Fast genre classification of web images using global and local features

Fast genre classification of web images using global and local features

To effectively mine the contents embedded in web images, it is useful to classify the images into different types so that they can be fed to different procedures for detailed analysis. The authors herein propose a hierarchical algorithm for efficiently classifying web images into four classes. Their...

Full description

Bibliographic Details
Main Authors: Guo-Shuai Liu, Rui-Qi Wang, Fei Yin, Jean-Marc Ogier, Cheng-Lin Liu
Format: Article
Language:English
Published: Wiley 2018-10-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
support vector machines
image texture
feature extraction
image classification
image colour analysis
cameras
support vector machine classifier
first-stage classifier
SVM classifier
second-stage classifier
camera-captured paper documents
global feature extraction
local texture feature extraction
natural scene imaging
fast genre web image classification
born-digital imaging
nontext image discriminations
text image discriminations
image fusion
bag-of-words framework
Intel(R) Xeon(R) central processing unit
frequency 2.9 GHz
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1018

Internet

https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1018

Similar Items