DocumentCode
2145356
Title
A Similarity Measuring Method Between Image Regions Based on Granular Computing
Author
Shi, Jinling ; Du, Genyuan
Author_Institution
Int. Sch. of Educ., Xuchang Univ., Xuchang, China
fYear
2010
fDate
14-16 Aug. 2010
Firstpage
755
Lastpage
758
Abstract
To effectively measure the similarity between image regions, this paper proposes a new measuring method based on granular computing theory. First, image feature information table is transformed into the type of order matrix by defining the concept of image feature information table, order matrix, feature granular and granular base. Secondly, further study and analysis of order matrix and feature granular with granular computing model are required. Moreover, a similarity measuring method is defined on condition that it doesn´t change the image information based on the concepts of feature values and feature weights. Lastly, a detailed example is given to prove the validity of the similarity measuring method.
Keywords
artificial intelligence; content-based retrieval; image retrieval; feature granular; feature values concept; feature weights concept; granular base; granular computing; image feature information table; image regions; order matrix; similarity measurement method; Computational modeling; Educational institutions; Feature extraction; Image retrieval; Velocity measurement; Weight measurement; granular computing; image feature; order relation; similarity measure;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location
San Jose, CA
Print_ISBN
978-1-4244-7964-1
Type
conf
DOI
10.1109/GrC.2010.27
Filename
5576067
Link To Document