Segmentation and deciısion fusion for building detection

Date

2014-07-18

Author

Karadag, Ozge Oztimur
Senaras, Caglar
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

195
views

0
downloads

Segment based classification is one of the popular approaches for object detection, where the performance of the classification task is sensitive to the accuracy of the output of the initial segmentation. Most of these studies includes generic segmentation methods and it is assumed that the segmentation output is compatible with the subsequent classification method. However, depending on the problem domain the properties of the regions such as size, shape etc. which are suitable for classification may vary. In this study, we propose a domain specific segmentation method for building detection. The contribution of the domain specific segmentation is empirically analyzed. For this purpose, first the decision fusion method is employed for building detection on the outputs of the state of the art segmentation methods, then it is employed on the output of the domain specific segmentation method and the classification performances for each method are compared. The advantage of domain specific segmentation is observed quantitatively and satisfactory results are obtained

Subject Keywords

Segmentation, Building detection, Fusion, Domain specific segmentation

URI

https://hdl.handle.net/11511/44269

DOI

https://doi.org/10.1109/igarss.2014.6946753

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Segmentation Fusion for Building Detection Using Domain-Specific Information Karadag, Ozge Oztimur; Senaras, Caglar; Yarman Vural, Fatoş Tunay (2015-07-01) Segment-based classification is one of the popular approaches for object detection, where the performance of the classification task is sensitive to the accuracy of the output of the initial segmentation. Majority of the object detection systems directly use one of the generic segmentation algorithms, such as mean shift or k-means. However, depending on the problem domain, the properties of the regions such as size, color, texture, and shape, which are suitable for classification, may vary. Besides, fine tu...
SEGMENTATION USING THE EDGE STRENGTH FUNCTION AS A SHAPE PRIOR WITHIN A LOCAL DEFORMATION MODEL 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...
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...
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...
Segmentation Driven Object Detection with Fisher Vectors Cinbiş, Ramazan Gökberk; Schmid, Cordelia (2013-01-01) We present an object detection system based on the Fisher vector (FV) image representation computed over SIFT and color descriptors. For computational and storage efficiency, we use a recent segmentation-based method to generate class-independent object detection hypotheses, in combination with data compression techniques. Our main contribution is a method to produce tentative object segmentation masks to suppress background clutter in the features. Re-weighting the local image features based on these masks...

Citation Formats

O. O. Karadag, C. Senaras, and F. T. Yarman Vural, “Segmentation and deciısion fusion for building detection,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/44269.