• Divyansh Sinha
• Dr. Samta Gajbhiye

This research shows how to extract any data from a satellite image, such as colours, shapes, textures, and other features. SVM (Support Vector Machine) and texture filters are used to achieve this. Using this image processing technique, significant urban features such as buildings and gardens as well as rural traits such as native flora, water features, and fields may be recognized. Texel is used to represent the textures, which are then divided into several sets depending on how many textures are present in the image. We require satellite pictures in order to use SVM to extract the appropriate image. It is essential to have an image search and indexing tool since picture database sizes have grown significantly. For browsing, searching, and retrieving pictures in a variety of fields—including web-based searching, industry inspection, satellite images, medical diagnosis images, etc.—content-based image retrieval systems (CBIR) have gained a lot of popularity. The difficulty, however, is in creating a system that provides a group of photos that are relevant to the query; for example, if the query image is an image of a horse, the first images returned from a vast image dataset must be horse images. To close the gap between high-level semantic and low-level semantic information, we used Multiple Support Vector Machines Ensemble with CBIR [7], a CBIR that uses colour, texture, and points of interest. By minimizing the empirical classification error and maximizing the geometric margin classifiers, descriptors and improve retrieval performance. The experimental findings demonstrate that the suggested strategy achieves

Retrieval, Satellite Images, Colour and texture, CBIR, SVM (Support Vector Machine).

"SVM Machine Learning Algorithm-Based Efficient Content-Based Image Retrieval System For Satellite Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.h71-h78, July-2023, Available :http://www.jetir.org/papers/JETIR2307708.pdf

"SVM Machine Learning Algorithm-Based Efficient Content-Based Image Retrieval System For Satellite Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. pph71-h78, July-2023, Available at : http://www.jetir.org/papers/JETIR2307708.pdf