• PAGADALA THARUN
• TUDURU MONISHA
• THATIKONDA NIKHIL SAI
• C R SHRUTHI REDDY

Abstract: In this paper, an ML-based system was built for the Detection of wild animals using images that have been captured with the help of a camera. The main purpose of this project is to reduce collisions between vehicles and animals on roads, such accidents resulting in ecological imbalance and large expenditures in public coffers. This paper presents the components of a simple animal detection system and also a methodology for animal detection in images provided by cameras installed on the roads. This method allows the feature extraction of the image and the use of Machine Learning techniques to classify the areas into animal classes. ML techniques were compared using synthetic images, traversing the pixels of the image using five distinctive approaches. Results show that the Support Vector Machine(SVM) identifies animals on roads accurately.

Animal Detection, SVM ML Algorithm, SVC ML Algorithm, Animal-N30

"Wildlife Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b147-b151, June-2021, Available :http://www.jetir.org/papers/JETIR2106162.pdf

"Wildlife Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb147-b151, June-2021, Available at : http://www.jetir.org/papers/JETIR2106162.pdf