Feasibility study on automated recognition of allergenic pollen: Grass, birch and mugwort

Aerobiologia

Volumn 22, Issue 4, 2006, Pages 275-284

  Chen, Chun ^a,c   Hendriks, Emile A ^a   Duin, Robert P W ^a   Reiber, Johan H C ^b   Hiemstra, Pieter S ^b   De Weger, Letty A ^b   Stoel, Berend C ^b  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

^c UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Airborne pollen; Automated recognition; Image analysis; Pore colpus; Shape features; Statistical gray level features

Indexed keywords

ARTICLE; BIRCH; DIGITAL IMAGING; FEASIBILITY STUDY; GRASS; MICROSCOPY; NONHUMAN; POLLEN ALLERGY; POLLEN ANALYSIS; PRIORITY JOURNAL;

ARTEMISIA VULGARIS;

EID: 33845875984     PISSN: 03935965     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10453-006-9040-0     Document Type: Article

References (23)

1. Bonton, P., Boucher, A., Thonnat, M., Belmonte, J., Galan, C., Bonton, P., & Tomczak, R. (2001). Color image in 2D and 3D microscopy for the automation of pollen rate measurement. Image Analysis and Stereology, 20(Suppl 1), 527-532.
2. Boucher, A., Hidalgo, P. J., Thonnat, M., Belmonte, J., Galan, C., Bonton, P., & Tomczak, R. (2002). Development of a semi-automatic system for pollen recognition. Aerobiologia, 18, 195-201.
3. Cernadas, E., Formella, A., & Rodríguez-Damiá, M. (2004). Pollen classification using brightness-based and shape-based descriptors. 17th International Conference on Pattern Recognition (ICPR '04) (vol. 2, pp. 212-215). Cambridge, UK.
4. Costa, L. F., & Cesar, R. M. (2001a). Shape characterization: some general descriptors. In Shape analysis and classification (pp. 422-439). Washington, DC: CRC Press.
5. Costa, L. F., & Cesar, R. M. (2001b). 2D Shape representation: Hough transforms. In Shape analysis and classification (pp 376-400). Washington, DC: CRC Press.
6. Dasarathy, B. V. (1991). Nearest neighbour norms: NN pattern classification techniques. Los Alamitos, CA: IEEE Computer Society Press.
7. Egan, J. P. (1975). Signal detection theory and ROC analysis. Academic, New York, USA.
8. Hough, P. C. V. (1962). Methods and means for recognizing complex patterns. U.S. Patent 3,069,654.
9. Illingworth, J., & Kittler, J. (1988). A survey of the Hough transform. Computer Vision, Graphics, and Image Processing, 44, 87-116.
10. Kittler, J. (1975). Mathematical methods of feature selection in pattern recognition. International Journal of Man-Machine Studies, 7, 609-637.
11. Lachenbruch, P. A., & Mickey, M. R. (1968). Estimation of error rates in discriminant analysis. Technometrics, 10, 1-11.
12. Li, P., & Flenley, J. R. (1999). Pollen texture identification using neural networks. Grana, 38, 59-64.
13. McLachlan, G. J. (1992). Discriminant analysis and statistical pattern recognition. New York: Wiley.
14. Pratt, W. K. (1978). Image detection and registration: template matching. Digital image processing (pp. 651-653). New York, USA: Wiley.
15. Ronneberger, O., Schultz, E., & Burkhardt, H. (2002). Automated pollen recognition using 3D volume images from fluorescence microscopy. Aerobiologia, 18, 107-115.
16. Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B, 36, 111-147.
17. Webb, A. R. (2002a). Clustering: hierarchical methods. Statistical pattern recognition (pp. 362-370). England: Wiley.
18. Webb, A. R. (2002b). Density estimation - parametric: normal-based models. Statistical pattern recognition (pp. 34-40). England: Wiley.
19. Weber, R. W. (1998). Pollen identification. Annals of Allergy, Asthma & Immunology, 80, 141-145.
20. Young, I. T., Gerbrands, J. J., & Van Vliet, L. J. (1998a). Chapter 51.10: Techniques: shading correction. In V. K. Madisetti & D. B. Williams (Eds.), The digital signal processing handbook (pp. 51:63-51:80). USA: CRC Pr I LIc.
21. Young, I. T., Gerbrands, J. J., & Van Vliet, L. J. (1998b). Chapter 51.10: Techniques: segmentation. In V. K. Madisetti & D. B. Williams (Eds.), The digital signal processing handbook (pp. 51:63-51:80). USA: CRC Pr I LIc.
22. Young, I. T., Gerbrands, J. J., & Van Vliet, L. J. (1998c). Chapter 51.9: Algorithms. In V. K. Madisetti & D. B. Williams (Eds.), The digital signal processing handbook (pp. 51:33-51:63). USA: CRC Pr I LIc.
23. Zhang, Y., & Wang, R. (2004). A combined method for texture analysis and its application. The International Conference on Computational Science (ICCS), part I (pp. 413-416). Krakow, Poland.