Vehicle guidance parameter determination from crop row images using principal component analysis

Journal of Agricultural and Engineering Research

Volumn 75, Issue 3, 2000, Pages 257-264

  Pinto, F A C ^a   Reid, J F ^b   Zhang, Q ^b   Noguchi, N ^c  

^a FEDERAL UNIVERSITY OF VIÇOSA   (Brazil)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c HOKKAIDO UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0043283136     PISSN: 00218634     EISSN: None     Source Type: Journal    
DOI: 10.1006/jaer.1999.0501     Document Type: Article

References (20)

1. Ahmad I S; Reid J F (1996). Evaluation of colour representations for maize images. Journal of Agricultural Engineering Research, 63, 185-196
2. Billingsley J; Schoenfish M (1997). The successful development of a vision guidance system for agriculture. Computers and Electronics in Agriculture, 16, 147-163
3. Gerrish J B; Stockman G; Mann L; Hu G (1987). Path-finding by image processing in agricultural field operation. Transactions of the SAE, 95(5), 540-554
4. Gonzalez R C; Woods R E (1992). Digital Image Processing. Addison-Wesley Publishing Company, Reading, MA
5. Hotelling H (1933). Analysis of a complex of statistical variables into principal components. The Journal of Educational Psychology
6. Isebrands J G; Crow T R (1975). Introduction to uses and interpretation of principal component analysis in foresty biology. USDA Forest Service General Technical Report NC-17
7. Jolliffe I T (1986). Principal Component Analysis, Springer Series in Statistics. Springer-Verlag, New York Inc., NY
8. Kirby M; Sirovich L (1990). Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(1), 103-108
9. Murakami H; Kumar V K (1982). Efficient calculation of primary images from a set of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 4(5), 511-515
10. Murase H; Nayar S K (1995). Visual learning and recognition of 3-D objects from appearance. International Journal of Computer Vision, 14, 5-24
11. Noguchi N; Ishii K; Terao H (1997). Development of an agricultural mobile robot using a geomagnetic direction sensor and image sensors. Journal of Agricultural Engineering Research, 67, 1-15
12. Noguchi N; Reid J F; Zhang Q; Tian L F (1998a). Vision intelligence for precision farming using fuzzy logic optimized genetic algorithm and artificial neural network. ASAE Paper No 98-3034
13. Noguchi N; Reid J F; Will J; Benson E R; Stombaugh T S (1998b). Vehicle automation system based on multisensor integration. ASAE Paper No 98-3111
14. Reid J F (1987). The development of computer vision algorithms for agricultural vehicle guidance. Unpublished PhD thesis Texas A and M University, College Station, TX
15. Slaughter D C; Chen P; Curley R G (1997). Computer vision guidance system for precision cultivation. ASAE Paper No 97-1079
16. Steward B; Tian L F (1998). Real-time machine vision weed sensing. ASAE Paper No 98-7006
17. Tou J T; Gonzalez R C (1974). Pattern Recognition Principles. Addison-Wesley Publishing Company, Reading, MA
18. Tillet N D (1991). Automatic guidance sensors for agricultural field machines: a review. Journal of Agricultural Engineering Research, 50, 167-187
19. Turk M; Pentland A (1991). Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1), 71-86
20. Von Qualen K E; Hummel J M; Reid J F (1991). Machine vision system for field sprayer guidance. In: Proceedings of the Automated Agriculture for the 21st Century, pp 192-200