A novel edge detection method for medicinal plant's leaf features extraction

Jibi G. Thanikkal (), Ashwani Kumar Dubey () and M. T. Thomas ()
Additional contact information
Jibi G. Thanikkal: Amity University Uttar Pradesh
Ashwani Kumar Dubey: Amity University Uttar Pradesh
M. T. Thomas: St. Thomas College

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 38, 448-458

Abstract: Abstract Morphological features-based leaf identification algorithms provide highly accurate results. But it is required a single-lined edge extraction algorithm for morphological feature generation. Existing edge extraction algorithms have heavy calculations and higher iteration steps to extract edges. The simplicity of the edge detection algorithm helps to reduce the complexity of the image feature extraction process. In this paper, a fast and straightforward novel edge detection algorithm is introduced in the spatial domain. In a single iteration over all the pixels of the image, our algorithm can achieve a better result than existing edge detection techniques. Also, this paper provides a novel algorithm for leaf shape, vein, apex, and base feature extraction techniques using the edge detection algorithm that can be utilized further for the classification and identification of medicinal plant species or any other plant species too. The performance measure of the proposed edge detection algorithm for leaf features is better as compared to the existing edge detection algorithms. This edge detection algorithm achieved 92% of accuracy and a PSNR rate of 10.88 dB with the time complexity of O(n*m), where n is the height and m is the width of the given image. The importance of medicinal plant identification and existing leaf identification techniques are also discussed in this paper.

Keywords: Image processing; Edge detection; Leaves classification; Morphological features; Plant identification (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-022-01814-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-022-01814-y

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-022-01814-y

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().