Fruit recognition system / Nurul Husna Mohd Hofni

Recognition system becomes an important field of computer science due to rapid development of technology. Several fruit recognitions have been developed to fulfill the needs on research based on image processing. Fruits can be recognized based on their basic features such as shape, color and texture...

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Main Author: Nurul Husna, Mohd Hofni
Format: Thesis
Language:English
Published: 2011
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/34265/1/34265.pdf
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spelling my-uitm-ir.342652023-10-26T00:17:35Z Fruit recognition system / Nurul Husna Mohd Hofni 2011-04-01 Nurul Husna, Mohd Hofni Application software Algorithms Algorithms Recognition system becomes an important field of computer science due to rapid development of technology. Several fruit recognitions have been developed to fulfill the needs on research based on image processing. Fruits can be recognized based on their basic features such as shape, color and texture. However, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruit images. A Fruit Recognition System has been proposed, which combines four features analysis methods which are edge-based, color-based, shape-based and size-based in order to increase accuracy of recognition. The objective of this project is to develop an automatic system for fruits recognition. Proposed method recognized fruit images based on obtained features. The recognition was done by calculating the properties of the shape of objects such as diameter, area, and also perimeter. Mean score from these three properties was calculated to recognize the fruits types. Then, the color of an image was extracted to find its dominant color by using RGB and HSV color space. 60 samples of fruits images from five different types of fruits were used to confirm the effectiveness of the proposed approach. Based on experimental results, approximately 96% of the fruits were recognized successfully. Future work could be directed to recognize more types of fruits images. Besides, the texture based analysis technique could be implemented with the existing four features analysis in order to obtain more accurate results for fruits recognition. This system can be applied in a variety fields such as educational, and image retrieval. 2011-04 Thesis https://ir.uitm.edu.my/id/eprint/34265/ https://ir.uitm.edu.my/id/eprint/34265/1/34265.pdf text en public degree Universiti Teknologi MARA Cawangan Perak Faculty of Computer and Mathematical Sciences Prof Madya Dr. Puteri Nor Hashimah, Megat Abdul Rahman
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Prof Madya Dr. Puteri Nor Hashimah, Megat Abdul Rahman
topic Application software
Algorithms
Algorithms
spellingShingle Application software
Algorithms
Algorithms
Nurul Husna, Mohd Hofni
Fruit recognition system / Nurul Husna Mohd Hofni
description Recognition system becomes an important field of computer science due to rapid development of technology. Several fruit recognitions have been developed to fulfill the needs on research based on image processing. Fruits can be recognized based on their basic features such as shape, color and texture. However, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruit images. A Fruit Recognition System has been proposed, which combines four features analysis methods which are edge-based, color-based, shape-based and size-based in order to increase accuracy of recognition. The objective of this project is to develop an automatic system for fruits recognition. Proposed method recognized fruit images based on obtained features. The recognition was done by calculating the properties of the shape of objects such as diameter, area, and also perimeter. Mean score from these three properties was calculated to recognize the fruits types. Then, the color of an image was extracted to find its dominant color by using RGB and HSV color space. 60 samples of fruits images from five different types of fruits were used to confirm the effectiveness of the proposed approach. Based on experimental results, approximately 96% of the fruits were recognized successfully. Future work could be directed to recognize more types of fruits images. Besides, the texture based analysis technique could be implemented with the existing four features analysis in order to obtain more accurate results for fruits recognition. This system can be applied in a variety fields such as educational, and image retrieval.
format Thesis
qualification_level Bachelor degree
author Nurul Husna, Mohd Hofni
author_facet Nurul Husna, Mohd Hofni
author_sort Nurul Husna, Mohd Hofni
title Fruit recognition system / Nurul Husna Mohd Hofni
title_short Fruit recognition system / Nurul Husna Mohd Hofni
title_full Fruit recognition system / Nurul Husna Mohd Hofni
title_fullStr Fruit recognition system / Nurul Husna Mohd Hofni
title_full_unstemmed Fruit recognition system / Nurul Husna Mohd Hofni
title_sort fruit recognition system / nurul husna mohd hofni
granting_institution Universiti Teknologi MARA Cawangan Perak
granting_department Faculty of Computer and Mathematical Sciences
publishDate 2011
url https://ir.uitm.edu.my/id/eprint/34265/1/34265.pdf
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