Logo

Segmentation of satellite imagery based on pulse-coupled neural network

Qayyum, Abdul and Malik, Aamir Saeed and Mohamad Saad, Mohamad Naufal (2015) Segmentation of satellite imagery based on pulse-coupled neural network. In: 2015 International Conference on Space Science and Communication (IconSpace), Langkawi, Malaysia.

[img] PDF
453Kb

Abstract

Vegetation encroachment under overhead high voltage power lines and its monitoring is a challenging problem for electricity distribution companies. Blackout can occurs if proper monitoring of vegetation is not done. The uninterrupted electric power supply is vital for industries, businesses, and daily life. Therefore, it is mandatory for electricity companies to monitor the vegetation/trees near power lines to avoid the blackouts. Pulse-coupled neural network (PCNN) considered as differently from converntial neural networks used in many signal and image processing applications. The main step to develop the automatic detection of vegetation is performing an image segmentation which is normally used to identify or marking of vegetation from the acquired images. We apply PCNN for image segmentation on satellite images for vegetation monitoring purposes and compared the performance with a thresholding image segmentation method with Pulse coupled neural network. The results show that PCNN produce outperform as compared to the thresholding method in terms of detection accuracy.

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > Q Science (General)
T Technology > T Technology (General)
Academic Subject One:Academic Department - Electrical And Electronics - Communications - Digital Communications - Digital Signal Processing
Departments / MOR / COE:Departments > Electrical & Electronic Engineering
Mission Oriented Research > Health
ID Code:11811
Deposited By: Dr Aamir Saeed Malik
Deposited On:07 Oct 2016 01:42
Last Modified:07 Oct 2016 01:42

Repository Staff Only: item control page

Document Downloads

More statistics for this item...