Username   Password       Forgot your password?  Forgot your username? 

 

Plant Leaves Recognition Combined PCA with AdaBoost.M1

Volume 15, Number 4, April 2019, pp. 1122-1130
DOI: 10.23940/ijpe.19.04.p7.11221130

Hui Chena, Haodong Zhub, and Xufeng Chaic

aEngineering Training Centre, Zhengzhou University of Light Industry, Zhengzhou,450002,China
bSchool of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China
cSida Foreign Language Primary School, Henan Experimental High School, Zhengzhou, 450000, China

 

(Submitted on November 8, 2018; Revised on December 10, 2018; Accepted on January 12, 2019)

Abstract:

In order to improve the overall performance of plant leaves recognition, this paper proposed a novel method combining PCA with AdaBoost.M1to recognize plant leaves. The proposed method firstly carries out the image preprocessing, which includes the image gray processing, the image binarization, and the edge extraction; extracts the 13 features of plant leaf with the characteristics of rotation invariance, proportion invariance, and translation invariance; subsequently employs PCA to reduce the dimensions of these feature parameters; and finally adopts the AdaBoost.M1 classifier to train and recognize the reduced-dimension plant leaf images. Simulation experiment results indicate that the proposed method is able to improve the overall performance effectively of plant leaves recognition.

References: 13

    1. Z. B. Wang, H. L. Li, Y. Zhu, et al., “Review of Plant Identification based on Image Processing,” Archives of Computational Methods in Engineering, Vol. 24, No. 3, pp. 637-654, 2017
    2. S. H. Lee, C. S. Chan, S. J. Mayo, et al., “How Deep Learning Extracts and Learns Leaf Features for Plant Classification,” Pattern Recognition, Vol. 71, pp. 1-13, 2017
    3. C. L. Zhang, S. W. Zhang, J. C. Yang, et al., “Apple Leaf Disease Identification using Genetic Algorithm and Correlation based Feature Selection Method,” International Journal of Agricultural and Biological Engineering, Vol. 10, No. 2, pp. 73-84, 2017
    4. H. D. Zhu and Z. Shen, “Plant Leaf Identification Method based on Cosine Theorem and K-Means,” Journal of Huazhong Normal University, Vol. 48, No. 5, pp. 650-655, 2014
    5. H. D. Zhu, H. C. Li, D. Wu, et al., “Image Texture Feature Extraction based on Cloud Platform and New ImageClass,” Journal of Computational Information Systems, Vol. 12, No. 17, pp. 6311-6321, 2015
    6. H. D. Zhu, D. Wu, H. C. Li, et al., “Plant Leaves Extraction Method under Complex Background based on Closed-Form Matting Algorithm,” Journal of Computational Information Systems, Vol. 11, No. 21, pp. 7633-7640, 2015
    7. H. X. Kan, L. Jin, and F. L. Zhou, “Classification of Medicinal Plant Leaf Image based on Multi-Feature Extraction,” Pattern Recognition and Image Analysis, Vol. 27, No. 3, pp. 581-587, 2017
    8. M. K. Hu, “Visual Pattern Recognition by Moment Invariants,” IRE Transaction Information Theory, Vol. 8, No. 2, pp. 179-187, 1962
    9. H. Tamura and S. Mori, “Textural Features Corresponding to Visual Perception,” IEEE Transactions on Systems, Man, & Cybernetics, Vol. 8, No. 6, pp. 460-473, 1978
    10. X. Q. Li, Q. Shao, and J. J. Wang, “Classification of Tongue Coating using Gabor and Tamura Features on Unbalanced Data Set,” in Proceedings of 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, pp. 108-109, USA, New York, 2013
    11. S. Y. Liao and T. Q. Huang, “Video Copy-Move Forgery Detection and Localization based on Tamura Texture Features,” 2013 6th International Congress on Image and Signal Processing (CISP), IEEE, pp. 864-868, USA, New York, 2013
    12. C. S. Lv, T. Zhang, and C. Lin, “Face Detection based on Skin Color and AdaBoost Algorithm,” in Proceedings of the 2017 29th Chinese Control and Decision Conference (CCDC), pp. 1363-1367, Chongqing, China, May 2017
    13. A. Minz and C. Mahobiya, “MR Image Classification using Adaboost for Brain Tumor Type,” in Proceedings of the 2017 IEEE 7th International Advance Computing Conference (IACC), pp. 701-705, Hyderabad, India, Jan 2017

     

    Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

     
    This site uses encryption for transmitting your passwords. ratmilwebsolutions.com