Open AccessFeature Extraction for Image Texture Classification
Author(s) -
Alexander John,
P. Praveen,
S. Balaji
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1078.1292s419
Subject(s) - histogram , texture (cosmology) , artificial intelligence , feature (linguistics) , computer science , surface (topology) , feature extraction , pattern recognition (psychology) , image (mathematics) , computer vision , channel (broadcasting) , mathematics , geometry , philosophy , linguistics , computer network
Surface request accept a critical activity in PC vision and picture taking care of utilizations. We propose an approach to manage concentrate picture features for surface portrayal. This procedure for removing picture features for request of surfaces is solid to picture insurgency, less sensitive to histogram leveling and bustle. It includes two courses of action of picture features: overpowering close-by twofold models (DLBP) in a surface picture and the beneficial features expelled by using circularly symmetric Gabor channel responses. The predominant close-by twofold model system use the most a great part of the time happened guide to find hypnotizing textural information, while the Gabor-based features go for giving additional overall textural information to the DLBP features