• PDF / 3,478,677 Bytes
• 26 Pages / 439.37 x 666.142 pts Page_size
• 33 Downloads / 201 Views

DOWNLOAD

REPORT

---

Deep neural network based Rider‑Cuckoo Search Algorithm for plant disease detection R. Cristin1 · B. Santhosh Kumar1 · C. Priya2 · K. Karthick3

© Springer Nature B.V. 2020

Abstract Agriculture is the main source of wealth, and its contribution is essential to humans. However, several obstacles faced by the farmers are due to different kinds of plant diseases. The determination and anticipation of plant diseases are the major concerns and should be considered for maximizing productivity. This paper proposes an effective image processing method for plant disease identification. In this research, the input image is subjected to the pre-processing phase for removing the noise and artifacts present in the image. After obtaining the pre-processed image, it is subjected to the segmentation phase for obtaining the segments using piecewise fuzzy C-means clustering (piFCM). Each segment undergoes a feature extraction phase in which the texture features are extracted, which involves information gain, histogram of oriented gradients (HOG), and entropy. The obtained texture features are subjected to the classification phase, which uses the deep belief network (DBN). Here, the proposed Rider-CSA is employed for training the DBN. The proposed Rider-CSA is designed by integrating the rider optimization algorithm (ROA) and Cuckoo Search (CS). The experimental results proved that the proposed Rider-CSA-DBN outperformed other existing methods with maximal accuracy of 0.877, sensitivity of 0.862, and the specificity of 0.877, respectively. Keywords  Plant disease · Piecewise fuzzy C-means clustering · Deep belief network · Classification · Texture features

1 Introduction In the Indian economy, Agriculture is considered as a crucial part, and also, it is considered as the source of income for numerous human beings in several countries (Kumar et  al. 2018). Agriculture is a basic need for human survival. Thus, it becomes essential to maximize the production of vegetables, crops, and fruits for the developing countries, * R. Cristin [email protected] 1

Department of CSE, GMR Institute of Technology, Rajam, AP 532127, India

2

Department of Information Technology, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai 600117, India

3

Department of EEE, GMR Institute of Technology, Rajam, AP 532127, India



13

Vol.:(0123456789)



R. Cristin et al.

such as India. Moreover, the quality of production should be high not only for productivity but also for attaining improved health. However, the quality and productivity of food get fraught by several factors, like disease spread, which could be avoided with early diagnosis. Most of these diseases are contagious, which can lead to the loss of crop yield (Singh 2018). Numerous varieties of food plants are harvested with the help of land’s environmental conditions, but simultaneously many issues are faced by the farmers, which involves water shortage, plant diseases, and natural disasters. However, most of these issues can be minimized by offering technical a