• Harshvardhan Singh

Introducing the process of identifying and marking an image location with the help of local features. Our main focus is on the introduction of geometric boundary that reduces the number of RANSAC multiplication by removing all smaller sets from the projective space of an image. In measuring performance we conclude that this restriction increases RANSAC performance by reducing approximately 40% and 80% the number of projective space-related duplicate entities. In addition, it is important to introduce an effective computer vision approach using the location feature and image classification to identify non-existent landmarks. This can be done by combining the VGG-16 and DELF methods to extract local features from images and compare them. Our model is based on K-Nearest neighbor search and geometric verification. With the help of our proposed method, the location of an image can be detected which was invisible in the previous system, as the use of DELF enables the system to extract location features from images and uses RANSAC to verify each image set. The final selection will be a picture of a landmark.

"TOUR RECOMMENDATION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.c262-c266, May-2022, Available :http://www.jetir.org/papers/JETIR2205336.pdf

"TOUR RECOMMENDATION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppc262-c266, May-2022, Available at : http://www.jetir.org/papers/JETIR2205336.pdf