Paper Info
Title
Automatic recognition of scenes with power line wires in real life aerial images using DCT-based features.
Abstract
This paper presents results of power line scene detection methods that use new feature extraction/selection strategies based on Discrete Cosine Transform (DCT) of scenes obtained from aircraft-based cameras. Whenever a scene from an aircraft contains power lines (may that be a visible-light image or infrared), the spectrum image or DCT matrix naturally exhibits coefficients with large magnitudes. On the other hand, since the direction of cables is arbitrary, the location of the DCT extrema may appear in different positions. This work attacks the problem of extracting signatures from the DCT coefficients by systematically changing the DCT matrix sizes and applying known classifiers to the DCT sub-matrices. These sub-matrices were selected at six different sizes (4 × 4, 8 × 8, 16 × 16, 32 × 32, 64 × 64, 128 × 128) with three types of starting points: (i) top-left corner (around DC), (ii) bottom-right corner (high frequency) and (iii) block-wise scanning the complete DCT matrix. A thorough dataset that contains thousands of aerial images with cables are used for testing the efficiencies of these DCT region selection approaches. Fast and successful detection performances are obtained and presented.
Year
DOI
Venue
2018
10.1016/j.dsp.2017.10.012
Digital Signal Processing
Keywords
Field
DocType
DCT,Feature extraction/selection,Classification,Power line wires recognition,Computer vision,Image features
Computer vision,Pattern recognition,Matrix (mathematics),Discrete cosine transform,Region selection,Maxima and minima,Electric power transmission,Feature extraction,Artificial intelligence,Mathematics
Journal
Volume
ISSN
Citations 
77
1051-2004
0
PageRank 
References 
Authors
0.34
21
2
Name
Order
Citations
PageRank
Omer Emre Yetgin111.03
Ömer Nezih Gerek211819.51