ROAD DETECTION USING MORPHOLOGICAL OPERATIONS IN A COMPLEX SCENARIO
Journal: ICTACT Journal on Image and Video Processing (IJIVP) (Vol.4, No. 2)Publication Date: 2013-11-01
Authors : Neetha Joseph; Jyotsna E;
Page : 702-708
Keywords : Imbalanced Data; Image Classification; Supervised Classification; Unsupervised Classification; DOG Filter;
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.
Other Latest Articles
- FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE PRIMITIVES FOR EFFICIENT FACE RECOGNITION
- IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK FOR FACE RECOGNITION USING GABOR FEATURE EXTRACTION
- ANALYSIS OF TARSAL TUNNEL SYNDROME USING IMAGE CORRELATION
- A MEDICAL MULTI-MODALITY IMAGE FUSION OF CT/PET WITH PCA, DWT METHODS
- COMPARATIVE ANALYSIS OF DS AND IDS ALGORITHMS IN SUPER-SPATIAL STRUCTURE PREDICTION FOR MEDICAL IMAGE SEQUENCES
Last modified: 2013-12-05 18:28:44