Email this article 
Open Access
Subscription or Fee Access
Dimensional Analysis and Segmentation of Touching Rice Grains
Abstract
This paper presents a novel image processing algorithm that has been developed and tested for the accuratesegmentation of contacting rice grains in digital images. This algorithm uses general shape properties for initial decision making, then use Erosion and dilation technique for segmented the contacting grains at the point of contact. This approach offers a autious, decisive and reliable segmentation between small sets of contacting rice grains. The algorithm has been applied to test images with success in all cases. Results for contacting rice grains are compared with shape descriptors for non-touching grains. It is found that the impact of segmentation on the shape of target grains is negligible. This algorithm is of benefit for intelligent grain analysis
Keywords
References
D.M. Hobson, R. M. Carter. and Y. Yan. “Characterisation and identification of rice grains through digital image analysis”. IEEE Instrumentation and Measurement Technology conference Proceedings, Proceedings of IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland, 1-3 May 2007.
N. Sakai, S. Yonekawa, A. Matsuzaki, and H. Morishima, “Two -dimensional image analysis of the shape of rice and its application to separating varieties”. Journal of Food Engineering, vol. 27, no. 4, pp. 397-407, 1996.
“Survey on Basmati Rice”. UK Food Standards Agency, 2004, UK Government. Available from http://www.food.gov.uk
S. Kumar; S. H. Ong, S. Ranganath, T. C. Ong, and F. T. Chew, “A rule-based approach for robust clump splitting”. Pattern Recognition, vol. 39, no. 6, pp. 1088-1098, 2006.
G. Zhang, D. S. Jayas, and N. D. G. White. “Separation of touching grain kernels in an image by ellipse fitting algorithm”. Biosystems Engineering,vol. 92, no. 2, pp. 135-142, 2005.
W. X. Wang, “Binary image segmentation of aggregates based on polygonal approximation and classification of concavities”. Pattern Recognition, vol. 31, no. 10, pp. 1503-1524, 1998.
Chen Bo Yong and Ling P. Peter, “Evaluation of HIS Colorimetric system for intensity invariant spectral feature extraction”, paper no; 01-013108, An ASAE meeting presentation 2001, ASAE annual international meeting at Sacramento convention centre California, USA, July30- Aug1,
Dalen G. Van, “Determination of size distribution and percentage of broken kernels of rice using flatbed scanner and image analysis”, Food Research International, vol. 37: pp 51-58, March 2003, science direct.
D.A Luzuriago and M.O Balaban, “Color machine vision system: An alternative for color measurement, proceeding of the world congress of computers in agriculture and natural resources”, Iguacu Falls, Brazil ASAE Publication No. 701P301, pp 93-100, 13-15 March 2002.
C. L¨urig and T. Ertl. “Hierarchical volume analysis and visualization based on morphological operators”. In IEEE Visualization’98, pp335 – 341, 1998.
J. Parker. “A system for fast erosion and dilation of bi-level images” Science computer, Vol5(3): pp187 –198, 1990.
L. van Vliet and B. Verwer “A contour processing method for fast binary neighborhood operations”. Pattern Rec. Letters, Vol1(1): pp27 – 36, 1988.
R. van Boomgaard and R. van Balen.”Methods for fast morphological image transforms using bitmapped binary images”. CVGIP: Graphical Models and Image Processing, Vol54(3): pp252 – 258, 1992.
Kawamura Shuso, Natriga Motoyasu, Takekara Kazuhoro and Itoh Kazuhiko; “Development of an automatic Rice quality inspection system”, computers and electronics in agriculture, Vol40: pp 115-126,2003, IEEE.
W. Wang, W, and J. Paliwal. “Separation and identification of touching kernels and dockage components in digital images”. Canadian Biosystems Engineering, vol. 48, pp.701-718, 2006.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.