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Invariant Recognition of Rectangular Biscuits with Fuzzy Moment Descriptors, Flawed Pieces Detection
Pulivarthi Srinivasa Rao, Sheli Sinha Chaudhuri, Romesh Laishram
Pages - 232 - 239     |    Revised - 30-06-2010     |    Published - 10-08-2010
Volume - 4   Issue - 3    |    Publication Date - July 2010  Table of Contents
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KEYWORDS
Fuzzy moment descriptors, Euclidean distance, Flawed biscuits detection
ABSTRACT
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.
CITED BY (2)  
1 Das, P. K., Mandhata, S. C., Behera, H. S., & Patro, S. N. (2012). Visual Perception based Motion Planning of Mobile Robot using Road Sign. International Journal of Computer Applications, 48(15), 4-9.
2 Parikh, P., Mehta, P., & Modi, C. K. (2011, June). Non-destructive Quality Evaluation of Chocolate Chip Cookies. In Communication Systems and Network Technologies (CSNT), 2011 International Conference on (pp. 694-698). IEEE.
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1 J. Illingworth and J. Kittler. “A survey of the Hough transform”, CVGIP, vol. 44, pages 87-1 16.1988
2 P.V.C Hough. “A method and means for recognizing complex patterns”, U.S. patent 3.069.654. (1962)
3 R. 0. Duda, and P.E. Han. “Use of the Hough transform to detect lines and curves in pictures”, Communications of the ACM. Vol. 15, No 1, 11-15, 1972
4 R Gonzalez. and R. E. Woods, “Digital image processing”, Addison-Wesley Publishing, (1992)
5 R. Krishnapuram. and D. Casasent, “Hough space transformation for discrimination and distortion estimation”, CVGIP, vol. 38, PP 299-316.1987
6 P.K. Sinha, F.Y. Chen. R.E.N. Horne, “Recognition and location of shapes in the Hough pattern space”, IEE Elect. Div. Colloq. on Hough transforms 19931106. Savoy place, London, 1993
7 J. Montenegro Joo, L. da F. Coata and R. KBberle, “Geometric transformation invariant pattern recognition with Hough transforms and distance discriminator neural networks”, presented at the Workshop sobre Computapio de Alto Descmpenho pam Processamenfo de Sinars, Si0 Carlos, SP, Brazil, 1993.
8 R. Scha1koff. “Digital image processing and computer vision”, John Wiley & Sons Inc. (1989)
9 G. Gesig G. and F. Klein., “Fast contour identification through efficient Hough transform and simplified interpretation strategy”, UCPR-8. Paris. 498.500. (1986).
10 J. Montenegro Joo. “A Polar-Hough-Transform Based Algorithm for the Translation, Orientation and Size-Scale Invariant Pattern Recognition of Polygonal Objects”, UMI Dissertations l.D03769, 1998.
11 J. Montenegro Joo. “Geometric-Transformations Invariant Pattern Recognition in the Hough Space”, Doctoral Degree Project. Cybernetic Vision Research Group, Instituto de Ffsica tic Sao Carlos (IFSC), Dpto. de Fisica c Informtica. Universidade de San Paulo (USP). San CarIes, SP. Brazil. (August 1994).
12 J. Montenegro Joo. “Invariant recognition of rectangular biscuits through an algorithm operating exclusively in Hough Space. Flawed pieces detection”. Revista de Investigacion de Fisica, Vol 5, No 1,2 ,2002
13 Montenegro Joo. “Hough Transform based Algorithm for the automatic Invariant Recognition of Rectangular Chocolates, Detection of defective pieces”, Industrial Data, Lima, Peru.Vol. 9, No 2, 2006
14 J. Montenegro Joo, (2007). “Hough-transform based automatic invariant recognition of metallic corner-fasteners”, SISTEMAS E INFO RMA TICA. Industrial Data, Lima, Peru. Vol 10, No 1, 2007
15 Yangxing Liu, Ikenaga. T, Goto.S. “A Novel Approach of Rectangular Shape Object Detection in Color Images Based on an MRF Model” In Proceedings of 5th IEEE International Conference on Cognitive Informatics, 2006
16 Amit Konar. “Artificial Intelligence and soft computing: Behavioral and Cognitive modeling of the Human brain”, CRC press (2000)
17 Biswas B., Konar A., Mukherjee A.K. “Image matching with fuzzy moment descriptors”. Engineering Applications of Artificial Intelligence, 14 (1), pp. 43-49, 2001
18 Jignesh Sarvaiya, Suprava Patnaik & Hemant Goklani.” Image Registration using NSCT and Invariant Moment”,International Journal of Image Processing ISSN (1985-2304) Vol. (4),issue (2),pp 119-130,May 2010.
Mr. Pulivarthi Srinivasa Rao
- India
Mr. Sheli Sinha Chaudhuri
- India
Mr. Romesh Laishram
MANIPUR INSTITUTE OF TECHNOLOGY - India