shown that the observability of an array is equivalent to the connectivity of its interconnection graph, whose edges are assigned matrix weights. Moreover, to better understand the relative behavior of distant units, pairwise observability that concerns wi...
A FRAGMENT OF 1ST-ORDER LOGIC ADEQUATE FOR OBSERVATION EQUIVALENCE Oğuztüzün, Mehmet Halit S. (1992-01-01) We present a logical characterization of the Milner's notion of observation equivalence of processes (''at most one observable action at a time'' variant) by using a restricted class of first order formulas. We use the game technique due to Ehrenfeucht as a means to achieve this characterization. First we extend the Ehrenfeucht game by introducing a pair of compatibility relations as a parameter to the game so that we can restrict the moves of the players on the basis of the previous moves. We then define t...
A new likelihood approach to autonomous multiple model estimation Söken, Halil Ersin (Elsevier BV, 2020-04-01) This paper presents an autonomous multiple model (AMM) estimation algorithm for hybrid systems with sudden changes in their parameters. Estimates of Kalman filters (KFs) that are tuned and employed for different system modes are merged based on a newly defined likelihood function without any necessity for filter interaction. The proposed likelihood function is composed of two measures, the filter agility measure and the steady-state error measure. These measures are derived based on filter adaptation rules....

Citation Formats

O. O. Karadag and F. T. Yarman Vural, “Fusion of Image Segmentations under Markov Random Fields,” presented at the 22nd International Conference on Pattern Recognition (ICPR), Swedish Soc Automated Image Anal, Stockholm, SWEDEN, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39641.