Automated Design of a Computer Vision System for Visual Food Quality Evaluation

Food and Bioprocess Technology

Volumn 6, Issue 8, 2013, Pages 2093-2108

  Mery, Domingo ^a   Pedreschi, Franco ^a   Soto, Alvaro ^a  

^a PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE   (Chile)

Author keywords

Classification; Computer vision; Feature extraction; Feature selection; Food quality evaluation; Image analysis; Image processing; Image segmentation; Pattern recognition

Indexed keywords

AUTOMATED DESIGN; CLASSIFICATION PERFORMANCE; COMPUTER VISION PROBLEMS; COMPUTER VISION SYSTEM; FOOD QUALITY; HYPOTHESIS SPACE; MATLAB TOOLBOXES; RESEARCH EFFORTS;

COMPUTER VISION; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE SEGMENTATION; LEARNING SYSTEMS; PATTERN RECOGNITION;

CLASSIFICATION (OF INFORMATION);

EID: 84880960512     PISSN: 19355130     EISSN: 19355149     Source Type: Journal    
DOI: 10.1007/s11947-012-0934-2     Document Type: Article

References (61)

1. Aguilera, J., Cipriano, A., Erana, M., Lillo, I., Mery, D., Soto, A. (2007). Computer vision for quality control in Latin American food industry, a case study. In Int. conf. on computer vision (ICCV2007): workshop on computer vision applications for developing countries (pp. 1-8).
2. Bishop, C. (2005). Neural networks for pattern recognition. London: Oxford University Press.
3. Bishop, C. M. (2006). Pattern recognition and machine learning. New York: Springer.
4. Chellappa, R., & Bagdazian, R. (1984). Fourier coding of image boundaries. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6(1), 102-105.
5. Cheng, H., Jiang, X., Sun, Y., Wang, J. (2001). Color image segmentation: advances and prospects. Pattern Recognition, 34(12), 2259-2281. ISSN 0031-3203.
6. Dalal, N., & Triggs, B. (2005). Histograms of oriented gradients for human detection. In Conference on computer vision and pattern recognition (CVPR2005) (Vol. 1, pp. 886-893).
7. Danielsson, P.-E. (1978). A new shape factor. Computer Graphics and Image Processing, 7, 292-299.
8. Davies, E. (2000). Image processing for the food industry. Singapore: World Scientific.
9. Diaz, R., Gil, L., Serrano, C., Blasco, M., Moltó, E., Blasco, J. (2004). Comparison of three algorithms in the classification of table olives by means of computer vision. Journal of Food Engineering, 61(1), 101-107.
10. Duda, R., Hart, P., Stork, D. (2001). Pattern classification (2nd ed.). New York: Wiley.
11. Escalante, H., Montes, M., Sucar, L. (2009). Particle swarm model selection. The Journal of Machine Learning Research, 10, 405-440.
12. Fitzgibbon, A., Pilu, M., Fisher, R. (1999). Direct least square fitting ellipses. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5), 476-480.
13. Flusser, J., & Suk, T. (1993). Pattern recognition by affine moment invariants. Pattern Recognition, 26(1), 167-174.
14. Gonzalez, R., & Woods, R. (2008). Digital image processing (3rd ed.). Upper Saddle River: Prentice-Hall.
15. Gupta, L., & Srinath, M. D. (1987). Contour sequence moments for the classification of closed planar shapes. Pattern Recognition, 20(3), 267-272.
16. Haff, R., & Slaughter, D. (2004). Real-time X-ray inspection of wheat for infestation by the granary weevil, sitophilus granarius (l.). Transactions of the American Society of Agricultural Engineers, 47, 531-537.
17. Haff, R., & Toyofuku, N. (2008). X-ray detection of defects and contaminants in the food industry. Sensing and Instrumentation for Food Quality and Safety, 2(4), 262-273.
18. Haralick, R. (1979). Statistical and structural approaches to texture. Proceedings of IEEE, 67(5), 786-804.
19. Hastie, T., Tibshirani, R., Friedman, J. (2001). The elements of statistical learning: Data mining, inference, and prediction (corrected ed.). New York: Springer.
20. Hu, M.-K. (1962). Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, IT(8), 179-187.
21. Inen, M. P., Pietikäinen, M., Hadid, A., Zhao, G., Ahonen, T. (2011). Computer vision using local binary patterns (Vol. 40). London: Springer.
22. Irudayaraj, J., & Reh, C. (eds.) (2008). Nondestructive testing for food quality. Ames: IFT Press.
23. Jain, A., Duin, R., Mao, J. (2000). Statistical pattern recognition: a review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1), 4-37.
24. Jiang, J., Chang, H., Wu, K., Ouyang, C., Yang, M., Yang, E., Chen, T., Lin, T. (2008). An adaptive image segmentation algorithm for X-ray quarantine inspection of selected fruits. Computers and Electronics in Agriculture, 60, 190-200.
25. Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. In International joint conference on artificial intelligence (Vol. 14, pp. 1137-1145).
26. Kumar, A., & Pang, G. (2002). Defect detection in textured materials using gabor filters. IEEE Transactions on Industry Applications, 38(2), 425-440.
27. Kwon, J., Lee, J., Kim, W. (2008). 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) (pp. 1-4). doi: 10. 1109/ISCE. 2008. 4559552.
28. Leemans, V., & Destain, M. F. (2004). A real-time grading method of apples based on features extracted from defects. Journal of Food Engineering, 61(1), 83-89.
