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Features Fusion for Retrieval of Flower Videos by D. S. Guru; V. K. Jyothi; Y. H. Sharath Kumar is a book available to read on EtoBox.

What is Features Fusion for Retrieval of Flower Videos about?

This paper presents a Flower Video Retrieval System (FVRS). An algorithmic model is proposed for the retrieval of natural flower videos using Local Binary Pattern (LBP) and Gray-Level Co-occurrence Matrix (GLCM) as texture features and Scale-Invariant Feature Transform (SIFT) features. For a given query flower video, the system retrieves similar videos from the database using Multi-class Support Vector Machine (MSVM). Euclidean distance is used as a proximity measure. The proposed model has been verified on keyframes selected from cluster-based approaches from natural flower videos. Our own dataset is used for the experimentation, which consists of 1919 videos belonging to 20 classes of flowers. It has been observed that the proposed model generates good retrieval results from the fusion of the features SIFT, GLCM, and LBP.

Author

D. S. Guru; V. K. Jyothi; Y. H. Sharath Kumar

Publisher

Springer Singapore : Imprint: Springer

Published

2018

Language

EN

ISBN

9789811325137

Subjects

Engineering, Mathematics, Management