A Fully automatic shape based geo-spatial object recognition

Download
index.pdf
2012
Ergül, Mustafa
Show full item record
225
views
91
downloads
A great number of methods based on local features or global appearances have been proposed in the literature for geospatial object detection and recognition from satellite images. However, since these approaches do not have enough discriminative capabilities between object and non-object classes, they produce results with innumerable false positives during their detection process. Moreover, due to the sliding window mechanisms, these algorithms cannot yield exact location information for the detected objects. Therefore, a geospatial object recognition algorithm based on the object shape mask is proposed to minimize the aforementioned imperfections. In order to develop such a robust recognition system, foreground extraction performance of some of popular fully and semi-automatic image segmentation algorithms, such as normalized cut, k-means clustering, mean-shift for fully automatic, and interactive Graph-cut, GrowCut, GrabCut for semi-automatic, are evaluated in terms of their subjective and objective qualities. After this evaluation, the retrieval performance of some shape description techniques, such as ART, Hu moments and Fourier descriptors, are investigated quantitatively. In the proposed system, first of all, some hypothesis points are generated for a given test image. Then, the foreground extraction operation is achieved via GrabCut algorithm after utilizing these hypothesis points as if these are user inputs. Next, the extracted binary object masks are described by means of the integrated versions of shape description techniques. Afterwards, SVM classifier is used to identify the target objects. Finally, elimination of the multiple detections coming from the generation of hypothesis points is performed by some simple post-processing on the resultant masks. Experimental results reveal that the proposed algorithm has promising results in terms of accuracy in recognizing many geospatial objects, such as airplane and ship, from high resolution satellite imagery.
Image processing, Imaging systems, Geospatial data., Spatial data infrastructures., Remote-sensing images.
http://etd.lib.metu.edu.tr/upload/12614680/index.pdf
https://hdl.handle.net/11511/21997
Graduate School of Natural and Applied Sciences, Thesis

Suggestions

A Computationally Efficient Appearance-Based Algorithm for Geospatial Object Detection
Arslan, Duygu; Alatan, Abdullah Aydın (2012-04-27)
A computationally efficient appearance-based algorithm for geospatial object detection is presented and evaluated specifically for aircraft detection from satellite imagery. An aircraft operator exploiting the edge information via gray level differences between the aircraft and its background is constructed with Haar-like polygon regions by using the shape information of the aircraft as an invariant. Fast evaluation of the aircraft operator is achieved by means of integral image. Rotated integral images are...
Global appearance based airplane detection from satellite imagery
Arslan, Duygu; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2012)
There is a rising interest in geospatial object detection due to not only the complexity of manual processing of such huge amount of data provided by high resolution satellite imagery but also for military application needs. A fundamental and yet state-of-the art approach for object detection is based on methods that utilize the global appearance. In such a holistic approach, the information of the object class is aimed to be modeled as a whole in the learning phase. And during the classification, a decisio...
A Fast shape detection approach by directional integrations
Okman, Osman Erman; Akar, Gözde; Department of Electrical and Electronics Engineering (2013)
Detection and identification of objects from aerial images are important problems for various types of application areas. For many of the man-made structures shape is a fundamental feature by which these objects are separated from the background and other structures. In this thesis, a novel geometric shape detection algorithm based on the spatial properties of structures is proposed. Since the objects are transformed into 1-D vectors by evaluating directional integrals and detections occur by the analysis o...
A Shadow based trainable method for building detection in satellite images
Dikmen, Mehmet; Halıcı, Uğur; Department of Geodetic and Geographical Information Technologies (2014)
The purpose of this thesis is to develop a supervised building detection and extraction algorithm with a shadow based learning method for high-resolution satellite images. First, shadow segments are identified on an over-segmented image, and then neighboring shadow segments are merged by assuming that they are cast by a single building. Next, these shadow regions are used to detect the candidate regions where buildings most likely occur. Together with this information, distance to shadows towards illuminati...
An Embedded spatial statistics toolbox (R techniques) in open source GİS software (uDig)
Çavur, Mahmut; Düzgün, H. Şebnem; Department of Geodetic and Geographical Information Technologies (2016)
It is widely considered that geographic information systems (GIS) should include more spatial data analysis (SDA) techniques. The issues of which techniques should be included and how statistical analysis can be integrated with GIS are still widely debated. However, the typical software does not include all geospatial techniques. In this respect, this thesis focuses on the means to develop a framework which implements R spatial statistical techniques in the uDig GIS so that GIS and spatial statistical analy...
Citation Formats
M. Ergül, “A Fully automatic shape based geo-spatial object recognition,” M.S. - Master of Science, Middle East Technical University, 2012.
METU IIS - Integrated Information Service open@metu.edu.tr