Region of Interest Detection Based Fast and Robust Geo-Spatial Object Recognition

Date

2013-01-01

Author

Gürbüz, Yeti Ziya
Alatan, Abdullah Aydın

Metadata

Show full item record

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

Item Usage Stats

126
views

0
downloads

In this paper a novel computationally efficient algorithm to detect objects automatically from high definition satellite imagery with high performance is presented. The proposed algorithm has three main steps supporting each other: Filtering, shape based and appearance based object detection. A region of interest indicating the possible regions that may have the objects to be detected is determined in a very short time via filtering step. In the remaining steps, the objects are extracted from that region and then target ones are detected. While shape based detection provides high precision; appearance based detection improves the recall by using the detected objects by shape based detector. The proposed method is superior with its computational efficiency and high performance. Computational efficiency mainly comes from the filter which is the main contribution of this study to determine region of interest and high detection performance is by means of using shape and appearance based approaches to support each other, which is another contribution as well. The method can detect objects of different scales and rotations with high detection and certain localization performance in high resolution satellite images.

Subject Keywords

Shape descriptors, Bilateral filtering, Image segmentation, Region of interest detection, Object recognition

URI

https://hdl.handle.net/11511/37616

DOI

https://doi.org/10.1109/siu.2013.6531484

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Geospatial Object Recognition From High Resolution Satellite Imagery Ergul, Mustafa; Alatan, Abdullah Aydın (2013-01-01) In this paper, a novel automatic geo-spatial object recognition algorithm from high resolution satellite imagery is proposed. The proposed algorithm consists of two main steps; the generation of hypothesis with a local feature based algorithm and verification step with a shape based approach. The superiority of this method is the ability of minimization of false alarm number in the recognition and this is because object shape includes more characteristic and discriminative information about object identity ...
An automatic geo-spatial object recognition algorithm for high resolution satellite images Ergul, Mustafa; Alatan, Abdullah Aydın (2013-09-26) This paper proposes a novel automatic geo-spatial object recognition algorithm for high resolution satellite imaging. The proposed algorithm consists of two main steps; a hypothesis generation step with a local feature-based algorithm and a verification step with a shape-based approach. In the hypothesis generation step, a set of hypothesis for possible object locations is generated, aiming lower missed detections and higher false-positives by using a Bag of Visual Words type approach. In the verification s...
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...
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...
Object Segmentation in Multi-view Video via Color, Depth and Motion Cues Cigla, Cevahir; Alatan, Abdullah Aydın (2009-01-01) In the light of dense depth map estimation, motion estimation and object segmentation, the research on multi-view video (MVV) content has becoming increasingly popular due to its wide application areas in the near future. In this work, object segmentation problem is studied by additional cues due to depth and motion fields. Segmentation is achieved by modeling images as graphical models and performing popular Normalized Cuts method with some modifications. In the graphical models, each node is represented b...

Citation Formats

Y. Z. Gürbüz and A. A. Alatan, “Region of Interest Detection Based Fast and Robust Geo-Spatial Object Recognition,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37616.