PLANT IDENTIFICATION USING LOCAL INVARIANTS

No Thumbnail Available

Date

2014

Journal Title

Journal ISSN

Volume Title

Publisher

Ieee

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Organizational Units

Journal Issue

Abstract

We present a plant image recognition system geared towards plants with flowers. The system uses local invariants with Dense SIFT features and Bag of Visual Words representation, while the classification is done using Support Vector Machines. Our approach contains a pre-classification stage where images are categorized into color subgroups, to reduce the complexity of the problem. Using a 161-class subset of the ImageClef'2013 flower dataset, the classification accuracy is measured as %42.68, compared to %18 eithout the pre-classification.

Description

Yanikoglu, Berrin/0000-0001-7403-7592

Keywords

Dense SIFT K Means Clustering, Bag of Visual Words (BOVW), SVMs, PHOW

Turkish CoHE Thesis Center URL

Fields of Science

Citation

0

WoS Q

Scopus Q

Source

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY

Volume

Issue

Start Page

2094

End Page

2097