Analysis of Satellite Images using Support Vector Machine (SVM)
| dc.contributor.advisor | Singh, Rajesh | |
| dc.contributor.author | Arya, Diksha | |
| dc.date.accessioned | 2019-02-06T04:03:19Z | |
| dc.date.available | 2019-02-06T04:03:19Z | |
| dc.date.issued | 2018-08 | |
| dc.description.abstract | Satellite captured images are eyes in the sky that contain information from around the globe. The information derived from the Satellite Images is helpful in Remote Sensing Applications, Research and Analysis, Organizations or Government bodies in monitoring space, Civil defence operations, etc. Satellites captures huge collection of images at a regular interval of time and analyzing those images manually is very difficult and time consuming. Therefore, an ideal picture classifier system is required to be located that intend to classify the images captured from the satellites so that the images of interest can be easily retrieved. Thus, in our research we aimed to propose a Satellite Image Classification system that can automatically classify the category of physical scene present in an image. For achieving our objective we have utilized Support Vector Machine (SVM), a supervised machine learning algorithm for performing classification; two widely used techniques for extracting Features which are Grey Level Co-occurrence Matrix (GLCM) and Gabor Filter; and Fuzzy C Means for Image Segmentation. We have performed Satellite Image Classification for five physical categories namely Desert, Mountain, Residential, River and Forest. We measured our classification system accuracy using confusion metrics and calculated the precision, sensitivity, specificity and F1 Score. Our classification system achieved overall accuracy of 91.66%. | en_US |
| dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/5810093772 | |
| dc.keywords | satellite surveys, satellite imagery | en_US |
| dc.language.iso | en | en_US |
| dc.pages | 104 | en_US |
| dc.publisher | G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand) | en_US |
| dc.research.problem | Satellite imagery | en_US |
| dc.sub | Information Technology | en_US |
| dc.subject | null | en_US |
| dc.theme | Satellite Surveys | en_US |
| dc.these.type | M.Tech. | en_US |
| dc.title | Analysis of Satellite Images using Support Vector Machine (SVM) | en_US |
| dc.type | Thesis | en_US |