Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval
Author(s) -
Manasee Kurkure,
Anuradha Thakare,
Santvana Gudadhe
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015907677
Subject(s) - computer science , content based image retrieval , cluster analysis , information retrieval , image retrieval , content (measure theory) , image (mathematics) , group (periodic table) , data mining , artificial intelligence , mathematics , mathematical analysis , chemistry , organic chemistry
amounts of databases are created daily in data storage Due to this it becomes very difficult to retrieve the images require for applications in various fields. Thus Content Based Image Retrieval Techniques play an important character in image processing. Here we will be using various masking methods to find out different features and apply different clustering algorithms. In this paper, we are proposing a hybrid model which is the combination of Genetic and Candidate Group Search algorithm. This gives us the best results in some aspects and find it suitable in point of time and accuracy. Candidate Group search Genetic Algorithm is employed to facilitate the users retrieve the images that are most relevant to the users demand.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom