Abstract

Image classification is an important research area in computer vision. Organizing images into semantic categories can be extremely useful for searching and browsing through large collections of images. It is a challenging task in various application domains, including satellite image classification, syntactic pattern recognition, medical diagnosis, biometry, video surveillance, vehicle navigation, industrial visual inspection, robot navigation etc. There are different approaches for image classification and imbalanced data classification. This paper provides a review of different methods for classifying images and imbalanced data classification. This paper proposes a method for road detection and highlights the importance of the imbalanced data classification in detecting the road in a complex scenario.

Authors

Neetha Joseph, Jyotsna E
Federal Institute of Science and Technology, India

Keywords

Imbalanced Data, Image Classification, Supervised Classification, Unsupervised Classification, DOG Filter