Synthetic High-Voltage Power Line Insulator Images

Citation Author(s):
Reinaldo
Bianchi
Centro Universitario FEI
Hericles
Ferraz
Universidade Federal de Uberlândia
Breno
Moura
Universidade Federal de Uberlândia
Rogério
Gonçalves
Universidade Federal de Uberlândia
Submitted by:
Reinaldo Bianchi
Last updated:
Thu, 04/25/2024 - 17:56
DOI:
10.21227/jfvg-v672
Data Format:
Images and Masks
License:
Creative Commons Attribution
437 Views
Categories:
Artificial Intelligence
Machine Learning
Power and Energy
Electric Utility
Image Processing
Computer Vision
Keywords:
High Voltage Insulators, Deep Learning, computer vision, object detection, Image Segmentation, image classification
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Abstract 

This database contains Synthetic High-Voltage Power Line Insulator Images.

There are two sets of images: one for image segmentation and another for image classification.

The first set contains images with different types of materials and landscapes, including the following landscape types: Mountains, Forest, Desert, City, Stream, Plantation. Each of the above-mentioned landscape types consists of 2,627 images per insulator type, which can be Ceramic, Polymeric or made of Glass, with a total of 47,286 distinct images.

The second file contains synthetic that simulate the most common impurities found on high-voltage transmission line insulator strings: salt, volcanic soot, bird excrement and a clean insulator. Each type of dirt has 3,608 images, with 1,202 images for each type of insulator material, with a total of 14,432 images.

 

Instructions: 

The dataset contains images. For segmentation, you have images and their masks. For classification, you have the images separated in folders for each class.

Funding Agency: 
CNPq, CELESC

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