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Invariant Recognition of Rectangular Biscuits with Fuzzy Moment Descriptors, Flawed Pieces Detection
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International Journal of Image Processing (IJIP)
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Volume:  4    Issue:  3
Pages:  192-286
Publication Date:   July 2010
ISSN (Online): 1985-2304
Pages 
232 - 239
Author(s)  
 
Published Date   
10-08-2010 
Publisher 
CSC Journals, Kuala Lumpur, Malaysia
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Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
 
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
Sheli Sinha Chaudhuri : Colleagues
Romesh Laishram : Colleagues  
 
 
 
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