Publication Type:

Journal Article

Source:

Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 28, p.422-436 (2018)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042399467&doi=10.1007%2f978-3-319-71767-8_35&partnerID=40&md5=5a001e8af4d8ad854b4602e92bea113b

Abstract:

Diseases in any plant decrease the productivity and quality of product. Identification of plant leaf diseases by naked human eye is very difficult. Image processing techniques can identify the diseased leaf by preprocessing and classifying leaf unhealthy regions. This paper delivers an implementation on Mango leaf unhealthy region detection and classification. In the Proposed work Multiclass SVM is used for diseases classification and segmentation through k-means. The experimental results show the effectiveness of the proposed method in recognizing the diseases affected mango leaf.

Notes:

cited By 0

Cite this Research Publication

K. Srunitha and D. Bharathi, “Mango leaf unhealthy region detection and classification”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 422-436, 2018.