Abstract
This paper presents an approach for the classification of satellite images by recognizing various objects in them. Satellite images are rich in geographical information that can be used in a number of useful ways. The proposed system classifies satellites images by extracting different objects from the images. Our object recognition mechanism extracts attributes from satellite images under two domains namely: color pixels’ organization and pixel intensity. The extracted attributes aid in the identification of objects lying inside the satellite images. Once we are able to identify objects, we proceeded further to classify satellite images with the help of decision trees. The system has been tested for a number satellite images acquired from around the globe. The objects in the images have been further subdivided into different sub categories to improve the classification and prediction process. This is a novel approach which is not using any image processing techniques but is utilizing the extracted features to identify objects and then using these objects to classify the satellite images.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