29. Leiva, G., Mondragon, G., Mery, D., Aguilera, J. (2011). The automatic sorting using image processing improves postharvest blueberries storage quality. In Proceedings of international congress on engineering and food.
30. Leon, K., Mery, D., Pedreschi, F., Leon, J. (2006). Color measurement in l*a*b* units from rgb digital images. Food Research International, 39(10), 1084-1091.
31. Mao, K. (2005). Identifying critical variables of principal components for unsupervised feature selection. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 35(2), 339-344.
32. Marsland, S. (2009). Machine learning: an algorithmic perspective. London: Chapman & Hall.
33. MathWorks (2003). Image processing toolbox for use with MATLAB: user's guide. The MathWorks Inc.
34. MathWorks (2007). Matlab toolbox of bioinformatics: user's guide. Mathworks Inc.
35. MathWorks (2009). Neural network toolbox for use with MATLAB: user's guide. The MathWorks Inc.
36. Mery, D. (2011). BALU: a toolbox Matlab for computer vision, pattern recognition and image processing. http://dmery. ing. puc. cl/index. php/balu.
37. Mery, D., & Filbert, D. (2002). Classification of potential defects in automated inspection of aluminium castings using statistical pattern recognition. In 8th European conference on non-destructive testing (ECNDT 2002), Barcelona, 17-21 June 2002 (pp. 1-10).
38. Mery, D., & Pedreschi, F. (2005). Segmentation of colour food images using a robust algorithm. Journal of Food Engineering, 66(3), 353-360.
39. Mery, D., & Soto, A. (2008). Features: the more the better. In ISCGAV'08: Proceedings of the 8th conference on signal processing, computational geometry and artificial vision (pp. 46-51). Wisconsin: Stevens Point.
40. Mery, D., Chanona-Pérez, J., Soto, A., Aguilera, J., Cipriano, A., Veléz-Rivera, N., Arzate-Vázque, I., Gutiérrez-López, G. (2010). Quality classification of corn tortillas using computer vision. Journal of Food Engineering, 101(4), 357-364.
41. Mery, D., Lillo, I., Loebel, H., Riffo, V., Soto, A., Cipriano, A., Aguilera, J. (2011). Automated fish bone detection using X-ray imaging. Journal of Food Engineering, 105(2011), 485-492.
42. Mitchell, T. (1997). Machine learning. Boston: McGraw-Hill.
43. Mu, Y., Yan, S., Liu, Y., Huang, T., Zhou, B. (2008). Discriminative local binary patterns for human detection in personal album. In IEEE conference on computer vision and pattern recognition (CVPR 2008) (pp. 1-8).
44. Nixon, M., & Aguado, A. (2008). Feature extraction and image processing (2nd ed.). New York: Academic.
45. Ogawa, Y., Kondo, N., Shibusawa, S. (2003). Inside quality evaluation of fruit by X-ray image. In 2003 IEEE/ASME international conference on advanced intelligent mechatronics, 2003. AIM 2003. Proceedings (Vol. 2, pp. 1360-1365).
46. Ojala, T., Pietikainen, M., Maenpaa, T. (2002). Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), 971-987.
47. Pedreschi, F., Mery, D., Mendoza, F., Aguilera, J. (2004). Classification of potato chips using pattern recognition. Journal of Food Science, 69(6), E264-E270.
48. Persoon, E., & Fu, K., (1977). Shape discrimination using Fourier descriptors. IEEE Transactions on Systems, Man, and Cybernetics, SMC-7(3), 170-179.
49. Polikar, H., Long, F., Ding, C. (2005). Criteria of max-dependency, max-relevance and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), 1226-1238.
50. Polikar, R. (2006). Ensemble based systems in decision making. IEEE Circuits and Systems Magazine, 3rd Quarter, 21-45.
51. Quevedo, R., Mendoza, F., Aguilera, J., Chanona, J., Gutiérrez-López, G. (2008). Determination of senescent spotting in banana (Musa cavendish) using fractal texture fourier image. Journal of Food Engineering, 84(4), 509-515.
52. Shawe-Taylor, J., & Cristianini, N. (2004). Kernel methods for pattern analysis. Cambridge: Cambridge University Press.
53. Sun, D. (2000). Inspecting pizza topping percentage and distribution by a computer vision method. Journal of Food Engineering, 44(4), 245-249.
54. Sun, D.-W. (ed.) (2008). Computer vision technology for food quality evaluation. New York: Academic.
55. Szeliski, R. (2011). Computer vision: algorithms and applications. New York: Springer.
56. Tan, J. (2004). Meat quality evaluation by computer vision. Journal of Food Engineering, 61(1), 27-35.
57. Viola, P., & Jones, M. (2004). Robust real-time object detection. International Journal of Computer Vision, 57(2), 137-154.
58. Webb, A. (2005). Statistical pattern recognition. England: Wiley.
59. Wei, H.-L., & Billings, S. (2007). Feature subset selection and ranking for data dimensionality reduction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(1), 162-166, Jan.
60. Witten, I., & Frank, E., (2005). Data mining: practical machine learning tools and techniques (2nd. ed.). San Mateo, CA: Morgan Kaufmann.
61. Zahn, C., & Roskies, R., (1971). Fourier descriptors for plane closed curves. IEEE Transactions on Computers, C-21(3), 269-281.