Paper Info
Title
Energy efficient mobile vision system for plant leaf disease identification
Abstract
Close monitoring, proper control and management of plant diseases are essential in the efficient cultivation of crops. This paper presents a scheme that uses mobile phones for real-time on-field imaging of diseased plants followed by disease diagnosis via analysis of visual phenotypes. A threshold based offloading scheme is employed for judicious sharing of the computational load between the mobile device and a central server at the plant pathology laboratory, thereby offering a trade-off between the power consumption in the mobile device and the transmission cost. The part of the processing carried out in the mobile device includes leaf image segmentation and spotting of disease patch using improved k-means clustering. The algorithm is simple and hence suitable for Android based mobile devices. The segmented image is subsequently communicated to the central server. This ensures reduced transmission cost compared to that in transmitting full leaf image.
Year
DOI
Venue
2014
10.1109/WCNC.2014.6953083
Wireless Communications and Networking Conference
Keywords
Field
DocType
Android (operating system),agriculture,crops,image segmentation,mobile computing,mobile handsets,Android based mobile devices,central server,disease diagnosis,energy efficient mobile vision system,k-means clustering,leaf image segmentation,mobile phones,plant leaf disease identification,plant pathology laboratory,real-time on-field imaging,transmission cost,visual phenotypes,Mobile vision,m-Agriculture,plant disease diagnosis,power conservation,unsupervised segmentation
Mobile computing,Wireless,Android (operating system),Mobile station,Computer science,Server,Computer network,Image segmentation,Real-time computing,Mobile device,Mobile telephony
Conference
ISSN
Citations 
PageRank 
1525-3511
7
0.65
References 
Authors
8
3
Name
Order
Citations
PageRank
Shitala Prasad170.65
Sateesh Kumar Peddoju2121.59
Debashis Ghosh381.33