A texture-based approach for content based image retrieval system for plant leaves images

Image identification of plant leaves based on human vision is difficult task as well as plant identification based on keywords retrieval. It requires the domain knowledge in the botanist field. This work proposes the image texture analysis using Discrete Wavelet Transformation (DWT) and combined wit...

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Main Authors: Hussein, Ahmed Naser, Mashohor, Syamsiah, Saripan, M. Iqbal
Format: Conference or Workshop Item
Language:English
Published: IEEE 2011
Online Access:http://psasir.upm.edu.my/id/eprint/69328/1/A%20texture-based%20approach%20for%20content%20based%20image%20retrieval%20system%20for%20plant%20leaves%20images.pdf
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author Hussein, Ahmed Naser
Mashohor, Syamsiah
Saripan, M. Iqbal
author_facet Hussein, Ahmed Naser
Mashohor, Syamsiah
Saripan, M. Iqbal
author_sort Hussein, Ahmed Naser
collection UPM
description Image identification of plant leaves based on human vision is difficult task as well as plant identification based on keywords retrieval. It requires the domain knowledge in the botanist field. This work proposes the image texture analysis using Discrete Wavelet Transformation (DWT) and combined with an entropy measurement to identify a query image to one of seven classes that consists of 280 plant leaves images. The experimental results show that the proposed method yields higher correctness retrieval accuracy rate which reaches up to 92% compared to the Gray Level Co-occurrence Matrix (GLCM) that gives 49.28%.
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spelling upm.eprints-693282019-07-02T07:59:11Z http://psasir.upm.edu.my/id/eprint/69328/ A texture-based approach for content based image retrieval system for plant leaves images Hussein, Ahmed Naser Mashohor, Syamsiah Saripan, M. Iqbal Image identification of plant leaves based on human vision is difficult task as well as plant identification based on keywords retrieval. It requires the domain knowledge in the botanist field. This work proposes the image texture analysis using Discrete Wavelet Transformation (DWT) and combined with an entropy measurement to identify a query image to one of seven classes that consists of 280 plant leaves images. The experimental results show that the proposed method yields higher correctness retrieval accuracy rate which reaches up to 92% compared to the Gray Level Co-occurrence Matrix (GLCM) that gives 49.28%. IEEE 2011 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69328/1/A%20texture-based%20approach%20for%20content%20based%20image%20retrieval%20system%20for%20plant%20leaves%20images.pdf Hussein, Ahmed Naser and Mashohor, Syamsiah and Saripan, M. Iqbal (2011) A texture-based approach for content based image retrieval system for plant leaves images. In: 2011 IEEE 7th International Colloquium on Signal Processing and its Applications (CSPA 2011), 4-6 Mar. 2011, Penang, Malaysia. (pp. 11-14). 10.1109/CSPA.2011.5759833
spellingShingle Hussein, Ahmed Naser
Mashohor, Syamsiah
Saripan, M. Iqbal
A texture-based approach for content based image retrieval system for plant leaves images
title A texture-based approach for content based image retrieval system for plant leaves images
title_full A texture-based approach for content based image retrieval system for plant leaves images
title_fullStr A texture-based approach for content based image retrieval system for plant leaves images
title_full_unstemmed A texture-based approach for content based image retrieval system for plant leaves images
title_short A texture-based approach for content based image retrieval system for plant leaves images
title_sort texture based approach for content based image retrieval system for plant leaves images
url http://psasir.upm.edu.my/id/eprint/69328/1/A%20texture-based%20approach%20for%20content%20based%20image%20retrieval%20system%20for%20plant%20leaves%20images.pdf
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