Title :
Semantic-based scene image classification
Author :
Xiaoru Wang ; Junping Du ; Jie Liu
Author_Institution :
Sch. of Comput. Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
As more and more people share and search the images on the Internet, there has strong demand to automatically classify the images and mimic human visual perception. This paper proposes a new semantic based classification method for scene images. It efficiently classifies the image with the semantic model of the scene. And it builds a 4-dimension object semantic histogram based on the low-level features of the major objects. The SVM is used for the multi-class classifier in order to get the scene semantics. The experiments show that this algorithm is very efficient and effective with a high accuracy level for scene images.
Keywords :
Internet; image classification; image enhancement; support vector machines; 4-dimension object semantic histogram; Internet; SVM; human visual perception; low-level features; multiclass classifier; semantic-based scene image classification; SVM classification; feature extraction; scene image classification; semantic based segmentation;
Conference_Titel :
Advanced Intelligence and Awareness Internet (AIAI 2011), 2011 International Conference on
Conference_Location :
Shenzhen
Electronic_ISBN :
978-1-84919-471-6
DOI :
10.1049/cp.2011.1446