Automated detection of fish bones in Salmon fillets using X-ray testing

Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010

Volumn , Issue , 2010, Pages 46-51

  Mery, Domingo ^a   Lillo, Iván ^a   Loebel, Hans ^a   Riffo, Vladimir ^a   Soto, Alvaro ^a   Cipriano, Aldo ^a   Aguilera, José Miguel ^a  

^a PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE   (Chile)

Author keywords

Automated visual inspection; Fish inspection; Quality control; X ray imaging

Indexed keywords

AUTOMATED DETECTION; AUTOMATED VISUAL INSPECTION; BAND PASS FILTERING; BONE DETECTION; CROSS VALIDATION; DETECTION PERFORMANCE; DETECTION WINDOWS; FISH FILLET; FLAT PANEL DETECTORS; HIGH RESOLUTION; HUMAN OPERATOR; MISCLASSIFICATIONS; MORPHOLOGICAL OPERATIONS; SALMON FILLET; SENSE OF TOUCH; THRESHOLDING; TRAINING PHASE; X RAY MACHINE; X-RAY IMAGE; X-RAY TESTING; XRAY IMAGING;

AUTOMATION; BONE; CHEMICAL DETECTION; CLASSIFIERS; COMPUTER VISION; DETECTORS; INSPECTION; MATHEMATICAL MORPHOLOGY; PIXELS; QUALITY ASSURANCE; X RAY ANALYSIS; X RAY APPARATUS; X RAYS;

FISH;

EID: 78751658571     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PSIVT.2010.15     Document Type: Conference Paper

References (29)

1. E. Davies, Image Processing for the Food Industry. World Scientific, 2000.
2. J. Kwon, J. Lee, and W. Kim, "Real-time detection of foreign objects using x-ray imaging for dry food manufacturing line," in Proceedings of IEEE International Symposium on Consumer Electronics (ISCE 2008), April 2008, pp. 1-4.
3. R. Haff and N. Toyofuku, "X-ray detection of defects and contaminants in the food industry," Sensing and Instrumentation for Food Quality and Safety, vol. 2, no. 4, pp. 262-273, 2008.
4. M. Graves, "X-ray bone detection in further processed poultry production," Machine Vision for the Inspection of Natural Products, pp. 421-449, 2003.
5. J. Jiang, H. Chang, K. Wu, C. Ouyang, M. Yang, E. Yang, T. Chen, and T. Lin, "An adaptive image segmentation algorithm for x-ray quarantine inspection of selected fruits," Computers and Electronics in Agriculture, vol. 60, pp. 190-200, 2008.
6. Y. Ogawa, N. Kondo, and S. Shibusawa, "Inside quality evaluation of fruit by X-ray image," International IEEE/ASME Conference on Advanced Intelligent Mechatronics (AIM2003), vol. 2, pp. 1360-1365, July 2003.
7. R. Haff and D. Slaughter, "Real-time X-ray inspection of wheat for infestation by the granary weevil, sitophilus granarius (l.)," Transactions of the American Society of Agricultural Engineers, vol. 47, pp. 531-537, 2004.
8. K. Andersen, "X-ray techniques for quality assessment," in Quality of Fish from Catch to Consumers, J. B. Luten, J. Oehlenschläeger, and G. Olafsdottir, Eds. Wageningen Academic Publ., 2003, pp. 283-286.
9. Y. Han and P. Shi, "An Efficient Approach for Fish Bone Detection Based on Image Preprocessing and Particle Swarm Clustering," Communications in Computer and Information Science, vol. 21, pp. 940-948, 2007.
10. A. Lorencs, I. Medniek, and J. Sinica-Sinavskis, "Fast object detection in digital grayscale images," Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences, vol. 63, no. 3, pp. 116-124, 2009.
11. J. Thielemann, T. Kirkhus, T. Kavli, Schumann-Olsen, O. Haugland, and H. Westavik, "System for estimation of pin bone positions in pre-rigor salmon," Lecture Notes in Computer Science, vol. Advanced Concepts for Intelligent Vision Systems (ACIVS2007), no. 4678, pp. 888-896, 2007.
12. Y. Akazawa, S. Watanabe, S. Nobukiyo, H. Iwatake, Y. Seki, T. Umehara, K. Tsutsumi, and I. Koizuka, "The management of possible fishbone ingestion," Auris Nasus Larynx, vol. 31, no. 4, pp. 413-416, 2004.
13. R. Gonzalez and R. Woods, Digital Image Processing, 3rd ed. Pearson, Prentice Hall, 2008.
14. H. Haken and H. Wolf, The Physics of Atoms and Quanta: Introduction to Experiments and Theory, 6th ed. Berlin, Heidelberg: Springer, 2000.
15. R. Halmshaw, Non-Destructive-Testing, 2nd ed. London: Edward Arnold, 1991.
16. M. Spahn, M. Strotzer, V. Markus, S. B. B. Geiger, G. Hahm, and S. Feuerbach, "Digital radiography with a large-area, amorphous-silicon, flat-panel X-Ray detector system," Investigative Radiology, vol. 35, no. 4, pp. 260-266, 2000.
17. J. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. PAMI-8, no. 6, pp. 679-698, 1986.
18. M. Nixon and A. Aguado, Feature Extraction and Image Processing, 2nd ed. Academic Press, 2008.
19. R. Haralick, "Statistical and structural approaches to texture," Proc. IEEE, vol. 67, no. 5, pp. 786-804, 1979.
20. A. Kumar and G. Pang, "Defect detection in textured materials using gabor filters," IEEE Trans. on Industry Applications, vol. 38, no. 2, pp. 425-440, 2002.
21. T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971-987, Jul 2002.
22. H.-L. Wei and S. Billings, "Feature subset selection and ranking for data dimensionality reduction," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 1, pp. 162-166, Jan. 2007.
23. K. Mao, "Identifying critical variables of principal components for unsupervised feature selection," IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 35, no. 2, pp. 339-344, April 2005.
24. MathWorks, Matlab Toolbox of Bioinformatics: User's Guide. Mathworks Inc., 2007.
25. C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.
26. A. Jain, R. Duin, and J. Mao, "Statistical pattern recognition: A review," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, 2000.
27. J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis. Cambridge University Press, 2004.
28. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, August 2003.
29. T. Mitchell, Machine Learning. Boston: McGraw-Hill, 1997.