Hybrid method for cereal grain identification using morphological and color features

Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems

Volumn , Issue , 2006, Pages 870-873

  Abdellaoui, Mehrez ^a   Douik, Ali ^a   Annabi, Mohamed ^b  

^a UNIVERSITY OF MONASTIR   (Tunisia)

^b UNIVERSITY OF TUNIS   (Tunisia)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL PRODUCTS; DECISION MAKING; FEATURE EXTRACTION; FUZZY INFERENCE; FUZZY SETS; FUZZY SYSTEMS; HYBRID SENSORS; PATTERN RECOGNITION; PROBLEM SOLVING; STATISTICAL METHODS;

COLOR FEATURES; HYBRID METHODS; INTERNATIONAL CONFERENCES; STATISTICAL PATTERN RECOGNITION;

FUZZY LOGIC;

EID: 47349109815     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICECS.2006.379927     Document Type: Conference Paper

References (16)

1. Barker D A; Vouri T A; Hegedus M R; Myers D G (1992). The use of ray parameters for the discrimination of Australian wheat varieties. Plant Varieties and Seeds, 5(1), 35-45.
2. Barker D A; Vouri T A; Myers DG (1992). The use of slice and aspect ratio parameters for the discrimination of Australian wheat varieties. Plant Varieties and Seeds, 5(1), 47-52.
3. Barker D A; Vouri T A; Myers D G (1992). The use of Fourier descriptors for the discrimination of Australian wheat varieties. Plant Varieties and Seeds, 5(1), 93-102.
4. Barker D A; Vouri T A; Hegedus M R; Myers D G (1992). The use of Chebychev coefficients for the discrimination of Australian wheat varieties. Plant Varieties and Seeds, 5(1), 103-111.
5. Keefe P D (1992). A dedicated wheat grain image analyzer. Plant Varieties and Seeds, 5(1), 27-33.
6. Sapirstein H D; Kohler J M (1995). Physical uniformity of graded railcar and vessel shipments of Canada Western Red Spring wheat determined by digital image analysis. Canadian Journal of Plant Science 75(2), 363-369
7. Paliwal J; Shashidhar N S; Jayas D S (1999). Grain kernel identification using kernel signature. Transactions of the ASAE, 42(6), 1921-1924.
8. Majumdar S; Jayas D S (2000). Classification of cereal grains using machine vision. I. Morphology models. Transactions of the ASAE, 43(6), 1669-1675.
9. Sayeed M S; Whittaker A D; Ksehtarnavaz N D (1995). Snack quality evaluation method based on image feature extraction and neural network prediction. Transactions of the ASAE, 38(4), 1239-1245.
10. Ozer N; Engel B A; Simon J E (1995). Neural network for quality sorting and grading of cantaloupes by multiple non-destructive sensors. ASAE Paper No. 95-3218.
11. Shibata T; Iwao K; Takano T (1996). Evaluating tomato ripeness using a neural network. Journal of the Society of High Technology in Agriculture, 8(3), 60-167.
12. Ghazanfari A; Wulfsohn D; Irudayaraj J (1998). Machine vision grading of pistachio nuts using gray-level histogram. Canadian Agricultural Engineering, 40(1), 61-66.
13. Visen N S; J. Paliwal J; Jayas D S; White NDG (2002). Specialist Neural Networks for Cereal Grain Classification Biosystems Engineering, 82 (2), 151-159.
14. Paliwal J; Visen N S; Jayas D S (2001). Evaluation of neural network architectures for cereal grain classification using morphological features. Journal of agricultural Engineering Research, 79(4), 361-370.
15. Paliwal J; Visen N S; Jayas D S; White NDG (2003). Cereal Grain and Dockage Identification using Machine Vision. Biosystems Engineering, 85(1), 51-57.
16. Abdellaoui M; Douik A; Annabi M (2006). Détermination des critères de forme et de couleur pour la classification des grains de céréales. Nouvelles Tendances Technologiques en Génie Electrique et Informatique, GEI'2006, pp. 393-402, Hammamet,Tunisia.