Evaluation of different pattern recognition techniques for apple sorting

Biosystems Engineering

Volumn 99, Issue 2, 2008, Pages 211-219

  Kavdir, I ^a   Guyer, D E ^b  

^a ÇANAKKALE ONSEKIZ MART UNIVERSITY   (Turkey)

^b Michigan State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; IMAGE CLASSIFICATION; NEURAL NETWORKS;

APPLE SORTING; BLUSH PERCENTAGE; PERCEPTRON NEURAL NETWORKS;

FRUITS;

MALUS X DOMESTICA;

EID: 38549101270     PISSN: 15375110     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystemseng.2007.09.019     Document Type: Article

References (15)

1. Alchanatis V., Peleg K., and Ziv M. Classification of tissue culture segments by colour machine vision. Journal of Agricultural Engineering Research 55 (1993) 299-311
2. Chen Y R; Nguyen M; Park B (1997). Improving performance of neural network classifiers by input data pretreatment with principal component analysis. ASAE Paper No. 97-3050
3. Hahn F., Irineo L., and Hernandez G. Spectral detection and neural network discrimination of Rhizopus stolonifer spores on red tomatoes. Biosystems Engineering 89 (2004) 93-99
4. Howard D., and Beale M. Neural Network Toolbox (1992), The Math Works Inc., Natick
5. Hung Y C; Morita K; Shewfelt R; Resurreccion A V A; Prussia S (1993). Color evaluation of apples. ASAE Paper No. 93-6541
6. Kavdi{dotless}r I., and Guyer D.E. Apple grading using fuzzy logic. Turkish Journal of Agriculture and Forestry 27 (2003) 375-382
7. Kim J., Mowat A., Poole P., and Kasabov N. Linear and non-linear pattern recognition models for classification of fruit from visible-near infrared spectra. Chemometrics and Intelligent Laboratory Systems 51 (2000) 201-216
8. Kirsten J., Tygesen K.T., Kesmir C., Skovgaard I.M., and Sondergaard I. Classification of potato varieties using isoelectrophoretic focusing patterns, neural nets, and statistical methods. Journal of Agricultural Food Chemistry 45 (1997) 158-161
9. Leemans V., Magein H., and Destain M.F. On-line fruit grading according to their external quality using machine vision. Biosystems Engineering 83 (2002) 397-404
10. Luo X., Jayas D.S., and Symons S.J. Comparison of statistical and neural network methods for classifying cereal grains using machine vision. Transactions of the ASAE 42 2 (1999) 413-419
11. Miller W.M., Throop J.A., and Upchurch B.L. Pattern recognition models for spectral reflectance evaluation of apple blemishes. Postharvest Biology and Technology 14 (1998) 11-20
12. Ozer N., Engel B.A., and Simon J.E. Fusion classification techniques for fruit quality. Transactions of the ASAE 38 6 (1995) 1927-1934
13. Penza M., Cassano G., Tortorella F., and Zaccaria G. Classification of food, beverages and perfumes by WO3 thin-film sensors array and pattern recognition techniques. Sensors and Actuators B 73 (2001) 76-87
14. USDA Agricultural Marketing Service (1976). United States Standards for Grades of Apples. Washington, D.C.
15. Venables W N; Ripley B D (1994). Modern Applied Statistics with S-plus, pp 329-348. Springer-Verlag Inc., Berlin