Publication Type : Conference Paper
Publisher : Elsevier BV
Source : Procedia Computer Science
Url : https://doi.org/10.1016/j.procs.2016.05.139
Keywords : 2D to 3D conversion, Segmentation, Occlusion elimination, Adaptive K-means
Campus : Bengaluru
Department : Electronics and Communication
Year : 2016
Abstract : Query by Image Content Retrieval abbreviated as QBIR, has become new thirst now a days. By using this systems, user can retrieve the similar images of an already existed image (or) a rough sketch (or) a symbolic representation. To make more efficient and user friendly QBIR multiple features areemployed. This paper proposes a novel approach for image retrieval using adaptive k-means clustering and shape, texture features. The experimental results portraystheperformance of the proposed retrieval system in terms of better precision. To evaluate the proposed method COIL and MPEG-7 shape 1 datasets are used.
Cite this Research Publication : N. Neelima, E. Sreenivasa Reddy, N. Kalpitha, An Efficient QBIR System Using Adaptive Segmentation and Multiple Features, Procedia Computer Science, Elsevier BV, 2016, https://doi.org/10.1016/j.procs.2016.05.139