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| Invariant Recognition of Rectangular Biscuits with Fuzzy Moment Descriptors, Flawed Pieces Detection
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Full
text: |
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Volume: 4 Issue: 3 |
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Pages: 192-286 |
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Publication
Date: July 2010 |
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ISSN
(Online): 1985-2304 |
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Pages |
232 - 239 |
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Author(s) |
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Published
Date |
10-08-2010 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
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| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Fuzzy moment descriptors, Euclidean distance, Flawed biscuits detection |
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| In this paper a new approach for invariant recognition of broken rectangular biscuits is proposed using fuzzy membership-distance products, called fuzzy moment descriptors. The existing methods for recognition of flawed rectangular biscuits are mostly based on Hough transform. However these methods are prone to error due to noise and/or variation in illumination. Fuzzy moment descriptors are less sensitive to noise thus making it an effective approach invariant to the above stray external disturbances. Further, the normalization and sorting of the moment vectors make it a size and rotation invariant recognition process .In earlier studies fuzzy moment descriptors has successfully been applied in image matching problem. In this paper the algorithm is applied in recognition of flawed and non-flawed rectangular biscuits. In general the proposed algorithm has potential applications in industrial quality control. |
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| Pulivarthi Srinivasa Rao : Colleagues
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| Sheli Sinha Chaudhuri : Colleagues
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| Romesh Laishram : Colleagues
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