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Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 132 - Number 16 |
| Year of Publication: 2015 |
| Authors: Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe |
10.5120/ijca2015907677
|
Manasee Kurkure, Anuradha Thakare, Santvana Gudadhe . Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval. International Journal of Computer Applications. 132, 16 ( December 2015), 6-9. DOI=10.5120/ijca2015907677
Abstract
Large 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.
References
- Cheng Huang Hung, Hua-Min Chiou, Wei-Ning Yang, "Candidate groups search for K-harmonic means data clustering," Applied Mathematical Modelling, Elsevier, 2013.
- Anuradha Thakare, Rohini Hanchate, http://research.ijcaonline.org /volume88 /number17 /pxc3894002.pdf, “Introducing Hybrid model for Data Clustering using K-Harmonic Means and Gravitational Search Algorithms,” 2014.
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- https://sites.google.com/site/dctresearch/Home/content-based-image-retrieval Last referred on 15 september 2015.
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