3D Color co-occurrence texture features as tool to evaluate quality of fruits
IR@NISCAIR: CSIR-NISCAIR, New Delhi - ONLINE PERIODICALS REPOSITORY (NOPR)
View Archive Info| Field | Value | |
| Creator |
Bama, B Sathya
Harinie, T Chellam, I Janani Raju, S Abhaikumar, V |
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| Date |
2011-10-31T10:08:49Z
2011-10-31T10:08:49Z 2011-11 |
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| Identifier |
0975-1084 (Online); 0022-4456 (Print)
http://hdl.handle.net/123456789/12960 |
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| Description |
912-917
This paper proposes a novel quality evaluation method to categorize fruits using color and texture features. In proposed method, input image is segmented using histogram based thresholding technique to identify whether the portion of image is defective or non defective. For defected samples, texture features are extracted from 3D color co-occurrence distribution. Sum of squared distance (SSD) is calculated between texture features of training and test fruits. Non defective fruits are considered as extra class, whereas classes I and II are moderately and highly defective fruits respectively. A database of 150 fruit samples was collected from mozambi and orange fruits with all quality classes for marketable – grade fruit inspection and distribution system. Images (80) were manually classified for training and the rest were used for testing. Proposed method (classification accuracy,> 93%) outperforms existing methods. |
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| Language |
en_US
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| Publisher |
NISCAIR-CSIR, India
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| Rights |
<img src='http://nopr.niscair.res.in/image/cc-license-sml.png'> <a href='http://creativecommons.org/licenses/by-nc-nd/2.5/in' target='_blank'>CC Attribution-Noncommercial-No Derivative Works 2.5 India</a>
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| Source |
JSIR Vol.70(11) [November 2011]
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| Subject |
3D Color co-occurrence distribution
Histogram based thresholding Sum of squared distance (SSD) |
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| Title |
3D Color co-occurrence texture features as tool to evaluate quality of fruits
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| Type |
Article
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