Recognizing tree diseases at a distance via image processing and computer vision

The project shows a method of recognizing different tree diseases based on distance via using image processing. The following technique is being used was by partitioning each image into sub regions and compute histograms of local features found inside individual sub regions. Any interesting points o...

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Main Author: Chan, Zhi Xian.
Other Authors: School of Electrical and Electronic Engineering
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/53262
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-532622023-07-07T15:58:01Z Recognizing tree diseases at a distance via image processing and computer vision Chan, Zhi Xian. School of Electrical and Electronic Engineering Ast/P Wang Gang DRNTU::Engineering::Electrical and electronic engineering The project shows a method of recognizing different tree diseases based on distance via using image processing. The following technique is being used was by partitioning each image into sub regions and compute histograms of local features found inside individual sub regions. Any interesting points on the object can be extracted to provide a feature description of it. Hence, Bag-of-features model is used to represent as an unordered collection of words and it has been widely used for computer vision. However, Spatial Pyramid is a better extension of an orderless Bag-of-Words which shows significant improvement of performance. To perform recognition, the features extracted from the training image are feed into Support Vector Machine for data classification. Based on the data classification, we would be able to see which type of trees diseases on highest accuracy. Bachelor of Engineering 2013-05-31T03:00:37Z 2013-05-31T03:00:37Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53262 en Nanyang Technological University 39 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Chan, Zhi Xian.
Recognizing tree diseases at a distance via image processing and computer vision
description The project shows a method of recognizing different tree diseases based on distance via using image processing. The following technique is being used was by partitioning each image into sub regions and compute histograms of local features found inside individual sub regions. Any interesting points on the object can be extracted to provide a feature description of it. Hence, Bag-of-features model is used to represent as an unordered collection of words and it has been widely used for computer vision. However, Spatial Pyramid is a better extension of an orderless Bag-of-Words which shows significant improvement of performance. To perform recognition, the features extracted from the training image are feed into Support Vector Machine for data classification. Based on the data classification, we would be able to see which type of trees diseases on highest accuracy.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Chan, Zhi Xian.
format Final Year Project
author Chan, Zhi Xian.
author_sort Chan, Zhi Xian.
title Recognizing tree diseases at a distance via image processing and computer vision
title_short Recognizing tree diseases at a distance via image processing and computer vision
title_full Recognizing tree diseases at a distance via image processing and computer vision
title_fullStr Recognizing tree diseases at a distance via image processing and computer vision
title_full_unstemmed Recognizing tree diseases at a distance via image processing and computer vision
title_sort recognizing tree diseases at a distance via image processing and computer vision
publishDate 2013
url http://hdl.handle.net/10356/53262
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