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
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;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.27