Development of an Improved Algorithm for Power Line Detection in Optical Images Using Frangi Filter and First Order Derivative Of Gaussian

Description

– Development of an Improved Algorithm for Power Line Detection in Optical Images Using Frangi Filter and First Order Derivative Of Gaussian –

Download Development of an Improved Algorithm for Power Line Detection in Optical Images Using Frangi Filter and First Order Derivative Of Gaussian. Electrical and Computer Engineering students who are writing their projects can get this material to aid their research work.

Abstract

This research presents the development of a frangi filter and first-order derivative of gaussian (ff-fdog) based power line detection (pld) algorithm as an improvement to the standard pld algorithm.

Vision-based pld is important in obstacle avoidance in low-altitude flight and also in the surveillance and maintenance of electrical infrastructure.

The need for high and real-time detection rates as well as low false alarm in noisy and cluttered images makes it a challenging task.

Matched filterand first-order derivative of gaussian (mf-fdog) based pld algorithm was developed to handle limitations associated with the standard pld algorithm in terms of its ability to automatically select a problem specific threshold in its edge detection.

Introduction

Electricity is vital for the activities of modern-day societies and effective monitoring and maintenance of power lines are needed to secure uninterrupted distribution of electricity, (matikainen et al., 2016).

Electricity companies spend a significant budget on power line inspections, and continuously pursue new approaches to reduce inspection cost (martinez et al., 2014).

For example, ergon energy, one of the top electricity companies in australia, spends $80 million a year inspecting and managing vegetation that encroaches on power line assets (li et al., 2010).

Inspection of high voltage power lines can be very dangerous if performed by humans, very expensive if performed by helicopters and damaging on the cable if performed by the roll robot. Unmanned aerial vehicle (uav) is, therefore, one of the best instruments for detailed power line inspection tasks (zhou et al., 2016).

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