Thai Fruit Recognition System (TFRS)

Chomtip Pornpanomchai; Khomkhwan Srikeaw; Voranun Harnprasert; Kamonwan Promnurakkit

doi:10.1145/1734605.1734633

Thai Fruit Recognition System (TFRS)

Chomtip Pornpanomchai
, Khomkhwan Srikeaw
, Voranun Harnprasert
, Kamonwan Promnurakkit

Computer Science Academic Group

Mahidol University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

The main objective of this research is to develop a computer system that can recognize Thai fruit by using image processing techniques. Our system is called "Thai Fruit Recognition System (TFRS)". The system consists of four major components, which are: 1) image acquisition, 2) image preprocessing, 3) recognition, and displaying result. We used three important features to recognize Thai fruit, which are RGB colors, size, and edge shape. The TFRS is trained system with 39 kinds of Thai fruit on 312 images. We test our system on 123 images of 39 kinds of fruit for a training dataset and 30 images of 10 kinds of fruit for an un-training dataset. The precision of our system is 93.50 percent for the training dataset and 86.67 percent for the un-training dataset. The average access time is 54.68 seconds per image.

Original language	English
Title of host publication	1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009
Pages	108-112
Number of pages	5
DOIs	https://doi.org/10.1145/1734605.1734633
Publication status	Published - 2009
Event	1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009 - Kunming, Yunnan, China Duration: 23 Nov 2009 → 25 Nov 2009

Publication series

Name	1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009

Conference

Conference	1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009
Country/Territory	China
City	Kunming, Yunnan
Period	23/11/09 → 25/11/09

Keywords

Fruit extraction
Fruit recognition
Thai fruit

Access to Document

10.1145/1734605.1734633

Cite this

@inproceedings{01e130c80283488d89d8c603fbb22111,

title = "Thai Fruit Recognition System (TFRS)",

abstract = "The main objective of this research is to develop a computer system that can recognize Thai fruit by using image processing techniques. Our system is called {"}Thai Fruit Recognition System (TFRS){"}. The system consists of four major components, which are: 1) image acquisition, 2) image preprocessing, 3) recognition, and displaying result. We used three important features to recognize Thai fruit, which are RGB colors, size, and edge shape. The TFRS is trained system with 39 kinds of Thai fruit on 312 images. We test our system on 123 images of 39 kinds of fruit for a training dataset and 30 images of 10 kinds of fruit for an un-training dataset. The precision of our system is 93.50 percent for the training dataset and 86.67 percent for the un-training dataset. The average access time is 54.68 seconds per image.",

keywords = "Fruit extraction, Fruit recognition, Thai fruit",

author = "Chomtip Pornpanomchai and Khomkhwan Srikeaw and Voranun Harnprasert and Kamonwan Promnurakkit",

year = "2009",

doi = "10.1145/1734605.1734633",

language = "English",

isbn = "9781605588407",

series = "1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009",

pages = "108--112",

booktitle = "1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009",

note = "1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009 ; Conference date: 23-11-2009 Through 25-11-2009",

}

Pornpanomchai, C, Srikeaw, K, Harnprasert, V & Promnurakkit, K 2009, Thai Fruit Recognition System (TFRS). in 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009. 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009, pp. 108-112, 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009, Kunming, Yunnan, China, 23/11/09. https://doi.org/10.1145/1734605.1734633

Thai Fruit Recognition System (TFRS). / Pornpanomchai, Chomtip; Srikeaw, Khomkhwan; Harnprasert, Voranun et al.
1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009. 2009. p. 108-112 (1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Thai Fruit Recognition System (TFRS)

AU - Pornpanomchai, Chomtip

AU - Srikeaw, Khomkhwan

AU - Harnprasert, Voranun

AU - Promnurakkit, Kamonwan

PY - 2009

Y1 - 2009

N2 - The main objective of this research is to develop a computer system that can recognize Thai fruit by using image processing techniques. Our system is called "Thai Fruit Recognition System (TFRS)". The system consists of four major components, which are: 1) image acquisition, 2) image preprocessing, 3) recognition, and displaying result. We used three important features to recognize Thai fruit, which are RGB colors, size, and edge shape. The TFRS is trained system with 39 kinds of Thai fruit on 312 images. We test our system on 123 images of 39 kinds of fruit for a training dataset and 30 images of 10 kinds of fruit for an un-training dataset. The precision of our system is 93.50 percent for the training dataset and 86.67 percent for the un-training dataset. The average access time is 54.68 seconds per image.

AB - The main objective of this research is to develop a computer system that can recognize Thai fruit by using image processing techniques. Our system is called "Thai Fruit Recognition System (TFRS)". The system consists of four major components, which are: 1) image acquisition, 2) image preprocessing, 3) recognition, and displaying result. We used three important features to recognize Thai fruit, which are RGB colors, size, and edge shape. The TFRS is trained system with 39 kinds of Thai fruit on 312 images. We test our system on 123 images of 39 kinds of fruit for a training dataset and 30 images of 10 kinds of fruit for an un-training dataset. The precision of our system is 93.50 percent for the training dataset and 86.67 percent for the un-training dataset. The average access time is 54.68 seconds per image.

KW - Fruit extraction

KW - Fruit recognition

KW - Thai fruit

UR - https://www.scopus.com/pages/publications/77951609668

U2 - 10.1145/1734605.1734633

DO - 10.1145/1734605.1734633

M3 - Conference contribution

AN - SCOPUS:77951609668

SN - 9781605588407

T3 - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009

SP - 108

EP - 112

BT - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009

T2 - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009

Y2 - 23 November 2009 through 25 November 2009

ER -

Thai Fruit Recognition System (TFRS)

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Keywords

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