DocumentCode :
1676393
Title :
Hierarchical clustering techniques and classification applied in Content Based Image Retrieval (CBIR)
Author :
Stefan, Radu Andrei ; Szoke, Ildiko-Angelica ; Holban, Stefan
Author_Institution :
Dept. of Comput. Sci., Politeh. Univ. of Timisoara, Timisoara, Romania
fYear :
2015
Firstpage :
147
Lastpage :
152
Abstract :
This paper presents a study on the effectiveness of hierarchical clustering techniques application and classification for imaging context in the Content-Based Image Retrieval (CBIR). The study has the purpose to compare the obtained results from using different hierarchical clustering algorithms with various input parameters and configurations using two types of comparison techniques. The aims is also to highlight the performance improvements and the costs brought up by the integration of such techniques in the content-based image retrieval.
Keywords :
content-based retrieval; image retrieval; pattern clustering; CBIR; content based image retrieval; hierarchical clustering classification; hierarchical clustering techniques; imaging context; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Histograms; Image color analysis; Image retrieval; classification; clustering; content-based; image; retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Computational Intelligence and Informatics (SACI), 2015 IEEE 10th Jubilee International Symposium on
Conference_Location :
Timisoara
Type :
conf
DOI :
10.1109/SACI.2015.7208188
Filename :
7208188
Link To Document :
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