JOURNAL ARTICLE

AUTOMATIC SHADOW DETECTION IN AERIAL AND TERRESTRIAL IMAGES

Vander L. S. FreitasBarbara Maximino da Fonseca ReisAntônio Maria Garcia Tommaselli

Year: 2017 Journal:   Boletim de Ciências Geodésicas Vol: 23 (4)Pages: 578-590   Publisher: Universidade Federal do Paraná

Abstract

Abstract: Shadows exist in almost all aerial and outdoor images, and they can be useful for estimating Sun position estimation or measuring object size. On the other hand, they represent a problem in processes such as object detection/recognition, image matching, etc., because they may be confused with dark objects and change the image radiometric properties. We address this problem on aerial and outdoor color images in this work. We use a filter to find low intensities as a first step. For outdoor color images, we analyze spectrum ratio properties to refine the detection, and the results are assessed with a dataset containing ground truth. For the aerial case we validate the detections depending of the hue component of pixels. This stage takes into account that, in deep shadows, most pixels have blue or violet wavelengths because of an atmospheric scattering effect.

Keywords:
Artificial intelligence Computer vision Computer science Shadow (psychology) Pixel Ground truth Hue Object detection Aerial image Remote sensing Filter (signal processing) Image (mathematics) Pattern recognition (psychology) Geology

Metrics

17
Cited By
1.14
FWCI (Field Weighted Citation Impact)
7
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Satellite Image Processing and Photogrammetry
Physical Sciences →  Engineering →  Ocean Engineering
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
3D Surveying and Cultural Heritage
Physical Sciences →  Earth and Planetary Sciences →  Geology

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