Changes between Version 8 and Version 9 of GSoC/2016/Additional_segmentation_algorithms
- Timestamp:
- 06/06/16 08:56:50 (9 years ago)
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GSoC/2016/Additional_segmentation_algorithms
v8 v9 4 4 5 5 | 6 | Student Name: 7 | Bo Yang 6 | Student Name: Bo Yang 8 7 |- 9 | Organization: 10 | [http://www.osgeo.org/ OSGeo - Open Source Geospatial Foundation] 8 | Organization: [http://www.osgeo.org/ OSGeo - Open Source Geospatial Foundation] 11 9 |- 12 | Mentors: 13 | Moritz Lennert, Markus Neteler, Markus Metz 10 | Mentors: Moritz Lennert, Markus Metz 14 11 |- 15 | Title: 16 | Additional segmentation algorithms for [https://grass.osgeo.org/grass71/manuals/i.segment.html i.segment] 12 | Title: Additional segmentation algorithms for [https://grass.osgeo.org/grass71/manuals/i.segment.html i.segment] 17 13 |- 18 | Repository: 19 | GRASS 7, browse at: [https://grass.osgeo.org/grass71/manuals/i.segment.html i.segment] 14 | Repository: GRASS 7, browse at: [https://grass.osgeo.org/grass71/manuals/i.segment.html i.segment] 20 15 |- 21 |Weekly Report: 22 | [https://trac.osgeo.org/grass/wiki/GSoC/2016/Additional_segmentation_algorithms/weekly_report Weekly Report] for GRASS GSoC 2016 Additional Image Segmentation Algorithms for i.segment 16 |Weekly Report: [https://trac.osgeo.org/grass/wiki/GSoC/2016/Additional_segmentation_algorithms/weekly_report Weekly Report] for GRASS GSoC 2016 Additional Image Segmentation Algorithms for i.segment 23 17 24 18 25 19 == Background == 26 20 GRASS GIS has the i.segment which provides the possibility to segment an image into objects. This is a basic step in object-based image analysis (OBIA). Currently, the module only provides one segmentation algorithm: region-growing. The code of i.segment was structured in a way that allows addition of other algorithms. The core of proposed GSoC project would thus be to add a series of these algorithms. It would be more useful and comprehensive to add more segment methods to the i.segment module, such as mean-shift and watershed, which could be used in more types of satellite image processing. Special care should be taken for the whole project to code as efficiently as possible, i.e. to make the code run in reasonable time, even for very large images. 27 21 28 22 Idea for this project was suggested by Moritz at [https://trac.osgeo.org/grass/wiki/GSoC/2016/ GDAL SoC Ideas]. 29 30 31 == Background ==32 23 33 24 * Image segmentation or object recognition is the process of grouping similar pixels into unique objects. Segmentation of remote sensing images is a challenging task. A myriad of different methods have been proposed and implemented in recent years. In spite of the huge effort invested in this problem, there is no single approach that can generally solve the problem of segmentation for the large variety of image modalities existing today. The most effective segmentation algorithms are obtained by carefully customizing combinations of components. The parameters of these components are tuned for the characteristics of the image modality used as input and the features of the objects to be segmented. [1]
