ROAD DETECTION USING MORPHOLOGICAL OPERATIONS IN A COMPLEX SCENARIO
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff185b130000002959010001000600
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
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 4 , Issue: 2 , Pages: 702-708 )
Date of Publication :
November 2013
Page Views :
245
Full Text Views :

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.