Segmentand Classify Satellte Images to Analyze The Environment and Ensure Safety, Using Machine Learning

Abstract

Image segmentation is a difficult task in computer vision. The process includes the classification of visual input to segments to simplify image analysis. There are many types of method for the image segmentation some of the common methods are edge detection based method region-based methods, clustering-based method, partial differential equation-based, watershed-based method, and neural network-based method. The proposed project work is mainly focused on image segmentation. Satellite images are given as the input of the proposed system. Machine learning techniques plan an important role in various domains. Here the remotely sensed data can be segmented by using the K-Means clustering method. Compared with other traditional methods this clustering technique yields better results. The system is implemented using the Matlab tool. Machine learning concepts drastically decrease the time needed to arrange an exact map. the project will be using K Nearest Neighbor (KNN) as existing and Support Vector Machine (SVM) as proposed system for classification and calculates results in terms of accuracy. From the results obtained its proved that proposed SVM works better than existing KNN.