Abstract
This work focuses on the development of a computer vision system for the automatic on-line inspection and classification of Satsuma segments. During the image acquisition the segments are in movement, wet and frequently in contact with other pieces. The segments are transported over six semi-transparent conveyor belts that advance at speed of 1 m/s. During on-line operation, the system acquires images of the segments using two cameras connected to a single computer and process the images in less than 50 ms. Extracting morphological features from the objects, the system identifies automatically pieces of skin and row material and separates entire segments from broken ones, discriminating between those with slight or large breaking degree. Combinations of morphological parameters were employed to decide the quality of each segment, classifying correctly 95% of sound segments.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Blasco, J., Aleixos, N., Moltó, E.: Machine vision system for automatic quality grading of fruit. Biosystems Engineering 85(4), 415–423 (2003)
Blasco, J., Aleixos, N., Moltó, E.: Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm. Journal of Food Engineering (2007), doi:10.1016/j.jfoodeng.2007.03.027
Aleixos, N., Blasco, J., Navarrón, F., Moltó, E.: Multispectral inspection of citrus in real-time using machine vision and digital signal processors. Computers and Electronics in Agriculture 33(2), 121–137 (2002)
Aranda, J.D., Tomás, L.M.: Automatic process for the stoning peach inspection and classification phase in a packaging fruits factory using artificial vision techniques. In: Robotics and automated machinery for bio-productions, BIO-ROBOTICS 97, Gandía (Valencia), Spain, pp. 77–82 (1997)
Vizmanos, J.G., Fuentes, L.M., Gutierrez, J.A.: Splinter detection in half-cut peaches. In: SPIE, vol. 3208, pp. 277–286 (1997)
Tomás, L.M., Torres, R., López, J.A., Doméénech, G.: Colour image processing and artificial vision techniques, used for detection, segmentation and identification of satsuma slices. In: Third international conference on automation, robotics and computer vision III, pp. 1955–1959 (1994)
Blasco, J., Arias, R., Cubero, S., Alegre, S., Alamar, M.C., Juste, F., Moltó, E.: Automatic inspection of satsuma slices using machine vision. In: AgEng 04, Leuven, Belgium, EurAgEng Paper N 243 (2004)
Gonzalez, R.C., Wintz, P.: Digital Image Processing, 2nd edn., pp. 396–397. Addison Wesley, New York (1987)
Throop, J.A., Aneshanesly, D.J.: Improvements in an image processing algorithm to find new and old bruises. In: International Winter Meeting of the American Society of Agricultural Engineers, ASAE Paper No. 93-6534 (1993)
Miao, Z.J., Gandelin, M.H., Yuan, B.Z.: A new image shape analysis approach and its application to flower shape analysis. Image and vision computing 24(10), 1112–1115 (2006)
Zhang, D.S., Lu, G.: A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures. In: Proc. of ICIMADE 01, Fargo, ND, USA, pp. 1–9 (2001)
Tao, Y., Morrow, C.T., Heinemann, P.H., Sommer, H.J.: Fourier-Based Separation Technique for Shape Grading of Potatoes Using Machine Vision. Transactions of the ASAE 38(3), 949–957 (1995)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Blasco, J., Cubero, S., Arias, R., Gómez, J., Juste, F., Moltó, E. (2007). Development of a Computer Vision System for the Automatic Quality Grading of Mandarin Segments. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_58
Download citation
DOI: https://doi.org/10.1007/978-3-540-72849-8_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
Online ISBN: 978-3-540-72849-8
eBook Packages: Computer ScienceComputer Science (R0)