Title :
Mixture Feature Based Junk Image Filtering
Author :
Bo, Qirong ; Pen, Jinye
Author_Institution :
Inst. of Inf. Sci. & Technol., Northwest Univ., Xi´´an, China
Abstract :
Text based image search tools such as Google and Baidu will cause lots of junk image, because only text near the image was searched. We construct a content based junk image filter system to resolve this problem. We use kernel based KNN to clustered the image searched by the Google into multiple classes by its vision feature, then use hyperbolic technique to display the image sampled from the clustered image, when user selected the image wanted, save the images which class equal to the image selected and filter out others.
Keywords :
computer vision; feature extraction; filtering theory; image retrieval; pattern clustering; search engines; Google; content based junk image filter system; hyperbolic technique; image search clustering; junk image filtering; kernel based KNN; mixture feature; text based image search tools; vision feature; Computers; Distributed control; Monitoring; Image filtering; Kernel function; Mixture feature;
Conference_Titel :
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4673-0458-0
DOI :
10.1109/CDCIEM.2012.104